A. Willsky

Dmitry M. Malioutov, Alan S. Willsky, Jason K. Johnson, 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

Describing Visual Scenes using Transformed Dirichlet Processes

Antonio Torralba, William T. Freeman, Alan S. Willsky, 2005, NIPS.

Nonparametric Bayesian Identification of Jump Systems with Sparse Dependencies

Michael I. Jordan, Alan S. Willsky, Emily B. Fox, 2009 .

A new class of upper bounds on the log partition function

Martin J. Wainwright, Tommi S. Jaakkola, Alan S. Willsky, 2002, IEEE Transactions on Information Theory.

Efficient multiscale regularization with applications to the computation of optical flow

W. Clem Karl, Alan S. Willsky, Mark R. Luettgen, 1994, IEEE Trans. Image Process..

Recursive and iterative estimation algorithms for multiresolution stochastic processes

K. C. Chou, A. Benveniste, A. Willsky, 1989, Proceedings of the 28th IEEE Conference on Decision and Control,.

An estimation-based approach to the reconstruction of optical flow

A. Willsky, B. Levy, A. Rougée, 1987 .

Redundancy Relations and Robust Failure Detection

A. Willsky, X. Lou, G. Verghese, 1985 .

MAP estimation via agreement on (hyper)trees: Message-passing and linear programming pdf

Martin J. Wainwright, Tommi S. Jaakkola, Alan S. Willsky, 2005, ArXiv.

Rank-Sparsity Incoherence for Matrix Decomposition

Pablo A. Parrilo, Venkat Chandrasekaran, Sujay Sanghavi, 2009, SIAM J. Optim..

Combining and updating of local estimates and regional maps along sets of one-dimensional tracks

A. Willsky, D. Castañón, B. Levy, 1982 .

Random Cascades on Wavelet Trees and Their Use in Analyzing and Modeling Natural Images

Eero P. Simoncelli, A. Willsky, M. Wainwright, 2001 .

On the fixed-interval smoothing problem †

A. Willsky, N. Sandell, J. Wall, 1981 .

Context models and out-of-context objects

Antonio Torralba, Alan S. Willsky, Myung Jin Choi, 2012, Pattern Recognition Letters.

MAP estimation via agreement on trees: message-passing and linear programming

Martin J. Wainwright, Tommi S. Jaakkola, Alan S. Willsky, 2005, IEEE Transactions on Information Theory.

Depth from Familiar Objects: A Hierarchical Model for 3D Scenes

Antonio Torralba, William T. Freeman, Alan S. Willsky, 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

Tree-reweighted belief propagation algorithms and approximate ML estimation by pseudo-moment matching

Martin J. Wainwright, Tommi S. Jaakkola, Alan S. Willsky, 2003, AISTATS.

Time-varying parametric modeling of speech☆

A. Willsky, A. Oppenheim, M. Hall, 1983 .

An Estimation Theoretic Perspective on Image Processing and the Calculation of Optical Flow

T. M. Chin, M. Luettgen, A. Willsky, 1992 .

Major Advances and Emerging Developments of Graphical Models [From the Guest Editors]

Martin J. Wainwright, Michael I. Jordan, Alan S. Willsky, 2010 .

Signals and Systems

A. Willsky, A. Oppenheim, 2004 .

Discrete-time Markovian-jump linear quadratic optimal control

A. Willsky, D. Castañón, H. Chizeck, 1986 .

Finite group homomorphic sequential system

A. Willsky, R. Brockett, 1972 .

Signals & systems (2nd ed.)

Alan V. Oppenheim, Alan S. Willsky, S. Hamid Nawab, 1996 .

On the invertibility of linear systems

A. Willsky, 1974 .

Particle filtering under communications constraints

A. Willsky, J. Fisher, A. Ihler, 2005, IEEE/SP 13th Workshop on Statistical Signal Processing, 2005.

Upper Extremity Limb Function Discrimination Using EMG Signal Analysis

A. Willsky, P. Doerschuk, Donald E. Gustafon, 1983, IEEE Transactions on Biomedical Engineering.

Multiscale Autoregressive Processes, Part I:

A. Benveniste, A. Willsky, M. Basseville, 1992 .

Latent variable graphical model selection via convex optimization

Pablo A. Parrilo, Venkat Chandrasekaran, Alan S. Willsky, 2010, 2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

Tree-based reparameterization framework for analysis of sum-product and related algorithms

Martin J. Wainwright, Tommi S. Jaakkola, Alan S. Willsky, 2003, IEEE Trans. Inf. Theory.

Nonparametric Belief Propagation and Facial Appearance Estimation

Erik B. Sudderth, W. Freeman, A. Willsky, 2002 .

Hierarchical aggregation of linear systems with multiple time scales

A. Willsky, S. Sastry, D. Castanon, 1981, 1981 20th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes.

Hierarchical aggregation of singularly perturbed finite state Markov processes

S. Sastry, A. Willsky, D. Castañón, 1983 .

A multiscale approach for estimating solute travel time distributions

A. Willsky, D. Mclaughlin, M. Daniel, 2000 .

Visual Hand Tracking Using Nonparametric Belief Propagation

Michael I. Mandel, William T. Freeman, Alan S. Willsky, 2004, 2004 Conference on Computer Vision and Pattern Recognition Workshop.

Estimating surface reflectance properties from images under unknown illumination

Edward H. Adelson, Alan S. Willsky, Ron O. Dror, 2001, IS&T/SPIE Electronic Imaging.

Nonparametric belief propagation

William T. Freeman, Alan S. Willsky, Alexander T. Ihler, 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

Multiscale stochastic modeling for tractable inference and data assimilation

Jason K. Johnson, A. Willsky, V. Chandrasekaran, 2008 .

Nonparametric belief propagation for self-calibration in sensor networks

A.S. Willsky, J.W. Fisher, R.L. Moses, 2004, Third International Symposium on Information Processing in Sensor Networks, 2004. IPSN 2004.

Learning Gaussian Tree Models: Analysis of Error Exponents and Extremal Structures

Vincent Y. F. Tan, Anima Anandkumar, Alan S. Willsky, 2009, IEEE Transactions on Signal Processing.

Binary and ternary flows for image segmentation

A. Willsky, A. Yezzi, A. Tsai, 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

Homotopy continuation for sparse signal representation

Dmitry M. Malioutov, Alan S. Willsky, Müjdat Çetin, 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

Statistical and Information-Theoretic Methods for Self-Organization and Fusion of Multimodal, Networked Sensors

Martin J. Wainwright, John W. Fisher, Alan S. Willsky, 2002, Int. J. High Perform. Comput. Appl..

A survey of design methods for failure detection in dynamic systems

Alan S. Willsky, A. Willsky, 1976, Autom..

A generalized likelihood ratio approach to state estimation in linear systems subjects to abrupt changes

A. Willsky, H. Jones, 1974, CDC 1974.

Joint Modeling of Multiple Related Time Series via the Beta Process

Michael I. Jordan, Alan S. Willsky, Emily B. Fox, 2011, 1111.4226.

Developing a tempered HDP-HMM for Systems with State Persistence

Michael I. Jordan, Alan S. Willsky, Emily B. Fox, 2007 .

Reconstruction from projections based on detection and estimation of objects--Parts I and II: Performance analysis and robustness analysis

A. Willsky, D. Rossi, 1984 .

Reconstructing Binary Polygonal Objects from Projections: A Statistical View

Peyman Milanfar, W. Clem Karl, Alan S. Willsky, 1994, CVGIP Graph. Model. Image Process..

A geometric projection-space reconstruction algorithm

Jerry L Prince, A. Willsky, 1990 .

Bayesian Nonparametric Inference of Switching Dynamic Linear Models

Michael I. Jordan, Alan S. Willsky, Emily B. Fox, 2010, IEEE Transactions on Signal Processing.

High-Dimensional Gaussian Graphical Model Selection: Tractable Graph Families pdf

Vincent Y. F. Tan, Anima Anandkumar, Alan S. Willsky, 2011, ArXiv.

Feedback Message Passing for Inference in Gaussian Graphical Models

Venkat Chandrasekaran, Anima Anandkumar, Alan S. Willsky, 2010, IEEE Transactions on Signal Processing.

