Tony Jebara

发表

Learning with Subgraph Estimation and Degree Priors

Bert Huang, Tony Jebara, 2010 .

Perfect Graphs and Graphical Modeling

Tony Jebara, T. Jebara, 2014, Tractability.

Maximum Relative Margin and Data-Dependent Regularization

Tony Jebara, Pannagadatta K. Shivaswamy, T. Jebara, 2010, J. Mach. Learn. Res..

Learning a Distance Metric from a Network

Bert Huang, Tony Jebara, Blake Shaw, 2011, NIPS.

Graph construction and b-matching for semi-supervised learning

Shih-Fu Chang, Jun Wang, Tony Jebara, 2009, ICML '09.

Probability Product Kernels

Tony Jebara, Risi Kondor, Andrew G. Howard, 2004, J. Mach. Learn. Res..

Approximating the Bethe Partition Function

Adrian Weller, Tony Jebara, T. Jebara, 2013, UAI.

Structure preserving embedding

Tony Jebara, Blake Shaw, T. Jebara, 2009, ICML '09.

Code Relatives: Detecting Similar Software Behavior

Gail E. Kaiser, Simha Sethumadhavan, Tony Jebara, 2015 .

Statistical imitative learning from perceptual data

Tony Jebara, A. Pentland, A. Pentland, 2002, Proceedings 2nd International Conference on Development and Learning. ICDL 2002.

Empirical Bernstein Boosting

Tony Jebara, Pannagadatta K. Shivaswamy, 2010, AISTATS.

Spectral Clustering and Embedding with Hidden Markov Models

Tony Jebara, Yingbo Song, Kapil Thadani, 2007, ECML.

Thompson Sampling for Noncompliant Bandits pdf

Tony Jebara, Andrew Stirn, T. Jebara, 2018, ArXiv.

Stochasticks: augmenting the billiards experience with probabilistic vision and wearable computers

Alex Pentland, Thad Starner, Tony Jebara, 1997, Digest of Papers. First International Symposium on Wearable Computers.

Learning a Degree-Augmented Distance Metric from a Network

Bert Huang, Tony Jebara, T. Jebara, 2011 .

Dynamical Systems Trees

Tony Jebara, Andrew G. Howard, 2004, UAI.

Semantic Concept Classification by Joint Semi-supervised Learning of Feature Subspaces and Support Vector Machines

Shih-Fu Chang, Alexander C. Loui, Tony Jebara, 2008, ECCV.

Clamping Variables and Approximate Inference

Adrian Weller, Tony Jebara, 2014, NIPS.

Bayesian Out-Trees pdf

Tony Jebara, T. Jebara, 2008, UAI.

A Privacy Analysis of Cross-device Tracking

Steven M. Bellovin, Sebastian Zimmeck, Tony Jebara, 2017, USENIX Security Symposium.

Learning Monotonic Transformations for Classification

Tony Jebara, Andrew G. Howard, 2007, NIPS.

Parametrized structure from motion for 3D adaptive feedback tracking of faces

Alex Pentland, Tony Jebara, A. Pentland, 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

Initialization and Coordinate Optimization for Multi-way Matching

Da Tang, Tony Jebara, T. Jebara, 2016, AISTATS.

Variance Penalizing AdaBoost

Tony Jebara, Pannagadatta K. Shivaswamy, 2011, NIPS.

Item Recommendation with Variational Autoencoders and Heterogeneous Priors

Jie Yuan, Da Tang, Tony Jebara, 2018, DLRS@RecSys.

Item Recommendation with Variational Autoencoders and Heterogenous Priors pdf

Jie Yuan, Da Tang, Tony Jebara, 2018, ArXiv.

An SVM learning approach to robotic grasping

Peter K. Allen, Tony Jebara, Andrew T. Miller, 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

Collaborative Filtering via Rating Concentration

Bert Huang, Tony Jebara, T. Jebara, 2010, AISTATS.

Graph transduction via alternating minimization

Shih-Fu Chang, Jun Wang, Tony Jebara, 2008, ICML '08.

SVM for Learning with Label Proportions Supplementary Material 1

Dong Liu, Shih-Fu Chang, Sanjiv Kumar, 2013 .

Majorization for CRFs and Latent Likelihoods

Anna Choromanska, Tony Jebara, T. Jebara, 2012, NIPS.

Code relatives: detecting similarly behaving software

Gail E. Kaiser, Simha Sethumadhavan, Jonathan Bell, 2016, SIGSOFT FSE.

Large margin transformation learning

Tony Jebara, Andrew Howard, T. Jebara, 2009 .

On MAP Inference by MWSS on Perfect Graphs pdf

Adrian Weller, Tony Jebara, T. Jebara, 2013, UAI.

Laplacian Spectrum Learning

Tony Jebara, Pannagadatta K. Shivaswamy, 2010, ECML/PKDD.

