Surflets: a sparse representation for multidimensional functions containing smooth discontinuities. - Venkat Chandrasekaran; Michael B. Wakin; Dror Baron; Richard G. Baraniuk (ISIT, 2004)

Adaptive Embedded Subgraph Algorithms using Walk-Sum Analysis. - Venkat Chandrasekaran; Jason K. Johnson; Alan S. Willsky (NIPS, 2007)

Learning Markov Structure by Maximum Entropy Relaxation. - Jason K. Johnson; Venkat Chandrasekaran; Alan S. Willsky (AISTATS, 2007)

Maximum entropy relaxation for multiscale graphical model selection. - Myung Jin Choi; Venkat Chandrasekaran; Alan S. Willsky (ICASSP, 2008)

Complexity of Inference in Graphical Models. - Venkat Chandrasekaran; Nathan Srebro; Prahladh Harsha (UAI, 2008)

Estimation in Gaussian Graphical Models Using Tractable Subgraphs: A Walk-Sum Analysis. - Venkat Chandrasekaran; Jason K. Johnson; Alan S. Willsky (IEEE Trans. Signal Process., 2008)

Sparse and low-rank matrix decompositions. - Venkat Chandrasekaran; Sujay Sanghavi; Pablo A. Parrilo; Alan S. Willsky (Allerton, 2009)

Exploiting sparse Markov and covariance structure in multiresolution models. - Myung Jin Choi; Venkat Chandrasekaran; Alan S. Willsky (ICML, 2009)

Representation and Compression of Multidimensional Piecewise Functions Using Surflets. - Venkat Chandrasekaran; Michael B. Wakin; Dror Baron; Richard G. Baraniuk (IEEE Trans. Inf. Theory, 2009)

Latent variable graphical model selection via convex optimization. - Venkat Chandrasekaran; Pablo A. Parrilo; Alan S. Willsky (Allerton, 2010)

The Convex algebraic geometry of linear inverse problems. - Venkat Chandrasekaran; Benjamin Recht; Pablo A. Parrilo; Alan S. Willsky (Allerton, 2010)

Gaussian multiresolution models: exploiting sparse Markov and covariance structure. - Myung Jin Choi; Venkat Chandrasekaran; Alan S. Willsky (IEEE Trans. Signal Process., 2010)

Iterative projections for signal identification on manifolds: Global recovery guarantees. - Parikshit Shah; Venkat Chandrasekaran (Allerton, 2011)

Tree-structured statistical modeling via convex optimization. - James Saunderson; Venkat Chandrasekaran; Pablo A. Parrilo; Alan S. Willsky (CDC/ECC, 2011)

Counting Independent Sets Using the Bethe Approximation. - Venkat Chandrasekaran; Misha Chertkov; David Gamarnik; Devavrat Shah; Jinwoo Shin (SIAM J. Discret. Math., 2011)

Rank-Sparsity Incoherence for Matrix Decomposition. - Venkat Chandrasekaran; Sujay Sanghavi; Pablo A. Parrilo; Alan S. Willsky (SIAM J. Optim., 2011)

Convex optimization methods for graphs and statistical modeling. - Venkat Chandrasekaran (2011)

Group symmetry and covariance regularization. - Parikshit Shah; Venkat Chandrasekaran (CISS, 2012)

Recovery of Sparse Probability Measures via Convex Programming. - Mert Pilanci; Laurent El Ghaoui; Venkat Chandrasekaran (NIPS, 2012)

Rejoinder: Latent variable graphical model selection via convex optimization - Venkat Chandrasekaran; Pablo A. Parrilo; Alan S. Willsky (CoRR, 2012)

Computational and Statistical Tradeoffs via Convex Relaxation - Venkat Chandrasekaran; Michael I. Jordan (CoRR, 2012)

The Convex Geometry of Linear Inverse Problems. - Venkat Chandrasekaran; Benjamin Recht; Pablo A. Parrilo; Alan S. Willsky (Found. Comput. Math., 2012)