Embedded trees: estimation of Gaussian Processes on graphs with cycles

Martin J. Wainwright, Alan S. Willsky, Erik B. Sudderth, 2004, IEEE Transactions on Signal Processing.

A multiresolution methodology for signal-level fusion and data assimilation with applications to remote sensing

A. Willsky, M. Daniel, 1997, Proc. IEEE.

Kalman filtering and Riccati equations for descriptor systems

A. Willsky, R. Nikoukhah, B. Levy, 1992 .

A large-deviation analysis for the maximum likelihood learning of tree structures

Lang Tong, Vincent Y. F. Tan, Anima Anandkumar, 2009, 2009 IEEE International Symposium on Information Theory.

An Efficient Message-Passing Algorithm for Optimizing Decentralized Detection Networks

Alan S. Willsky, O. Patrick Kreidl, O. P. Kreidl, 2010, IEEE Transactions on Automatic Control.

Modeling And Estimation Of Multiresolution Stochastic Processes And Random Fields

K. C. Chou, M. Luettgen, A. Willsky, 1991, Proceedings of the Seventh Workshop on Multidimensional Signal Processing.

A Tree-Based Context Model for Object Recognition

Antonio Torralba, Alan S. Willsky, Myung Jin Choi, 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Consistent and efficient reconstruction of latent tree models

A. Willsky, Anima Anandkumar, V. Tan, 2010, 2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

Surface Reflectance Estimation and Natural Illumination Statistics

Edward H. Adelson, Alan S. Willsky, Ron O. Dror, 2001 .

A Sticky HDP-HMM With Application to Speaker Diarization

Michael I. Jordan, Alan S. Willsky, Emily B. Fox, 2009, 0905.2592.

Incorporating Spatial Priors into an Information Theoretic Approach for fMRI Data Analysis

John W. Fisher, William M. Wells, Alan S. Willsky, 2000, MICCAI.

Reconstructing Convex Sets from Support Line Measurements

Jerry L. Prince, Alan S. Willsky, Jerry L Prince, 1990, IEEE Trans. Pattern Anal. Mach. Intell..

Estimation algorithms for reconstructing a convex set given noisy measurments of its support lines

Jerry L Prince, A. Willsky, 1986 .

Convex set estimation from support line measurements and applications to target reconstruction from laser radar data

Sanjeev R. Kulkarni, Alan S. Willsky, Avinash S. Lele, 1990, Photonics West - Lasers and Applications in Science and Engineering.

A sequential method for spline approximation with variable knots. [recursive piecewise polynomial signal processing]

A. Willsky, A. M. Muth, 1978 .

Limit laws for random spatial graphical models

Anima Anandkumar, Alan S. Willsky, Joseph E. Yukich, 2010, 2010 IEEE International Symposium on Information Theory.

The Sticky HDP-HMM: Bayesian Nonparametric Hidden Markov Models with Persistent States

Michael I. Jordan, Emily B. Fox, Erik B. Sudderth, 2009 .

High-dimensional structure estimation in Ising models: Local separation criterion

Vincent Y. F. Tan, Alan S. Willsky, Furong Huang, 2011, 1107.1736.

Multiscale representations of Markov random fields

W. Clem Karl, Alan S. Willsky, Robert R. Tenney, 1993, IEEE Trans. Signal Process..

Semidefinite Descriptions of the Convex Hull of Rotation Matrices

Pablo A. Parrilo, Alan S. Willsky, James Saunderson, 2014, SIAM J. Optim..

Convex Solution to a Joint Attitude and Spin-Rate Estimation Problem

A. Willsky, P. Parrilo, J. Saunderson, 2014, 1410.2841.

A Large-Deviation Analysis of the Maximum-Likelihood Learning of Markov Tree Structures

Lang Tong, Vincent Y. F. Tan, Anima Anandkumar, 2009, IEEE Transactions on Information Theory.

Optical flow computation via multiscale regularization

M. Luettgen, A. Willsky, Decision Systems., 1992 .

Low-Rank Variance Approximation in GMRF Models: Single and Multiscale Approaches

Dmitry M. Malioutov, Alan S. Willsky, Jason K. Johnson, 2008, IEEE Transactions on Signal Processing.

Multiscale Gaussian Graphical Models and Algorithms for Large-Scale Inference

A. Willsky, M. Choi, 2007, 2007 IEEE/SP 14th Workshop on Statistical Signal Processing.

Analyzing Hogwild Parallel Gaussian Gibbs Sampling

Matthew J. Johnson, Alan S. Willsky, James Saunderson, 2013, NIPS.

Sampling GMRFs by Subgraph Correction

A. Willsky, Y. Liu, 2013 .

Distributed Occlusion Reasoning for Tracking with Nonparametric Belief Propagation

Michael I. Mandel, William T. Freeman, Alan S. Willsky, 2004, NIPS.

A Comprehensive Approach to Fusion for Microsensor Networks: Distributed and Hierarchical Inference, Communication, and Adaption REPORT DOCUMENTATION PAGE

John N. Tsitsiklis, Tommi S. Jaakkola, Sergio Verdu, 2000 .

Superresolution source localization through data-adaptive regularization

A. Willsky, J. Fisher, D. Malioutov, 2002, Sensor Array and Multichannel Signal Processing Workshop Proceedings, 2002.

Tree-based reparameterization analysis of belief propagation and related algorithms for approximate inference on graphs with cycles

T. Jaakkola, A. Willsky, M. Wainwright, 2002, Proceedings IEEE International Symposium on Information Theory,.

Stability and stabilization of discrete event dynamic systems

A. Willsky, C. Özveren, P. Antsaklis, 1991 .

Estimation for bilinear stochastic systems

S. Marcus, A. Willsky, 1975 .

Some Estimation Problems on Lie Groups

A. Willsky, 1973 .

Tree consistency and bounds on the performance of the max-product algorithm and its generalizations

Martin J. Wainwright, Tommi S. Jaakkola, Alan S. Willsky, 2004, Stat. Comput..

Stabilized inverse diffusion equations and segmentation of vector-valued images

Alan S. Willsky, Hamid Krim, Ilya Pollak, 1998, Proceedings 1998 International Conference on Image Processing. ICIP98 (Cat. No.98CB36269).

Stochastic Variational Inference for Bayesian Time Series Models

Matthew J. Johnson, Alan S. Willsky, A. Willsky, 2014, ICML.

Curve evolution implementation of the Mumford-Shah functional for image segmentation, denoising, interpolation, and magnification

Anthony J. Yezzi, Alan S. Willsky, Andy Tsai, 2001, IEEE Trans. Image Process..

Image segmentation and edge enhancement with stabilized inverse diffusion equations

Alan S. Willsky, Hamid Krim, Ilya Pollak, 2000, IEEE Trans. Image Process..

Digital Signal Processing and Control and Estimation Theory: Points of Tangency, Areas of Intersection, and Parallel Directions

Alan S. Willsky, A. Willsky, 1979 .

Analysis of bilinear noise models in circuits and devices

S. Marcus, A. Willsky, 1976 .

The use of group-theoretic concepts in solving problems in estimation and control

A. Willsky, 1976, 1976 IEEE Conference on Decision and Control including the 15th Symposium on Adaptive Processes.

Estimation of Time-Invariant Random Fields via Observations from a Moving Point Sensor.

A. Willsky, P. Kam, 1977 .

Estimation for Rotational Processes with One Degree of Freedom

A. Willsky, J. Lo, 1972 .

Some modeling and estimation problems involving space-time stochastic processes

A. Willsky, P. Kam, 1976, 1976 IEEE Conference on Decision and Control including the 15th Symposium on Adaptive Processes.

Multiple-hypothesis and graph-based tracking for kinematic and identity fusion

Alan S. Willsky, Stefano P. Coraluppi, Craig A. Carthel, 2018, 2018 IEEE Aerospace Conference.

Bayesian nonparametric hidden semi-Markov models

Matthew J. Johnson, Alan S. Willsky, A. Willsky, 2012, J. Mach. Learn. Res..

Dirichlet Posterior Sampling with Truncated Multinomial Likelihoods

Matthew J. Johnson, A. Willsky, 2012, 1208.6537.