Multi-object tracking with representations of the symmetric group

Tony Jebara, Risi Kondor, Andrew G. Howard, 2007, AISTATS.

Identification and Targeting of Cortical Ensembles

Rafael Yuste, Tony Jebara, Luis Carrillo-Reid, 2017, bioRxiv.

Feature Selection and Dualities in Maximum Entropy Discrimination pdf

Tommi S. Jaakkola, Tony Jebara, T. Jaakkola, 2000, UAI.

Ellipsoidal Machines

Tony Jebara, Pannagadatta K. Shivaswamy, T. Jebara, 2007, AISTATS.

Correlated Variational Auto-Encoders

Nicholas Ruozzi, Dawen Liang, Tony Jebara, 2019, ICML.

Nicholas Ruozzi, Da Tang, Dawen Liang, 2019, ArXiv.

Machine Learning

Tony Jebara, T. Jebara, 2003, Encyclopedia of Social Network Analysis and Mining. 2nd Ed..

Images as bags of pixels

Tony Jebara, T. Jebara, 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

On Reversing Jensen's Inequality

Alex Pentland, Tony Jebara, 2000, NIPS.

Maximum Conditional Likelihood via Bound Maximization and the CEM Algorithm

Alex Pentland, Tony Jebara, A. Pentland, 1998, NIPS.

Structured Prediction with Relative Margin

Tony Jebara, Pannagadatta K. Shivaswamy, 2009, 2009 International Conference on Machine Learning and Applications.

A refinement of Bennett's inequality with applications to portfolio optimization pdf

Tony Jebara, 2018, ArXiv.

On the Design of Estimators for Bandit Off-Policy Evaluation

Nikos Vlassis, Tony Jebara, Aurélien F. Bibaut, 2019, ICML.

Bethe Learning of Conditional Random Fields via MAP Decoding pdf

Nicholas Ruozzi, Tony Jebara, David Belanger, 2015, ArXiv.

A markov routing algorithm for mobile DTNs based on spatio-temporal modeling of human movement data

Henning Schulzrinne, Tony Jebara, Arezu Moghadam, 2011, MSWiM '11.

Multimodal person recognition using unconstrained audio and video

Tanzeem Choudhury, Tony Jebara, Brian Clarkson, 1998 .

Subgoal Discovery for Hierarchical Dialogue Policy Learning pdf

Chong Wang, Jianfeng Gao, Xiujun Li, 2018, EMNLP.

Bethe Learning of Graphical Models via MAP Decoding

Nicholas Ruozzi, Tony Jebara, David Belanger, 2016, AISTATS.

Adaptive Anonymity via b-Matching

Krzysztof Choromanski, Tony Jebara, Kui Tang, 2013, NIPS.

Machine Learning: Discriminative and Generative (Kluwer International Series in Engineering and Computer Science)

Tony Jebara, T. Jebara, 2003 .

New trends in Cognitive Science: Integrative approaches to learning and development

Marian Stewart Bartlett, Tony Jebara, Gedeon O. Deák, 2007, Neurocomputing.

An EM Algorithm for Localizing Multiple Sound Sources in Reverberant Environments

Daniel P. W. Ellis, Michael I. Mandel, Tony Jebara, 2006, NIPS.

Structured Prediction Models for Chord Transcription of Music Audio

Daniel P. W. Ellis, Adrian Weller, Tony Jebara, 2009, 2009 International Conference on Machine Learning and Applications.

B-Matching for Spectral Clustering

Tony Jebara, Vlad Shchogolev, Vlad Shchogolev, 2006, ECML.

Loopy Belief Propagation for Bipartite Maximum Weight b-Matching

Bert Huang, Tony Jebara, T. Jebara, 2007, AISTATS.

Machine Learning: Discriminative and Generative

Tony Jebara, Tony Jebara, 2012 .

Understanding the Bethe Approximation: When and How can it go Wrong?

Adrian Weller, Tony Jebara, David Sontag, 2014, UAI.

Modularity and Specialized Learning: Reexamining Behavior-Based Artificial Intelligence

Jochen Triesch, Joanna J. Bryson, Tony Jebara, 2004 .

MAP Estimation, Message Passing, and Perfect Graphs pdf

Tony Jebara, T. Jebara, 2009, UAI.

SCMPS 2009 Organizing and Program Committees

Deborah Estrin, Benjamin N. Waber, Daniel Olguin Olguin, 2009 .

A Kernel Between Sets of Vectors

Tony Jebara, Risi Kondor, R. Kondor, 2003, ICML.

Multitask Sparsity via Maximum Entropy Discrimination

Tony Jebara, T. Jebara, 2011, J. Mach. Learn. Res..

Learning a Distance Metric for Structured Network Prediction

Tony Jebara, Stuart J. Andrews, 2006 .

