Venkat Chandrasekaran

According to our database, Venkat Chandrasekaran authored at least 46 papers between 2004 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Kronecker Product Approximation of Operators in Spectral Norm via Alternating SDP.

Mareike Dressler, André Uschmajew, Venkat Chandrasekaran

SIAM J. Matrix Anal. Appl., December, 2023

Terracini convexity.

James Saunderson, Venkat Chandrasekaran

Math. Program., March, 2023

Spectrahedral Regression.

Eliza O'Reilly, Venkat Chandrasekaran

SIAM J. Optim., 2023

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

2022

Convex graph invariant relaxations for graph edit distance.

Utkan Onur Candogan, Venkat Chandrasekaran

Math. Program., 2022

2021

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

Riley Murray, Venkat Chandrasekaran, Adam Wierman

Math. Program. Comput., 2021

Signomial and polynomial optimization via relative entropy and partial dualization.

Riley Murray, Venkat Chandrasekaran, Adam Wierman

Math. Program. Comput., 2021

Newton Polytopes and Relative Entropy Optimization.

Riley Murray, Venkat Chandrasekaran, Adam Wierman

Found. Comput. Math., 2021

Fitting Tractable Convex Sets to Support Function Evaluations.

Yong Sheng Soh, Venkat Chandrasekaran

Discret. Comput. Geom., 2021

2020

Learning Exponential Family Graphical Models with Latent Variables using Regularized Conditional Likelihood.

Armeen Taeb, Parikshit Shah, Venkat Chandrasekaran

CoRR, 2020

2019

Learning Semidefinite Regularizers.

Yong Sheng Soh, Venkat Chandrasekaran

Found. Comput. Math., 2019

2018

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

Utkan Onur Candogan, Venkat Chandrasekaran

SIAM J. Optim., 2018

Interpreting latent variables in factor models via convex optimization.

Armeen Taeb, Venkat Chandrasekaran

Math. Program., 2018

2017

Relative entropy optimization and its applications.

Venkat Chandrasekaran, Parikshit Shah

Math. Program., 2017

A Matrix Factorization Approach for Learning Semidefinite-Representable Regularizers.

Yong Sheng Soh, Venkat Chandrasekaran

CoRR, 2017

2016

Regularization for Design.

Nikolai Matni, Venkat Chandrasekaran

IEEE Trans. Autom. Control., 2016

Relative Entropy Relaxations for Signomial Optimization.

Venkat Chandrasekaran, Parikshit Shah

SIAM J. Optim., 2016

Resource Allocation for Statistical Estimation.

Quentin Berthet, Venkat Chandrasekaran

Proc. IEEE, 2016

Recovering Games from Perturbed Equilibrium Observations Using Convex Optimization.

Juba Ziani, Venkat Chandrasekaran, Katrina Ligett

CoRR, 2016

2015

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

Yong Sheng Soh, Venkat Chandrasekaran

Proceedings of the IEEE International Symposium on Information Theory, 2015

2014

Conic geometric programming.

Venkat Chandrasekaran, Parikshit Shah

Proceedings of the 48th Annual Conference on Information Sciences and Systems, 2014

2012

Feedback Message Passing for Inference in Gaussian Graphical Models.

Ying Liu, Venkat Chandrasekaran, Animashree Anandkumar, Alan S. Willsky

IEEE Trans. Signal Process., 2012

Convex Graph Invariants.

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

SIAM Rev., 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

The Convex Geometry of Linear Inverse Problems.

Venkat Chandrasekaran, Benjamin Recht, Pablo A. Parrilo, Alan S. Willsky

Found. Comput. Math., 2012

Computational and Statistical Tradeoffs via Convex Relaxation

Venkat Chandrasekaran, Michael I. Jordan

CoRR, 2012

Rejoinder: Latent variable graphical model selection via convex optimization

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

CoRR, 2012

Recovery of Sparse Probability Measures via Convex Programming.

Mert Pilanci, Laurent El Ghaoui, Venkat Chandrasekaran

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Group symmetry and covariance regularization.

Parikshit Shah, Venkat Chandrasekaran

Proceedings of the 46th Annual Conference on Information Sciences and Systems, 2012

2011

Convex optimization methods for graphs and statistical modeling.

Venkat Chandrasekaran

PhD thesis, 2011

Rank-Sparsity Incoherence for Matrix Decomposition.

Venkat Chandrasekaran, Sujay Sanghavi, Pablo A. Parrilo, Alan S. Willsky

SIAM J. Optim., 2011

Counting Independent Sets Using the Bethe Approximation.

Venkat Chandrasekaran, Misha Chertkov, David Gamarnik, Devavrat Shah, Jinwoo Shin

SIAM J. Discret. Math., 2011

Tree-structured statistical modeling via convex optimization.

James Saunderson, Venkat Chandrasekaran, Pablo A. Parrilo, Alan S. Willsky

Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, 2011

Iterative projections for signal identification on manifolds: Global recovery guarantees.

Parikshit Shah, Venkat Chandrasekaran

Proceedings of the 49th Annual Allerton Conference on Communication, 2011

2010

Gaussian multiresolution models: exploiting sparse Markov and covariance structure.

Myung Jin Choi, Venkat Chandrasekaran, Alan S. Willsky

IEEE Trans. Signal Process., 2010

The Convex algebraic geometry of linear inverse problems.

Venkat Chandrasekaran, Benjamin Recht, Pablo A. Parrilo, Alan S. Willsky

Proceedings of the 48th Annual Allerton Conference on Communication, 2010

Latent variable graphical model selection via convex optimization.

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

Proceedings of the 48th Annual Allerton Conference on Communication, 2010

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

Exploiting sparse Markov <i>and</i> covariance structure in multiresolution models.

Myung Jin Choi, Venkat Chandrasekaran, Alan S. Willsky

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Sparse and low-rank matrix decompositions.

Venkat Chandrasekaran, Sujay Sanghavi, Pablo A. Parrilo, Alan S. Willsky

Proceedings of the 47th Annual Allerton Conference on Communication, 2009

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

Complexity of Inference in Graphical Models.

Venkat Chandrasekaran, Nathan Srebro, Prahladh Harsha

Proceedings of the UAI 2008, 2008

Maximum entropy relaxation for multiscale graphical model selection.

Myung Jin Choi, Venkat Chandrasekaran, Alan S. Willsky

Proceedings of the IEEE International Conference on Acoustics, 2008

2007

Learning Markov Structure by Maximum Entropy Relaxation.

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

Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

Adaptive Embedded Subgraph Algorithms using Walk-Sum Analysis.

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

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2004

Surflets: a sparse representation for multidimensional functions containing smooth discontinuities.

Venkat Chandrasekaran, Michael B. Wakin, Dror Baron, Richard G. Baraniuk

Proceedings of the 2004 IEEE International Symposium on Information Theory, 2004