Tree-structured statistical modeling via convex optimization

Pablo A. Parrilo, Venkat Chandrasekaran, Alan S. Willsky, 2011, IEEE Conference on Decision and Control and European Control Conference.

Modeling and estimation of multiresolution stochastic processes

Michèle Basseville, Albert Benveniste, Alan S. Willsky, 1992, IEEE Trans. Inf. Theory.

Wavelet Transforms, Multiresolution Dynamical Models, and Multigrid Estimation Algorithms

K. C. Chou, A. Benveniste, A. Willsky, 1990 .

Multiscale Riccati equations and a two-sweep algorithm for the optimal fusion of multiresolution data

K. C. Chou, A. Willsky, Decision Systems., 1990 .

Reconstruction from projections based on detection and estimation of objects

Alan S. Willsky, David J. Rossi, A. Willsky, 1983, ICASSP.

THE DIGITAL IMPLEMENTATION OF COWTROL COMPENSATORS: THE COrnICIENT WORDLFNGTR ISSUE

P K Houpt, Alan S. Willsky, Paul Moroney, 1979 .

A scattering framework for decentralized estimation problems

George C. Verghese, Alan S. Willsky, Bernard C. Levy, 1983, Autom..

Modeling and estimation for a class of multiresolution random fields

Peyman Milanfar, Alan S. Willsky, Robert R. Tenney, 1994, Proceedings of 1st International Conference on Image Processing.

Hierarchical reconstruction using geometry and sinogram restoration

Jerry L. Prince, Alan S. Willsky, Jerry L Prince, 1993, IEEE Trans. Image Process..

An estimation-theoretic technique for motion-compensated synthetic-aperture array imaging

C. L. Logan, Alan S. Willsky, Hamid Krim, 1998, Proceedings 1998 International Conference on Image Processing. ICIP98 (Cat. No.98CB36269).

Random cascades on wavelet trees and their use in analyzing and modeling natural images

Martin J. Wainwright, Eero P. Simoncelli, Alan S. Willsky, 2000, SPIE Optics + Photonics.

Krylov Subspace Estimation

Michael K. Schneider, Alan S. Willsky, A. Willsky, 2000, SIAM J. Sci. Comput..

Applications of a Regulator Theory for Discrete-Event Dynamic Systems

Alan S. Willsky, C. M. Ozveren, A. Willsky, 1991 .

Output stabilizability of discrete event dynamic systems

A. Willsky, C. Ozveren, 1989, Proceedings of the 28th IEEE Conference on Decision and Control,.

Efficient implementations of 2-D noncausal IIR filters

A. Willsky, M. Daniel, 1997 .

Sampling theorems for two-dimensional isotropic random fields

Ahmed H. Tewfik, Alan S. Willsky, Bernard C. Levy, 1988, IEEE Trans. Inf. Theory.

An eigenstructure approach for the retrieval of cylindrical harmonics

A. Willsky, B. Levy, A. Tewfik, 1987 .

Expectation-maximization algorithms for image processing using multiscale models and mean- field theory, with applications to laser radar range profiling and segmentation

Jun Zhang, Alan S. Willsky, Andy Tsai, 2001 .

MULTISCALE METHODS AND MEAN FIELD THEORY IN EM PROCEDURES FOR IMAGE PROCESSING

A. Willsky, A. Tsai, Jun Zhang, .

Modeling and Estimation of Multiresolution

K. C. Chou, A. Benveniste, A. Willsky, 1992 .

A multi-resolution approach for imaging hydraulic conductivity

Dennis McLaughlin, Alan S. Willsky, David J. Rossi, 1995, Proceedings., International Conference on Image Processing.

A MULTI-RESOLUTION , PROBABILISTIC APPROACH TO TWO- DIMENSIONAL INVERSE CONDUCTIVITY PROBLEMS*

K. C. Chou, A. Willsky, 1989 .

MCMC curve sampling and geometric conditional simulation

John W. Fisher, Alan S. Willsky, Jonathan Kane, 2008, Electronic Imaging.

Loopy Belief Propagation: Convergence and Effects of Message Errors

John W. Fisher, Alan S. Willsky, Alexander T. Ihler, 2005, J. Mach. Learn. Res..

Estimation and detection of signals in multiplicative noise (Corresp.)

Alan S. Willsky, A. Willsky, 1975, IEEE Trans. Inf. Theory.

Stochastic Control of Rotational Processes with One Degree of Freedom

A. Willsky, J. Lo, 1975 .

Estimation and detection of signals in multiplicative noise

A. Willsky, 1974, CDC 1974.

Estimation for rotational processes with one degree of freedom--Part I: Introduction and continuous-

A. Willsky, J. Lo, 1975 .

A distributed and iterative method for square root filtering in space-time estimation

T. M. Chin, W. Clem Karl, Alan S. Willsky, 1995, Autom..

Solution and linear estimation of 2-D nearest-neighbor models

A. Willsky, B. Levy, M. Adams, 1990 .

Boundary-value descriptor systems: well-posedness, reachability and observability

A. Willsky, R. Nikoukhah, B. Levy, 1987 .

A multiscale hypothesis testing approach to anomaly detection and localization from noisy tomographic data

W. Clem Karl, Alan S. Willsky, Austin B. Frakt, 1998, IEEE Trans. Image Process..

The stochastic control of the F-8C aircraft using a multiple model adaptive control (MMAC) method--Part I: Equilibrium flight

Michael Athans, Alan S. Willsky, David A. Castanon, 1977 .

Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science Proposal for Thesis Research in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

A. Willsky, S. Kulkarni, J. Fisher, 2022 .

Graph structure and recursive estimation of noisy linear relations

Ramine Nikoukhah, Alan S. Willsky, Bernard C. Levy, 1992 .

OPTIMUM AND SUBOPTIMUM ARRAY PROCESSING FOR THE ESTIMATION OF SUPERIMPOSED SIGNALS

A. Willsky, Decision Systems., B. Levy, 1987 .

Classification using geometric level sets Citation

A. Willsky, K. Varshney, 2010 .

AUGUST 1986 LIDS-P-1600 Estimation for Boundary-Value Descriptor Systems 1

A. Willsky, R. Nikoukhah, B. Levy, 2006 .

Realization of acausal weighting patterns with boundary-value descriptor systems

A. Willsky, R. Nikoukhah, B. Levy, 1991 .

Realization Theory for Deterministic Boundary-Value Descriptor Systems

A. Willsky, R. Nikoukhah, B. Levy, 1990 .

Reachability, observability, and minimality for shift-invariant two-point boundary-value descriptor systems

A. Willsky, R. Nikoukhah, B. Levy, 1989 .

Stability, stochastic stationarity, and generalized Lyapunov equations for two-point boundary-value descriptor systems

A. Willsky, R. Nikoukhah, B. Levy, 1989 .

Estimation for boundary-value descriptor systems

A. Willsky, R. Nikoukhah, B. Levy, 1989 .

OBJECT SHAPE ESTIMATION FROM TOMOGRAPHIC MEASUREMENTS--A PERFORMANCE ANALYSIS*

A. Willsky, D. Rossi, D. Spielman, 1989 .

Failure detection and identification in linear time-invariant systems

A. Willsky, M. Massoumnia, G. Verghese, 1986 .

OBJECT SHAPE ESTIMATION FROK 1TKGORAPHIC EASUREMENS - A PERFORANCE ANALYSIS 1

A. Willsky, D. Rossi, 1987 .

Learning dimensionality-reduced classifiers for information fusion Citation

A. Willsky, K. Varshney, 2009 .

Nonuniform array processing via the polynomial approach

A. Willsky, B. Levy, A. Weiss, 1989 .

A ug 2 00 5 1 MAP estimation via agreement on trees : Message-passing and linear programming

T. Jaakkola, A. Willsky, M. Wainwright, 2022 .

Supervised learning of classifiers via level set segmentation

A. Willsky, K. Varshney, 2008, IEEE Workshop on Machine Learning for Signal Processing.

Scaling laws for learning high-dimensional Markov forest distributions

A. Willsky, Anima Anandkumar, V. Tan, 2010, 2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

Linear estimation of boundary value stochastic processes-- Part I: The role and construction of complementary models

A. Willsky, B. Levy, M. Adams, 1984 .

Optic flow estimation inside a bounded domain

A. Willsky, B. Levy, A. Rougée, 1986 .

Structural Decomposition of Multiple Time Scale Markov Processes

J. R. Rohlicek, A. Willsky, 1987 .

Multiscale Statistical Signal Processing: Stochastic Processes Indexed by Trees

K. C. Chou, A. Benveniste, A. Willsky, 1990 .

Nonparametric Bayesian Identification of Jump Systems with Sparse Dependencies

Michael I. Jordan, Alan S. Willsky, Emily B. Fox, 2009 .