Fast b-matching via Sufficient Selection Belief Propagation

Bert Huang, Tony Jebara, T. Jebara, 2011, AISTATS.

Coloring tournaments with forbidden substructures pdf

Krzysztof Choromanski, Tony Jebara, 2015, ArXiv.

Making Pairwise Binary Graphical Models Attractive

Nicholas Ruozzi, Tony Jebara, N. Ruozzi, 2014, NIPS.

Gaussian and Wishart Hyperkernels

Tony Jebara, Risi Kondor, R. Kondor, 2006, NIPS.

Bayesian face recognition

Alex Pentland, Tony Jebara, Baback Moghaddam, 2000, Pattern Recognit..

Frank-Wolfe Algorithms for Saddle Point Problems

Tony Jebara, Gauthier Gidel, Simon Lacoste-Julien, 2016, AISTATS.

Computational Social Science

Lada A. Adamic, David Lazer, Albert-László Barabási, 2009, Science.

Multi-task feature and kernel selection for SVMs

Tony Jebara, T. Jebara, Tony Jebara, 2004, ICML.

3D structure from 2D motion

Alex Pentland, Ali J. Azarbayejani, Tony Jebara, 1999, IEEE Signal Process. Mag..

Minimum Volume Embedding

Tony Jebara, Blake Shaw, T. Jebara, 2007, AISTATS.

Mixtures of eigenfeatures for real-time structure from texture

Alex Pentland, Tony Jebara, Kenneth B. Russell, 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

Fast Spectral Clustering via the Nyström Method

Anna Choromanska, Tony Jebara, Claire Monteleoni, 2013, ALT.

Efficient MAP/ML similarity matching for visual recognition

Alex Pentland, Tony Jebara, Baback Moghaddam, 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

Transformation Learning Via Kernel Alignment

Tony Jebara, Andrew G. Howard, 2009, 2009 International Conference on Machine Learning and Applications.

Augmented realities integrating user and physical models

Alex Pentland, Bernt Schiele, Nuria Oliver, 1999 .

Bayesian Modeling of Facial Similarity

Alex Pentland, Tony Jebara, Baback Moghaddam, 1998, NIPS.

Collaborative Ranking for Local Preferences

Berk Kapicioglu, Robert E. Schapire, Tony Jebara, 2014, AISTATS.

On Learning with Label Proportions pdf

Shih-Fu Chang, Sanjiv Kumar, Tony Jebara, 2014, ArXiv.

Maximum Entropy Discrimination

Tommi S. Jaakkola, Marina Meila, Tony Jebara, 1999, NIPS.

Stochastic Bound Majorization pdf

Anna Choromanska, Tony Jebara, T. Jebara, 2013, ArXiv.

Clustered blockwise PCA for representing visual data

Shree K. Nayar, Ko Nishino, Tony Jebara, 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Bethe Bounds and Approximating the Global Optimum

Adrian Weller, Tony Jebara, T. Jebara, 2012, AISTATS.

Kernelizing Sorting, Permutation, and Alignment for Minimum Volume PCA

Tony Jebara, T. Jebara, 2004, COLT.

Behavior-based network traffic synthesis

Salvatore J. Stolfo, Tony Jebara, Yingbo Song, 2011, 2011 IEEE International Conference on Technologies for Homeland Security (HST).

Proceedings of the 31st International Conference on International Conference on Machine Learning - Volume 32

Eric P. Xing, Tony Jebara, E. Xing, 2014 .

A multi-agent control framework for co-adaptation in brain-computer interfaces

Roy Fox, Liam Paninski, Tony Jebara, 2013, NIPS.

Bhattacharyya Expected Likelihood Kernels

Tony Jebara, Risi Kondor, R. Kondor, 2003, COLT.

An Interactive Computer Vision System DyPERS: Dynamic Personal Enhanced Reality System

Alex Pentland, Bernt Schiele, Nuria Oliver, 1999, ICVS.

Support vector machine learning from heterogeneous data: an empirical analysis using protein sequence and structure

William Stafford Noble, Tony Jebara, Darrin P. Lewis, 2006, Bioinform..

Semi-supervised learning using greedy max-cut

Shih-Fu Chang, Jun Wang, Tony Jebara, 2013, J. Mach. Learn. Res..

Action Reaction Learning: Automatic Visual Analysis and Synthesis of Interactive Behaviour

Alex Pentland, Tony Jebara, A. Pentland, 1999, ICVS.

Variational low rank multinomials for collaborative filtering with side-information

Wei Wang, Tony Jebara, Ehtsham Elahi, 2019, RecSys.

Sensory-augmented computing: wearing the museum's guide

Bernt Schiele, Nuria Oliver, Tony Jebara, 2001 .

A New Distribution on the Simplex with Auto-Encoding Applications

David A. Knowles, Tony Jebara, Andrew Stirn, 2019, NeurIPS.

