Venkat Chandrasekaran

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False discovery and its control in low rank estimation

Armeen Taeb, Parikshit Shah, Venkat Chandrasekaran, 2018, Journal of the Royal Statistical Society: Series B (Statistical Methodology).

Gaussian Multiresolution Models: Exploiting Sparse Markov and Covariance Structure

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

Fitting Tractable Convex Sets to Support Function Evaluations

Venkat Chandrasekaran, Yong Sheng Soh, V. Chandrasekaran, 2019, Discret. Comput. Geom..

Recovering Games from Perturbed Equilibrium Observations Using Convex Optimization pdf

Venkat Chandrasekaran, Katrina Ligett, Juba Ziani, 2016, ArXiv.

Counting Independent Sets Using the Bethe Approximation

Devavrat Shah, Jinwoo Shin, Michael Chertkov, 2011, SIAM J. Discret. Math..

Resource Allocation for Statistical Estimation

Venkat Chandrasekaran, Quentin Berthet, V. Chandrasekaran, 2014, Proceedings of the IEEE.

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.

Surflets: a sparse representation for multidimensional functions containing smooth discontinuities

Venkat Chandrasekaran, Richard G. Baraniuk, Michael B. Wakin, 2004, International Symposium onInformation Theory, 2004. ISIT 2004. Proceedings..

Resource Allocation for Statistical Estimation Adoptingageneralviewofthenotionofaresourceanditseffectonthequalityofadata source, the authors describe in this paper aframework for the allocation of a given set of resources to a collection of sources in order to optimize a specified metric of statisti

Venkat Chandrasekaran, Quentin Berthet, 2016 .

High-dimensional change-point estimation: Combining filtering with convex optimization

Venkat Chandrasekaran, Yong Sheng Soh, V. Chandrasekaran, 2014, 2015 IEEE International Symposium on Information Theory (ISIT).

Complexity of Inference in Graphical Models

Venkat Chandrasekaran, Nathan Srebro, Prahladh Harsha, 2008, UAI.

Finding Planted Subgraphs with Few Eigenvalues using the Schur-Horn Relaxation pdf

Venkat Chandrasekaran, Utkan Onur Candogan, V. Chandrasekaran, 2016, SIAM J. Optim..

A Matrix Factorization Approach for Learning Semidefinite-Representable Regularizers pdf

Venkat Chandrasekaran, Yong Sheng Soh, V. Chandrasekaran, 2017, ArXiv.

Relative entropy optimization and its applications

Parikshit Shah, Venkat Chandrasekaran, 2017, Math. Program..

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..

Modeling and estimation in Gaussian graphical models : maximum-entropy methods and walk-sum analysis

Venkat Chandrasekaran, V. Chandrasekaran, 2007 .

Regularization for Design

Venkat Chandrasekaran, Nikolai Matni, N. Matni, 2014, IEEE Transactions on Automatic Control.

Feedback message passing for inference in gaussian graphical models

Venkat Chandrasekaran, Anima Anandkumar, Alan S. Willsky, 2010, 2010 IEEE International Symposium on Information Theory.

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).

Interpreting latent variables in factor models via convex optimization

Armeen Taeb, Venkat Chandrasekaran, V. Chandrasekaran, 2016, Math. Program..

Representation and Compression of Multidimensional Piecewise Functions Using Surflets

Venkat Chandrasekaran, Richard G. Baraniuk, Michael B. Wakin, 2009, IEEE Transactions on Information Theory.

Recovery of Sparse Probability Measures via Convex Programming

Venkat Chandrasekaran, Mert Pilanci, Laurent El Ghaoui, 2012, NIPS.

Relative Entropy Relaxations for Signomial Optimization

Parikshit Shah, Venkat Chandrasekaran, V. Chandrasekaran, 2014, SIAM J. Optim..

Group symmetry and covariance regularization

Parikshit Shah, Venkat Chandrasekaran, V. Chandrasekaran, 2011, 2012 46th Annual Conference on Information Sciences and Systems (CISS).

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.

Convex graph invariants

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

Learning Semidefinite Regularizers

Venkat Chandrasekaran, Yong Sheng Soh, 2019, Found. Comput. Math..

Exploiting sparse Markov and covariance structure in multiresolution models

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

Computational and statistical tradeoffs via convex relaxation

Michael I. Jordan, Venkat Chandrasekaran, V. Chandrasekaran, 2012, Proceedings of the National Academy of Sciences.

Learning Semidefinite-Representable Regularizers

Venkat Chandrasekaran, Yong Sheng Soh, 2019 .

The Convex Geometry of Linear Inverse Problems

Pablo A. Parrilo, Venkat Chandrasekaran, Alan S. Willsky, 2010, Foundations of Computational Mathematics.

Message passing and distributed statistical inference

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

Rank-Sparsity Incoherence for Matrix Decomposition

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

Efficiently Characterizing Games Consistent with Perturbed Equilibrium Observations

Venkat Chandrasekaran, Katrina Ligett, Juba Ziani, 2017 .

Regularization for design

Venkat Chandrasekaran, Nikolai Matni, N. Matni, 2016, 53rd IEEE Conference on Decision and Control.

Convex graph invariant relaxations for graph edit distance pdf

Venkat Chandrasekaran, Utkan Onur Candogan, V. Chandrasekaran, 2019, Mathematical Programming.

Feedback message passing for inference in gaussian graphical models

Venkat Chandrasekaran, Anima Anandkumar, Alan S. Willsky, 2010, ISIT.

Convex graph invariants

Pablo A. Parrilo, Venkat Chandrasekaran, Alan S. Willsky, 2012, CISS.

Conic geometric programming

Parikshit Shah, Venkat Chandrasekaran, V. Chandrasekaran, 2013, 2014 48th Annual Conference on Information Sciences and Systems (CISS).

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.

Convex optimization methods for graphs and statistical modeling

Venkat Chandrasekaran, V. Chandrasekaran, 2011 .

Adaptive Embedded Subgraph Algorithms using Walk-Sum Analysis

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

Iterative projections for signal identification on manifolds: Global recovery guarantees

Parikshit Shah, Venkat Chandrasekaran, V. Chandrasekaran, 2011, 2011 49th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

Learning Markov Structure by Maximum Entropy Relaxation

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

Spectrahedral Regression

Venkat Chandrasekaran, Eliza O'Reilly, 2021 .

A note on convex relaxations for the inverse eigenvalue problem

Venkat Chandrasekaran, Yong Sheng Soh, Utkan Candogan, 2021, Optim. Lett..

Publisher Correction to: Signomial and polynomial optimization via relative entropy and partial dualization

Adam Wierman, Venkat Chandrasekaran, Riley Murray, 2021, Math. Program. Comput..

Compressing Piecewise Smooth Multidimensional Functions Using Surflets: Rate-Distortion Analysis

Venkat Chandrasekaran, Richard G. Baraniuk, Michael B. Wakin, 2004 .

Compression of Higher Dimensional Functions Containing Smooth Discontinuities

Venkat Chandrasekaran, Richard G. Baraniuk, Michael B. Wakin, 2004 .

Computational and Sample Tradeoffs via Convex Relaxation

Michael I. Jordan, Venkat Chandrasekaran, V. Chandrasekaran, 2012 .