Estimation and filter stability of stochastic delay systems

Alan S. Willsky, A. Willsky, R. Kwong, 1978 .

Algebraic Structure and Finite Dimensional Nonlinear Estimation

Alan S. Willsky, Steven I. Marcus, S. Marcus, 1978 .

High Dimensional Structure Learning of Ising Models on Sparse Random Graphs

A. Willsky, Anima Anandkumar, V. Tan, 2010, 1011.0129.

Asymptotic orders of reachability in perturbed linear systems

A. Willsky, C. Özveren, G. Verghese, 1988 .

Asymptotic orders of reachability in perturbed linear systems

Alan Willsky, George Verghese, A. Willsky, 1987, 26th IEEE Conference on Decision and Control.

Adaptation of a fast optimal interpolation algorithm to the mapping of oceanographic data

Carl Wunsch, Paul Fieguth, Alan S. Willsky, 1997 .

Kalman filtering and Riccati equations for descriptor systems

A. Willsky, R. Nikoukhah, B. Levy, 1990, 29th IEEE Conference on Decision and Control.

A Multiscale Approach to Sensor Fusion and the Solution of Linear Inverse Problems

Eric L. Miller, Alan S. Willsky, A. Willsky, 1995 .

Wavelet based methods for multiscale tomographic reconstruction

Alan S. Willsky, William Clement Karl, A. Willsky, 1994, Proceedings of 16th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Bayesian Design of Decision Rules for Failure Detection

Alan Willsky, A. Willsky, E. Chow, 1984, IEEE Transactions on Aerospace and Electronic Systems.

Scale Space Analysis by Stabilized Inverse Diffusion Equations

Alan S. Willsky, Hamid Krim, Ilya Pollak, 1997, Scale-Space.

How do the structure and the parameters of Gaussian tree models affect structure learning?

A. Willsky, Anima Anandkumar, V. Tan, 2009, 2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

Linear estimation for 2-D nearest-neighbor models

A. Willsky, Decision Systems., B. Levy, 1988 .

Laboratory for Information and Decision Systems M.I.T., Cambridge, MA. 02139

A. Willsky, Anne Rougte, Bernard C. Levyv, 1986 .

Computationally Eecient Steady-state Multiscale Estimation for 1-d Diiusion Processes

A. Willsky, P. Fieguth, T. Ho, 2008 .

Adaptation of a fast optimal interpolation algorithmto the mapping of oceanographic dataDimitris

A. Willsky, P. Fieguth, C. Wunsch, 1997 .

A NEW PAFALLEL SMOOTHING ALGORITHM

A. Willsky, B. Levy, A. Tewfik, 1986 .

LIDS-P-2022 MODELING AND ESTIMATION OF MULTIRESOLTUTION STOCHASTIC PROCESSES

K. C. Chou, A. Willsky, R. Nikoukhah, 2022 .

velet-I3 ased ethod for Multiscale Tomographic Reconstruction

A. Willsky, W. Karl, M. Bhatia, 1996 .

Robust multiscale representation of processes and optimal signal reconstruction

Hamid Krim, A. S. Willsky, A. Willsky, 1994, Proceedings of IEEE-SP International Symposium on Time- Frequency and Time-Scale Analysis.

Estimation and Control for a Sensor Moving along a One-Dimensional Track,

Pooi Yuen Kam, Alan S. Willsky, A. Willsky, 1980 .

Optimal filtering and filter stability of linear stochastic delay systems

A. Willsky, A. Willsky, R. Kwong, 1976, 1976 IEEE Conference on Decision and Control including the 15th Symposium on Adaptive Processes.

MAX-WEIGHT DISCRIMINATIVE FORESTS

A. Willsky, John W. Fisher III, V. Tan, 2009 .

Sample Complexity for Topology Estimation in Networks of LTI Systems

A. Willsky, V. Tan, 2011 .

High Resolution Pursuit for Feature Extraction Contact

W. Karl, A. Willsky, S. Mallat, 2022 .

A PDE approach to image smoothing and magnification using the Mumford-Shah functional

A. Willsky, A. Yezzi, A. Tsai, 2000, Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154).

Introduction to the special issue on wavelet transforms and multiresolution signal analysis

Stéphane Mallat, Alan S. Willsky, Ingrid Daubechies, 1992, IEEE Transactions on Information Theory.

e, Statisti ased Inversion Scheme cattering Problems

A. Willsky, E. Miller, 1996 .

Conditions for scale-based decompositions in singularly perturbed systems

A. Willsky, G. Verghese, P. Coxson, 1988 .

Projection operators in correlated noise fields

A. Willsky, Decision Systems., H. Krim, 1995 .

Asymptotic analysis, approximation, and aggregation methods for stochastic hybrid systems

Alan S. Willsky, Bernard C. Levy, M. Coderch, 1980 .

( SPECIAL SECTION - DISTRIBUTED SIGNAL PROCESSING IN SENSOR NETWORKS )

Rabab K. Ward, Petar M. Djuric, Ling Guan, 2006 .

Linear estimation of two-point boundary value processes

A. Willsky, Decision Systems., B. Levy, 1983 .

Parallel Smoothing 1

A. Willsky, B. Levy, A. Tewfik, 2022 .

Tracking and restrictability in discrete-event dynamic systems

A. Willsky, C. Ozveren, A.S. Willsky, 1990, 29th IEEE Conference on Decision and Control.

Kalman filtering and Riccati equations for multiscale processes

Alan S. Willsky, K. C. Chou, A. Willsky, 1990, 29th IEEE Conference on Decision and Control.

DISCRETE-TIME SMOOTHING ERROR MODELS

A. Willsky, B. Levy, Martin G. Bellol, 1988 .

MURI : Value-centered Information Theory Year 4 IPR

A. Willsky, A. Hero, U. Berkeley, 2022 .

Tracking and restrictability in discrete event dynamic systems

Alan S. Willsky, Cüneyt M. Özveren, A. Willsky, 1992 .

Upper Extremity LimbFunction Discrimination UsingEMG Signal Analysis

Alan S. Willsky, A. Willsky, 1983 .

ECG/VCG Rhythm Diagnosis Using Statistical Signal Analysis-II. Identification of Transient Rhythms

A. Willsky, J. Triebwasser, M. Lancaster, 1978, IEEE Transactions on Biomedical Engineering.

January , 1984 LIDS-P-1351 Detection of Abrupt Changes in Dynamic Systems

A. Willsky, 1986 .

Filtering for Random Finite Group Homomorphic Sequential Systems

A. Willsky, 1976 .

A Bayesian Approach to the Design of Decision Rules for Failure Detection and Identification

A. Willsky, E. Chow, 1983 .

Multiscale Methods for the Segmentation of Images Multiscale Methods for the Segmentation of Images Multiscale Methods for the Segmentation of Images

Michael K. Schneider, A. Willsky, M. Schneider, 1996 .

Analysis of Singularly Perturbed Linear Systems

A. Willsky, X. Lou, G. Verghese, 2022 .

An Efficient Message-Passing Algorithm for Optimizing Decentralized Detection Networks

O. P. Kreidl, A. Willsky, 2006, Proceedings of the 45th IEEE Conference on Decision and Control.

Measurements Using Prior Geometric Information

A. Willsky, Jerry L. Princet, 1988 .

The Mumford-Shah functional: from segmentation to stereo

Stefano Soatto, Alan S. Willsky, Anthony Yezzi, 2003 .

4-2011 Bayesian Nonparametric Inference of Switching Linear Dynamical Systems

Michael I. Jordan, Erik B. Sudderth, E. Fox, 2017 .