Generative Versus Discriminative Learning

Tony Jebara, T. Jebara, 2004 .

Density Estimation under Independent Similarly Distributed Sampling Assumptions

Tony Jebara, Yingbo Song, Kapil Thadani, 2007, NIPS.

Beta Survival Models pdf

Tony Jebara, Yves Raimond, David Hubbard, 2019, ArXiv.

3D Pose Estimation and Normalization for Face Recognition

Tony Jebara, T. Jebara, Tony Jebara, 1995 .

Semistochastic Quadratic Bound Methods

Dimitri Kanevsky, Anna Choromanska, Aleksandr Y. Aravkin, 2013, ICLR 2013.

Markov Models for Network-Behavior Modeling and Anonymization

Salvatore J. Stolfo, Tony Jebara, Yingbo Song, 2011 .

Permutation invariant SVMs

Tony Jebara, Pannagadatta K. Shivaswamy, T. Jebara, 2006, ICML.

Artwork personalization at netflix

Justin Basilico, Ashok Chandrashekar, Tony Jebara, 2018, RecSys.

Tree Dependent Identically Distributed Learning

Philip M. Long, Tony Jebara, T. Jebara, 2005 .

ADMM SLIM: Sparse Recommendations for Many Users

Harald Steck, Tony Jebara, Maria Dimakopoulou, 2020, WSDM.

$\propto$SVM for learning with label proportions pdf

Dong Liu, Shih-Fu Chang, Sanjiv Kumar, 2013, ICML 2013.

Approximating the Permanent with Belief Propagation pdf

Bert Huang, Tony Jebara, 2009, ArXiv.

Convex Invariance Learning

Tony Jebara, 2003, AISTATS.

Marginal Posterior Sampling for Slate Bandits

Nikos Vlassis, Tony Jebara, Maria Dimakopoulou, 2019, IJCAI.

When Enough is Enough: Location Tracking, Mosaic Theory, and Machine Learning

Steven M. Bellovin, Sebastian Zimmeck, Tony Jebara, 2014 .

DyPERS: Dynamic Personal Enhanced Reality System

Alex Pentland, Bernt Schiele, Nuria Oliver, 1998 .

Tracking Conversational Context for Machine Mediation of Human Discourse

Alex Pentland, Tony Jebara, Ali Rahimi, 2000 .

Variational Autoencoders for Collaborative Filtering

Matthew D. Hoffman, Dawen Liang, Tony Jebara, 2018, WWW.

Collaborative Place Models

Berk Kapicioglu, Robert E. Schapire, Tony Jebara, 2015, IJCAI.

Semistochastic Quadratic Bound Methods for Convex and Nonconvex Learning Problems pdf

Dimitri Kanevsky, Anna Choromanska, Aleksandr Y. Aravkin, 2014, ICLR.

Binary embeddings with structured hashed projections

Sanjiv Kumar, Yann LeCun, Mariusz Bojarski, 2015, ICML.

Exact Graph Structure Estimation with Degree Priors

Bert Huang, Tony Jebara, T. Jebara, 2009, 2009 International Conference on Machine Learning and Applications.

Discriminative, generative and imitative learning

Alex Pentland, Tony Jebara, A. Pentland, 2002 .

Nonstationary kernel combination

William Stafford Noble, Tony Jebara, Darrin P. Lewis, 2006, ICML.

Relative Margin Machines

Tony Jebara, Pannagadatta K. Shivaswamy, 2008, NIPS.

Large relative margin and applications

Tony Jebara, Pannagadatta K. Shivaswamy, T. Jebara, 2010 .

Active Multitask Learning with Committees pdf

Tony Jebara, Jingxi Xu, Da Tang, 2021, ArXiv.

Accordion: A Trainable Simulator for Long-Term Interactive Systems

Justin Basilico, Tony Jebara, Ehtsham Elahi, 2021, RecSys.

3 D Structure from 2 D Motion

Alex Pentland, Ali Azarbayejani, Tony Jebara, 2001 .

Maximum Weight b-Matching via Belief Propagation

Bert Huang, Tony Jebara, T. Jebara, 2006 .

Combining kernels for classification

Tony Jebara, Darrin P. Lewis, 2006 .

Structured Network Learning

Tony Jebara, T. Jebara, Stuart Andrews, 2006 .

A novel drill set for the enhancement and assessment of robotic surgical performance.

Tony Jebara, Celina Imielinska, T. Jebara, 2005, Studies in health technology and informatics.

Statistical Prediction of ENSO from Subsurface Sea Temperature Using a Nonlinear Dimensionality Reduction

Upmanu Lall, Tony Jebara, Carlos H.R. Lima, 2009, Journal of Climate.

Convex Invarian e Learning

Tony Jebara, 2003 .