Diagonal and Low-Rank Matrix Decompositions, Correlation Matrices, and Ellipsoid Fitting. - James Saunderson; Venkat Chandrasekaran; Pablo A. Parrilo; Alan S. Willsky (SIAM J. Matrix Anal. Appl., 2012)

Convex Graph Invariants. - Venkat Chandrasekaran; Pablo A. Parrilo; Alan S. Willsky (SIAM Rev., 2012)

Feedback Message Passing for Inference in Gaussian Graphical Models. - Ying Liu 009; Venkat Chandrasekaran; Animashree Anandkumar; Alan S. Willsky (IEEE Trans. Signal Process., 2012)

Conic geometric programming. - Venkat Chandrasekaran; Parikshit Shah (CISS, 2014)

High-dimensional change-point estimation: Combining filtering with convex optimization. - Yong Sheng Soh; Venkat Chandrasekaran (ISIT, 2015)

Recovering Games from Perturbed Equilibrium Observations Using Convex Optimization. - Juba Ziani; Venkat Chandrasekaran; Katrina Ligett (CoRR, 2016)

Resource Allocation for Statistical Estimation. - Quentin Berthet; Venkat Chandrasekaran (Proc. IEEE, 2016)

Relative Entropy Relaxations for Signomial Optimization. - Venkat Chandrasekaran; Parikshit Shah (SIAM J. Optim., 2016)

Regularization for Design. - Nikolai Matni; Venkat Chandrasekaran (IEEE Trans. Autom. Control., 2016)

A Matrix Factorization Approach for Learning Semidefinite-Representable Regularizers. - Yong Sheng Soh; Venkat Chandrasekaran (CoRR, 2017)

Relative entropy optimization and its applications. - Venkat Chandrasekaran; Parikshit Shah (Math. Program., 2017)

Interpreting latent variables in factor models via convex optimization. - Armeen Taeb; Venkat Chandrasekaran (Math. Program., 2018)

Finding Planted Subgraphs with Few Eigenvalues using the Schur-Horn Relaxation. - Utkan Onur Candogan; Venkat Chandrasekaran (SIAM J. Optim., 2018)

Learning Semidefinite Regularizers. - Yong Sheng Soh; Venkat Chandrasekaran (Found. Comput. Math., 2019)

Learning Exponential Family Graphical Models with Latent Variables using Regularized Conditional Likelihood. - Armeen Taeb; Parikshit Shah; Venkat Chandrasekaran (CoRR, 2020)

Fitting Tractable Convex Sets to Support Function Evaluations. - Yong Sheng Soh; Venkat Chandrasekaran (Discret. Comput. Geom., 2021)

Newton Polytopes and Relative Entropy Optimization. - Riley Murray; Venkat Chandrasekaran; Adam Wierman (Found. Comput. Math., 2021)

Signomial and polynomial optimization via relative entropy and partial dualization. - Riley Murray; Venkat Chandrasekaran; Adam Wierman (Math. Program. Comput., 2021)

Publisher Correction to: Signomial and polynomial optimization via relative entropy and partial dualization. - Riley Murray; Venkat Chandrasekaran; Adam Wierman (Math. Program. Comput., 2021)

Convex graph invariant relaxations for graph edit distance. - Utkan Onur Candogan; Venkat Chandrasekaran (Math. Program., 2022)

Modeling groundwater levels in California's Central Valley by hierarchical Gaussian process and neural network regression. - Anshuman Pradhan; Kyra H. Adams; Venkat Chandrasekaran; Zhen Liu; John T. Reager; Andrew M. Stuart; Michael J. Turmon (CoRR, 2023)

Spectrahedral Regression. - Eliza O'Reilly; Venkat Chandrasekaran (SIAM J. Optim., 2023)

Terracini convexity. - James Saunderson; Venkat Chandrasekaran (Math. Program., 2023)

Kronecker Product Approximation of Operators in Spectral Norm via Alternating SDP. - Mareike Dressler; André Uschmajew; Venkat Chandrasekaran (SIAM J. Matrix Anal. Appl., 2023)

Poset-Markov Channels: Capacity via Group Symmetry. - Eray Unsal Atay; Eitan Levin; Venkat Chandrasekaran; Victoria Kostina (CoRR, 2025)