Detection of abrupt Chancgas in Dynamic Systems* OF ABRUPT ChANGES IN DYNAMIC SYSTEMS

A. Willsky, 2010 .

REPORT OF THE TRI-SERVICE WORKING GROUP ON THE ROLE OF PROBABILITY AND STATISTICS IN COMMAND AND CONTROL Working Group Participants: Principal Authors: Prof

S. Marcus, A. Willsky, D. Castañón, 1998 .

Algebraic methods in system theory

A. Willsky, J. Willems, R. Brockett, 1975 .

Graphical Models and Fusion in Sensor Networks

Martin J. Wainwright, Lei Chen, John W. Fisher, 2007 .

The fixed-interval smoother for continuous-time processes

A. Willsky, N. Sandell, J. Wall, 1980, 1980 19th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes.

Status Report on Estimation and Statistical Analysis of Spatially Distributed Random Processes

A. Willsky, B. Levy, Haddad, 2022 .

Redundancy Relations ane Robust Failure Detections

A. Willsky, 2010 .

COMPRESSED SENSINGWITH SEQUENTIAL OBSERVATIONS

A. Willsky, S. Sanghavi, D. Malioutov, 2008 .

Kalman estimation for a class of rational isotropic random fields

A. Willsky, B. Levy, A. Tewfik, 1985, 1985 24th IEEE Conference on Decision and Control.

Spatial Priors into an Information Theoretic Approach for f MRI Data Analysis (cid:1)

A. Willsky, C. Wible, John W. Fisher III, 2008 .

Convergence study of an iterative joint detector for wavelet packet multiple-access communication

A. Willsky, W. Karl, H. Krim, 1994, Proceedings of IEEE-SP International Symposium on Time- Frequency and Time-Scale Analysis.

MURI 06: Integrated Fusion, Performance Prediction, and Sensor Management for Automatic Target Exploitation FA9550-06-1-0324

Alfred O. Hero, John W. Fisher, Emre Ertin, 2008 .

Level Set Methods in an EM Framework for Shape Classification and Estimation

Pierre Hellier, Christian Barillot, Computer-Assisted Intervention, 2004, International Conference on Medical Image Computing and Computer-Assisted Intervention.

Hierarchical aggregation of diffusion processes with multiple equilibrium points

A. Willsky, D. Castañón, M. Coderch, 1982, 1982 21st IEEE Conference on Decision and Control.

Nonparametric belief propagation for self-calibration in sensor networks

John W. Fisher, Alan S. Willsky, Randolph L. Moses, 2004, Third International Symposium on Information Processing in Sensor Networks, 2004. IPSN 2004.

Data Fusion in Large Arrays of Microsensors 1

A. Willsky, 2002 .

Issues in the development of a general design algorithm for reliable failure detection

Edward Chow, Alan Willsky, A. Willsky, 1980, 1980 19th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes.

Finite time zero-error control for linear continuous time systems via delay feedback

Alan Willsky, Raymond Kwong, A. Willsky, 1975, 1975 IEEE Conference on Decision and Control including the 14th Symposium on Adaptive Processes.

6.003 Signals and Systems, Fall 2003

Victor Zue, Joel Voldman, Alan Willsky, 2003 .

Inter American University of Puerto Rico Bayamon Campus School of Engineering Department of Electrical Engineering

Leon O. Chua, Alan V. Oppenheim, Ernest S. Kuh, 1997 .

STOCHASTIC PROCESSES, DETECTION AND ESTIMATION 6.432 Course Notes

Jeffrey H. Shapiro, Gregory W. Wornell, Alan S. Willsky, 2003 .

Detection of incidents on freeways

S. Gershwin, A. Willsky, E. Chow, 1978, 1978 IEEE Conference on Decision and Control including the 17th Symposium on Adaptive Processes.

Learning Latent Tree Graphical Models

Vincent Y. F. Tan, Anima Anandkumar, Alan S. Willsky, 2010, J. Mach. Learn. Res..

A canonical correlations approach to multiscale stochastic realization

Alan S. Willsky, W. W. Irving, William W. Irving, 2001, IEEE Trans. Autom. Control..

Computationally Efficient Stochastic Realization for Internal Multiscale Autoregressive Models

Alan S. Willsky, Austin B. Frakt, A. Willsky, 2001, Multidimens. Syst. Signal Process..

Multiscale autoregressive processes. I. Schur-Levinson parametrizations

A. Benveniste, M. Basseville, A.S. Willsky, 1992, IEEE Trans. Signal Process..

Exploiting hierarchical context on a large database of object categories

Antonio Torralba, Joseph J. Lim, Alan S. Willsky, 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

A sparse signal reconstruction perspective for source localization with sensor arrays

Dmitry M. Malioutov, Alan S. Willsky, Müjdat Çetin, 2005, IEEE Transactions on Signal Processing.

A moment-based variational approach to tomographic reconstruction

Peyman Milanfar, W. Clem Karl, Alan S. Willsky, 1996, IEEE Trans. Image Process..

Using Sample-based Representations Under Communications Constraints

John W. Fisher, Alan S. Willsky, Alexander T. Ihler, 2004 .

Efficient Multiscale Sampling from Products of Gaussian Mixtures

William T. Freeman, Alan S. Willsky, Alexander T. Ihler, 2003, NIPS.

Data association based on optimization in graphical models with application to sensor networks

Martin J. Wainwright, Lei Chen, Alan S. Willsky, 2006, Math. Comput. Model..

Distributed data association for multi-target tracking in sensor networks

Alan S. Willsky, Lei Chen, Mujdat Cetin, 2005 .

Multitarget-multisensor data association using the tree-reweighted max-product algorithm

Martin J. Wainwright, Lei Chen, Mujdat Cetin, 2003, SPIE Defense + Commercial Sensing.

Expectation-maximization approach to target model generation from multiple synthetic aperture radar images

John A. Richards, John W. Fisher, Alan S. Willsky, 2002 .

A Unified Multiresolution Framework for Automatic Target Recognition (ATR)

John W. Fisher, Eric Grimson, Alan S. Willsky, 2001 .

Expectation-maximization approach to target model generation from multiple SAR images

John A. Richards, John W. Fisher, Alan S. Willsky, 2000, SPIE Defense + Commercial Sensing.

A curve evolution approach to smoothing and segmentation using the Mumford-Shah functional

Anthony J. Yezzi, Alan S. Willsky, Andy Tsai, 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

Convex set reconstruction using prior shape information

Jerry L. Prince, Alan S. Willsky, Jerry L Prince, 1991, CVGIP Graph. Model. Image Process..

On the Use of Descriptor Systems for Failure Detection and Isolation

Michèle Basseville, Alan S. Willsky, A. Benveniste, 1993 .

A design methodology for robust failure detection and isolation

Krishna R. Pattipati, Alan S. Willsky, J. C. Deckert, 1984 .

Dynamic model-based techniques for the detection of incidents on freeways

P K Houpt, Stanley B. Gershwin, Alan S. Willsky, 1980 .

ECG/VCG Rhythm Diagnosis Using Statistical Signal Analysis-I. Identification of Persistent Rhythms

Donald E. Gustafson, Alan S. Willsky, Malcolm C. Lancaster, 1978, IEEE Transactions on Biomedical Engineering.

F-8 DFBW sensor failure identification using analytic redundancy

Alan S. Willsky, J. C. Deckert, J. Deyst, 1977 .

Two self-test methods applied to an inertial system problem. [estimating gyroscope and accelerometer bias

Alan S. Willsky, J. Deyst, B. S. Crawford, 1975 .

Fiber Tract Clustering on Manifolds With Dual Rooted-Graphs

Alfred O. Hero, Carl-Fredrik Westin, Alan S. Willsky, 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

Sparsity-Driven Synthetic Aperture Radar Imaging: Reconstruction, autofocusing, moving targets, and compressed sensing

Kush R. Varshney, W. Clem Karl, Alan S. Willsky, 2014, IEEE Signal Processing Magazine.

A Fully Global Approach to Image Segmentation via Coupled Curve Evolution Equations

Anthony J. Yezzi, Alan S. Willsky, Andy Tsai, 2002, J. Vis. Commun. Image Represent..

A wavelet-based method for multiscale tomographic reconstruction

W. Clem Karl, Alan S. Willsky, Mickey Bhatia, 1996, IEEE Trans. Medical Imaging.

Nonlinear evolution equations as fast and exact solvers of estimation problems

Alan S. Willsky, Ilya Pollak, Yan Huang, 2005, IEEE Transactions on Signal Processing.

Time-varying parametric modeling of speech

Alan Oppenheim, Alan Willsky, Mark Hall, 1977, 1977 IEEE Conference on Decision and Control including the 16th Symposium on Adaptive Processes and A Special Symposium on Fuzzy Set Theory and Applications.

Relationships between digital signal processing and control and estimation theory

A.S. Willsky, A. Willsky, 1978, Proceedings of the IEEE.

The Hierarchical Dirichlet Process Hidden Semi-Markov Model

Matthew J. Johnson, Alan S. Willsky, A. Willsky, 2010, UAI.

Linear Dimensionality Reduction for Margin-Based Classification: High-Dimensional Data and Sensor Networks

Kush R. Varshney, Alan S. Willsky, A. Willsky, 2011, IEEE Transactions on Signal Processing.

Classification Using Geometric Level Sets

Kush R. Varshney, Alan S. Willsky, A. Willsky, 2010, J. Mach. Learn. Res..

A multiscale, statistically based inversion scheme for linearized inverse scattering problems

Eric L. Miller, Alan S. Willsky, A. Willsky, 1996, IEEE Trans. Geosci. Remote. Sens..

Wavelet‐based methods for the nonlinear inverse scattering problem using the extended Born approximation

Eric L. Miller, Alan S. Willsky, A. Willsky, 1996 .

Walk-Sums and Belief Propagation in Gaussian Graphical Models

Dmitry M. Malioutov, Alan S. Willsky, Jason K. Johnson, 2006, J. Mach. Learn. Res..

Walk-Sum Interpretation and Analysis of Gaussian Belief Propagation

Dmitry M. Malioutov, Alan S. Willsky, Jason K. Johnson, 2005, NIPS.

A multiscale approach to solving one dimensional inverse problems

Alan S. Willsky, A. Willsky, E. Miller, 1992, [1992] Proceedings of the IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis.

Learning Graphical Models for Hypothesis Testing and Classification

Vincent Y. F. Tan, John W. Fisher, Sujay Sanghavi, 2010, IEEE Transactions on Signal Processing.

On the Algebraic Structure of Certain Partially Observable Finite-State Markov Processes

Alan S. Willsky, A. Willsky, 1978, Inf. Control..

The digital implementation of control compensators: The coefficient wordlength issue

Paul Moroney, Alan Willsky, Paul Houpt, 1979, 1979 18th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes.

Multiscale representations of Markov random fields

W. Clem Karl, Alan S. Willsky, Robert R. Tenney, 1993, 1993 IEEE International Conference on Acoustics, Speech, and Signal Processing.

Internal models and recursive estimation for 2-D isotropic random fields

Ahmed H. Tewfik, Alan S. Willsky, Bernard C. Levy, 1991, IEEE Trans. Inf. Theory.

A new parallel smoothing algorithm

A. Tewfik, B. Levy, A. Willsky, 1986, 1986 25th IEEE Conference on Decision and Control.

Algorithms for the incorporation of predictive information in surveillance theory

Alan S. Willsky, Bernard C. Levy, David A. Castanon, 1985 .

Linear estimation of boundary value stochastic processes--Part II: 1-D smoothing problems

Alan S. Willsky, Bernard C. Levy, Milton B. Adams, 1984 .

Interim Progress Report

A. Willsky, A. Hero, U. Berkeley, 2010 .

Digital Phase Lock Loops: Architechtures and Applications

Ali M. Niknejad, Alan V. Oppenheim, Alan S. Willsky, 2012 .

Probabilistic and sequential computation of optical flow using temporal coherence

T. M. Chin, W. Clem Karl, Alan S. Willsky, 1994, IEEE Trans. Image Process..

A Statistical Method for Efficient Segmentation of MR Imagery

W. Clem Karl, Alan S. Willsky, John P. Kaufhold, 1997, Int. J. Pattern Recognit. Artif. Intell..

Low complexity optimal joint detection for oversaturated multiple access communications

Alan S. Willsky, Don M. Boroson, Rachel E. Learned, 1997, IEEE Trans. Signal Process..

A Wavelet Packet Approach to Transient Signal Classification

Alan S. Willsky, Rachel E. Learned, A. Willsky, 1995 .

Multiresolution approach to discriminating targets from clutter in SAR imagery

Alan S. Willsky, Leslie M. Novak, W. W. Irving, 1995, Defense, Security, and Sensing.

Estimation of dynamically evolving ellipsoids with applications to medical imaging

W. Clem Karl, Alan S. Willsky, Seema Jaggi, 1995, IEEE Trans. Medical Imaging.

Optimal and suboptimal filtering for Toeplitz systems

A. Willsky, Decision Systems., N. Sandell, 1979 .

Multiresolution optimal interpolation and statistical analysis of TOPEX/POSEIDON satellite altimetry

Paul W. Fieguth, Carl Wunsch, W. Clem Karl, 1995, IEEE Transactions on Geoscience and Remote Sensing.

Trees and beyond: exploiting and improving tree-structured graphical models

Antonio Torralba, Myung Jin Choi, Alan S. Willsky, 2011 .

An efficient maximum entropy technique for 2-D isotropic random fields

Ahmed H. Tewfik, Alan S. Willsky, Bernard C. Levy, 1988, ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing.

Nonparametric shape priors for active contour-based image segmentation

Alan S. Willsky, Müjdat Çetin, Junmo Kim, 2005, 2005 13th European Signal Processing Conference.

A variational technique for source localization based on a sparse signal reconstruction perspective

Dmitry M. Malioutov, Alan S. Willsky, Müjdat Çetin, 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

Convex graph invariants

Pablo A. Parrilo, Venkat Chandrasekaran, Alan S. Willsky, 2010, 2012 46th Annual Conference on Information Sciences and Systems (CISS).

Tree-Based Modeling and Estimation of Gaussian Processes on Graphs with Cycles

Martin J. Wainwright, Alan S. Willsky, Erik B. Sudderth, 2000, NIPS.

The Modeling and Estimation of Statistically Self-Similar Processes in a Multiresolution Framework

Alan S. Willsky, Michael M. Daniel, A. Willsky, 1999, IEEE Trans. Inf. Theory.

An overlapping tree approach to multiscale stochastic modeling and estimation

Paul W. Fieguth, Alan S. Willsky, W. W. Irving, 1997, IEEE Trans. Image Process..

Tomographic reconstruction and estimation based on multiscale natural-pixel bases

W. Clem Karl, Alan S. Willsky, Mickey Bhatia, 1997, IEEE Trans. Image Process..

Multiscale methods for the segmentation of images

Paul W. Fieguth, W. Clem Karl, Alan S. Willsky, 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

A shape-based approach to the segmentation of medical imagery using level sets

W. Eric L. Grimson, William M. Wells, Anthony J. Yezzi, 2003, IEEE Transactions on Medical Imaging.

Constrained sinogram restoration for limited-angle tomography

Jerry L. Prince, Alan S. Willsky, Jerry L Prince, 1990 .

Exact MAP Estimates by (Hyper)tree Agreement

Martin J. Wainwright, Tommi S. Jaakkola, Alan S. Willsky, 2002, NIPS.

The stochastic analysis of dynamic systems moving through random fields

A. Willsky, N. Sandell, 1982 .

Roundoff noise and scaling in the digital implementation of control compensators

P K Houpt, Alan S. Willsky, Paul Moroney, 1983 .

Submitted to Ieee Transactions on Image Processing a Nonparametric Statistical Method for Image Segmentation Using Information Theory and Curve Evolution

John W. Fisher, Anthony J. Yezzi, Alan S. Willsky, 2022 .

Model-based curve evolution technique for image segmentation

W. Eric L. Grimson, William M. Wells, Anthony J. Yezzi, 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

Diagonal and Low-Rank Matrix Decompositions, Correlation Matrices, and Ellipsoid Fitting

Pablo A. Parrilo, Venkat Chandrasekaran, Alan S. Willsky, 2012, SIAM J. Matrix Anal. Appl..

An efficient message passing algorithm for multi-target tracking

Lei Chen, Alan S. Willsky, Müjdat Çetin, 2009, 2009 12th International Conference on Information Fusion.

Semidefinite relaxations for optimization problems over rotation matrices

Pablo A. Parrilo, Alan S. Willsky, James Saunderson, 2014, 53rd IEEE Conference on Decision and Control.

Gaussian Multiresolution Models: Exploiting Sparse Markov and Covariance Structure

Venkat Chandrasekaran, Alan S. Willsky, Myung Jin Choi, 2010, IEEE Transactions on Signal Processing.

Exploiting sparse Markov and covariance structure in multiresolution models

Venkat Chandrasekaran, Alan S. Willsky, Myung Jin Choi, 2009, ICML '09.

Analysis of Functional MRI Data Using Mutual Information

John W. Fisher, William M. Wells, Alan S. Willsky, 1999, MICCAI.

Detection error exponent for spatially dependent samples in random networks

Lang Tong, Anima Anandkumar, Alan S. Willsky, 2009, 2009 IEEE International Symposium on Information Theory.

Feature-preserving regularization method for complex-valued inverse problems with application to coherent imaging

Alan S. Willsky, Mujdat Cetin, William Clement Karl, 2006 .

Sparse Representation in Structured Dictionaries With Application to Synthetic Aperture Radar

Kush R. Varshney, John W. Fisher, Alan S. Willsky, 2008, IEEE Transactions on Signal Processing.

MIT Open Access Articles Sparsity-Driven Synthetic Aperture Radar Imaging: Reconstruction, autofocusing, moving targets, and compressed sensing

W. Karl, A. Willsky, K. Varshney, 2022 .

Sparsity-Driven Synthetic Aperture Radar Imaging

Kush R. Varshney, W. Clem Karl, Alan S. Willsky, 2014 .

Energy-latency tradeoff for in-network function computation in random networks

Béla Bollobás, Anima Anandkumar, Alan S. Willsky, 2011, 2011 Proceedings IEEE INFOCOM.

Nonparametric belief propagation for self-localization of sensor networks

John W. Fisher, Alan S. Willsky, Randolph L. Moses, 2005, IEEE Journal on Selected Areas in Communications.

Variational approaches on discontinuity localization and field estimation in sea surface temperature and soil moisture

T. M. Chin, Alan S. Willsky, Müjdat Çetin, 2006, IEEE Transactions on Geoscience and Remote Sensing.

Statistical characterization of real-world illumination.

Ron O Dror, Alan S Willsky, Edward H Adelson, 2004, Journal of vision.

Statistics of real-world illumination

Edward H. Adelson, Alan S. Willsky, Thomas K. Leung, 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

A Krylov Subspace Method for Covariance Approximation and Simulation of Random Processes and Fields

Alan S. Willsky, Michael K. Schneider, A. Willsky, 2003, Multidimens. Syst. Signal Process..

Diagonal and low-rank decompositions and fitting ellipsoids to random points

Pablo A. Parrilo, Alan S. Willsky, James Saunderson, 2013, 52nd IEEE Conference on Decision and Control.

Source localization by enforcing sparsity through a Laplacian prior: an SVD-based approach

A.S. Willsky, D.M. Malioutov, M. Cetin, 2004, IEEE Workshop on Statistical Signal Processing, 2003.

Likelihood calculation for a class of multiscale stochastic models, with application to texture discrimination

Alan S. Willsky, Mark R. Luettgen, M. Luettgen, 1995, IEEE Trans. Image Process..

Maximum likelihood array processing for the estimation of superimposed signals

Anthony J. Weiss, Alan S. Willsky, Bernard C. Levy, 1988, Proc. IEEE.

A statistical approach to rhythm diagnosis of cardiograms

A. Willsky, M. Lancaster, D. Gustafson, 1977, 1976 IEEE Conference on Decision and Control including the 15th Symposium on Adaptive Processes.

Reconstructing Ellipsoids from Projections

W. Clem Karl, George C. Verghese, Alan S. Willsky, 1994, CVGIP Graph. Model. Image Process..

Segmentation-directed SAR image compression via hierarchical stochastic modeling

Alan S. Willsky, A. Hamid Krim, Andrew J. Kim, 1997, Defense, Security, and Sensing.

MCMC Curve Sampling for Image Segmentation

John W. Fisher, James J. Levitt, William M. Wells, 2007, MICCAI.

Time Scale Decomposition: The Role of Scaling in Linear Systems and Transient States in Finite-State Markov Processes

J. R. Rohlicek, A. Willsky, X. Lou, 1985, 1985 American Control Conference.

A statistical approach to snakes for bimodal and trimodal imagery

Anthony J. Yezzi, Alan S. Willsky, Andy Tsai, 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

A Unified Variational Approach to Denoising and Bias Correction in MR

John W. Fisher, William M. Wells, Alan S. Willsky, 2003, IPMI.

Learning the Dynamics and Time-Recursive Boundary Detection of Deformable Objects

Alan S. Willsky, Müjdat Çetin, Raymond C. Chan, 2008, IEEE Transactions on Image Processing.

Segmenting and Tracking the Left Ventricle by Learning the Dynamics in Cardiac Images

Alan S. Willsky, Müjdat Çetin, Venkat Chandar, 2005, IPMI.

A curve evolution-based variational approach to simultaneous image restoration and segmentation

Alan S. Willsky, Müjdat Çetin, Junmo Kim, 2002, Proceedings. International Conference on Image Processing.

Nonparametric methods for image segmentation using information theory and curve evolution

John W. Fisher, Anthony J. Yezzi, Alan S. Willsky, 2002, Proceedings. International Conference on Image Processing.

Curve evolution, boundary-value stochastic processes, the Mumford-Shah problem, and missing data applications

Anthony J. Yezzi, Alan S. Willsky, Andy Tsai, 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).

Mutual information in coupled multi-shape model for medical image segmentation

W. Eric L. Grimson, William M. Wells, Alan S. Willsky, 2004, Medical Image Anal..

Estimating dependency and significance for high-dimensional data

John W. Fisher, Alan S. Willsky, Alexander T. Ihler, 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

Architectural issues in the implementation of digital compensators

P K Houpt, Alan S. Willsky, Paul Moroney, 1981 .

Sequential Compressed Sensing

Dmitry M. Malioutov, Sujay Sanghavi, Alan S. Willsky, 2010, IEEE Journal of Selected Topics in Signal Processing.

Optimal sparse representations in general overcomplete bases

Dmitry M. Malioutov, Alan S. Willsky, Müjdat Çetin, 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

Compressed sensing with sequential observations

Dmitry M. Malioutov, Sujay Sanghavi, Alan S. Willsky, 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

Silhouette recognition using high-resolution pursuit

Stéphane Mallat, W. Clem Karl, Alan S. Willsky, 1999, Pattern Recognit..

Lagrangian Relaxation for MAP Estimation in Graphical Models pdf

Dmitry M. Malioutov, Alan S. Willsky, Jason K. Johnson, 2007, ArXiv.

A multiscale approach to pixel-level image fusion

Yun He, A. Ben Hamza, Alan S. Willsky, 2005, Integr. Comput. Aided Eng..

Networking sensors using belief propagation

A. Willsky, S. Sanghavi, D. Malioutov, 2008, 2008 46th Annual Allerton Conference on Communication, Control, and Computing.

Linear programming analysis of loopy belief propagation for weighted matching

Dmitry M. Malioutov, Sujay Sanghavi, Alan S. Willsky, 2007, NIPS.

Embedded trees: estimation of Gaussian Processes on graphs with cycles

Erik B. Sudderth, A. Willsky, M. Wainwright, 2004, IEEE Transactions on Signal Processing.

High-dimensional Gaussian graphical model selection: walk summability and local separation criterion

Vincent Y. F. Tan, Anima Anandkumar, Alan S. Willsky, 2011, J. Mach. Learn. Res..

Error exponents for composite hypothesis testing of Markov forest distributions

Vincent Y. F. Tan, Anima Anandkumar, Alan S. Willsky, 2010, 2010 IEEE International Symposium on Information Theory.

Learning Markov Structure by Maximum Entropy Relaxation

Venkat Chandrasekaran, Alan S. Willsky, Jason K. Johnson, 2007, AISTATS.

A multiresolution approach to discrimination in SAR imagery

W. W. Irving, A. Willsky, L. Novak, 1997, IEEE Transactions on Aerospace and Electronic Systems.

Fractal estimation using models on multiscale trees

Paul W. Fieguth, Alan S. Willsky, A. Willsky, 1996, IEEE Trans. Signal Process..

Best basis algorithm for signal enhancement

Stéphane Mallat, Alan S. Willsky, Hamid Krim, 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

Dynamical systems defined on groups : structural properties and estimation.

Alan S. Willsky, A. Willsky, 1973 .

Message Passing for Maximum Weight Independent Set

Devavrat Shah, Sujay Sanghavi, Alan S. Willsky, 2008, IEEE Transactions on Information Theory.

Sampling From Gaussian Markov Random Fields Using Stationary and Non-Stationary Subgraph Perturbations

Alan S. Willsky, Oliver Kosut, Ying Liu, 2015, IEEE Transactions on Signal Processing.

Sampling from Gaussian graphical models using subgraph perturbations

Alan S. Willsky, Oliver Kosut, Ying Liu, 2013, 2013 IEEE International Symposium on Information Theory.

Sample complexity for topology estimation in networks of LTI systems

Vincent Y. F. Tan, Alan S. Willsky, A. Willsky, 2011, IEEE Conference on Decision and Control and European Control Conference.

Necessary and sufficient conditions for high-dimensional salient feature subset recovery

Vincent Y. F. Tan, Matthew J. Johnson, Alan S. Willsky, 2010, 2010 IEEE International Symposium on Information Theory.

Maximum entropy relaxation for multiscale graphical model selection

Venkat Chandrasekaran, Alan S. Willsky, Myung Jin Choi, 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

Estimation in Gaussian Graphical Models Using Tractable Subgraphs: A Walk-Sum Analysis

Venkat Chandrasekaran, Alan S. Willsky, Jason K. Johnson, 2008, IEEE Transactions on Signal Processing.

Network Intrusion Detection with Minimal Communication Overhead

O. P. Kreidl, A. Willsky, 2009 .

A Recursive Model-Reduction Method for Approximate Inference in Gaussian Markov Random Fields

Alan S. Willsky, Jason K. Johnson, A. Willsky, 2008, IEEE Transactions on Image Processing.

Embedded Trees : Estimation of Gaussian Processes on Graphs with Cycles

Erik B. Sudderth, A. Willsky, M. Wainwright, 2002 .

Learning High-Dimensional Markov Forest Distributions: Analysis of Error Rates pdf

Vincent Y. F. Tan, Anima Anandkumar, Alan S. Willsky, 2010, J. Mach. Learn. Res..

Learning Graphical Models for Hypothesis Testing

Alan Willsky, Sujay Sanghavi, Vincent Tan, 2007, 2007 IEEE/SP 14th Workshop on Statistical Signal Processing.

Random cascades of Gaussian scale mixtures and their use in modeling natural images with application to denoising

Martin J. Wainwright, Eero P. Simoncelli, Alan S. Willsky, 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).

Adaptive Embedded Subgraph Algorithms using Walk-Sum Analysis

Venkat Chandrasekaran, Alan S. Willsky, Jason K. Johnson, 2007, NIPS.

Graphical models and message-passing algorithms for network-constrained decision problems

Greg, Jason K. Johnson, Wee Peng Tay, 2008 .

Message passing and distributed statistical inference

Venkat Chandrasekaran, Alan S. Willsky, Jason K. Johnson, 2007 .

Message Passing for Max-weight Independent Set

Devavrat Shah, Sujay Sanghavi, Alan S. Willsky, 2007, NIPS.

Learning Latent Tree Graphical Models

A. Willsky, Anima Anandkumar, M. Choi, 2022 .

A State-Space Analysis for Reconstruction of Goal-Directed Movements Using Neural Signals

Emery N. Brown, Alan S. Willsky, Uri T. Eden, 2006, Neural Computation.

Describing Visual Scenes Using Transformed Objects and Parts

Erik B. Sudderth, A. Torralba, W. Freeman, 2008, International Journal of Computer Vision.

Multiresolution stochastic models, data fusion, and wavelet transforms

Alan S. Willsky, Stuart A. Golden, Kenneth C. Chou, 1993, Signal Process..

Sequential filtering for multi-frame visual reconstruction

T. M. Chin, W. Clem Karl, Alan S. Willsky, 1992, Signal Process..

LATENT VARIABLE GRAPHICAL MODEL SELECTION VIA CONVEX OPTIMIZATION1 BY VENKAT CHANDRASEKARAN,

A. Willsky, P. Parrilo, Venkat Chandrasekaran, 2012 .

Reachability, observability, minimality, and extendibility for two-point boundary-value descriptor systems

A. Willsky, R. Nikoukhah, B. Levy, 1991 .

November 1986 LIDS-P-1626 Boundary-Value Descriptor Systems : Well-Posedness , Reachability , and Observability 1

A. Willsky, C. Levy, Bernard C. Levy, 2022 .

Generalized Riccati equations for two-point boundary-value descriptor systems

Ramine Nikoukhah, Alan Willsky, Bernard Levy, 1987, 26th IEEE Conference on Decision and Control.

Linear smoothing for descriptor systems

Alan Willsky, Milton Adams, Bernard Levy, 1984, The 23rd IEEE Conference on Decision and Control.

The reduction of perturbed Markov generators: an algorithm exposing the role of transient states

Alan S. Willsky, Jan Robin Rohlicek, J. R. Rohlicek, 1988, JACM.

Belief Propagation and LP Relaxation for Weighted Matching in General Graphs

Dmitry M. Malioutov, Sujay Sanghavi, Alan S. Willsky, 2011, IEEE Transactions on Information Theory.

Trees and beyond: exploiting and improving tree-structured graphical models

A. Willsky, M. Choi, Antonio Torralba, 2011 .

Mapping Mediterranean Altimeter Data with a Multiresolution Optimal Interpolation Algorithm

Carl Wunsch, Paul Fieguth, T. T. Ho, 1998 .

Multiresolution statistical analysis and assimilation of large ocean data sets

Paul W. Fieguth, W. Clem Karl, Alan S. Willsky, 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

Multiresolution stochastic processing of Topex/Poseidon oceanographic altimetry

Paul Fieguth, Alan S. Willsky, William Clement Karl, 1994, Proceedings of OCEANS'94.

Statistical multiscale approach to mapping altimetric data

Paul W. Fieguth, Alan S. Willsky, William C. Karl, 1994, Optics & Photonics.

Some structural properties of automata defined on groups

Alan S. Willsky, Roger W. Brockett, A. Willsky, 1974, Category Theory Applied to Computation and Control.

Fourier series and estimation on the circle with applications to synchronous communication-I: Analysis

Alan S. Willsky, A. Willsky, 1974, IEEE Trans. Inf. Theory.

Robust detection-isolation-accommodation for sensor failures

Krishna R. Pattipati, Alan S. Willsky, Jerold L. Weiss, 1985 .

Optimally robust redundancy relations for failure detection in uncertain systems

George C. Verghese, Alan S. Willsky, Xi-Cheng Lou, 1986, Autom..

A Constraint Generation Integer Programming Approach to Information Theoretic Sensor Resource Management

John W. Fisher, Alan S. Willsky, Jason L. Williams, 2007, 2007 IEEE/SP 14th Workshop on Statistical Signal Processing.

Performance Guarantees for Information Theoretic Active Inference

John W. Fisher, Alan S. Willsky, Jason L. Williams, 2007, AISTATS.

Curve sampling and geometric conditional simulation

Ayres C. Fan, A. Willsky, John W. Fisher III, 2008 .

A nonparametric statistical method for image segmentation using information theory and curve evolution

A. Willsky, A. Yezzi, John W. Fisher III, 2005, IEEE Transactions on Image Processing.

Local tests for consistency of support hyperplane data

Sanjeev R. Kulkarni, W. Clem Karl, George C. Verghese, 1996, Journal of Mathematical Imaging and Vision.

System theory: A unified state-space approach to continuous and discrete systems : L. Padulo and M. A. Arbib. 779 pages, diagrams, 6× 9 in. W. B. Saunders, Philadelphia, 1974. Price, $17.50. (approx. £8.75)

Alan S. Willsky, A. Willsky, 1976 .