Chandrasekaran, Venkat

Article from CaltechAUTHORS

• Taeb, Armeen and Bühlmann, Peter, et el. (2024) Model selection over partially ordered sets; Proceedings of the National Academy of Sciences; Vol. 121; No. 8; e2314228121; 10.1073/pnas.2314228121
• Candogan, Utkan Onur and Chandrasekaran, Venkat (2022) Convex graph invariant relaxations for graph edit distance; Mathematical Programming; Vol. 191; No. 2; 595-629; 10.1007/s10107-020-01564-4
• Saunderson, James and Chandrasekaran, Venkat (2020) Terracini convexity; Mathematical Programming; 10.1007/s10107-022-01774-y
• Taeb, Armeen and Shah, Parikshit, et el. (2020) False Discovery and Its Control in Low Rank Estimation; Journal of the Royal Statistical Society: Series B; Vol. 82; No. 4; 997-1027; 10.1111/rssb.12387
• Soh, Yong Sheng and Chandrasekaran, Venkat (2019) Learning Semidefinite-Representable Regularizers; Foundations of Computational Mathematics; Vol. 19; No. 2; 375-434; 10.1007/s10208-018-9386-z
• Candogan, Utkan-Onur and Chandrasekaran, Venkat (2018) Finding Planted Subgraphs with Few Eigenvalues using the Schur-Horn Relaxation; SIAM Journal on Optimization; Vol. 28; No. 1; 735-759; 10.1137/16M1075144
• Taeb, Armeen and Chandrasekaran, Venkat (2018) Interpreting Latent Variables in Factor Models via Convex Optimization; Mathematical Programming; Vol. 167; No. 1; 129-154; 10.1007/s10107-017-1187-7
• Taeb, A. and Reager, J. T., et el. (2017) A Statistical Graphical Model of the California Reservoir System; Water Resources Research; Vol. 53; No. 11; 9721-9739; 10.1002/2017WR020412
• Soh, Yong Sheng and Chandrasekaran, Venkat (2017) High-dimensional change-point estimation: Combining filtering with convex optimization; Applied and Computational Harmonic Analysis; Vol. 43; No. 1; 122-147; 10.1016/j.acha.2015.11.003
• Chandrasekaran, Venkat and Shah, Parikshit (2017) Relative entropy optimization and its applications; Mathematical Programming; Vol. 161; No. 1-2; 1-32; 10.1007/s10107-016-0998-2
• Matni, Nikolai and Chandrasekaran, Venkat (2016) Regularization for Design; IEEE Transactions on Automatic Control; Vol. 61; No. 12; 3991-4006; 10.1109/TAC.2016.2517570
• Li, Yen-Li and Chandrasekaran, Viswanathan, et el. (2016) Primate TRIM5 proteins form hexagonal nets on HIV-1 capsids; eLife; Vol. 5; Art. No. 16269; PMCID PMC4936896; 10.7554/eLife.16269
• Chandrasekaran, Venkat and Shah, Parikshit (2016) Relative Entropy Relaxations for Signomial Optimization; SIAM Journal on Optimization; Vol. 26; No. 2; 1147-1173; 10.1137/140988978
• Berthet, Quentin and Chandrasekaran, Venkat (2016) Resource Allocation for Statistical Estimation; Proceedings of the IEEE; Vol. 104; No. 1; 111-125; 10.1109/JPROC.2015.2494098
• Chandrasekaran, Venkat and Jordan, Michael I. (2013) Computational and statistical tradeoffs via convex relaxation; Proceedings of the National Academy of Sciences of the United States of America; Vol. 110; No. 13; E1181-E1190; PMCID PMC3612621; 10.1073/pnas.1302293110
• Saunderson, J. and Chandrasekaran, V., et el. (2012) Diagonal and Low-Rank Matrix Decompositions, Correlation Matrices, and Ellipsoid Fitting; SIAM Journal on Matrix Analysis and Applications; Vol. 33; No. 4; 1395-1416; 10.1137/120872516
• Chandrasekaran, Venkat and Recht, Benjamin, et el. (2012) The Convex Geometry of Linear Inverse Problems; Foundations of Computational Mathematics; Vol. 12; No. 6; 805-849; 10.1007/s10208-012-9135-7
• Chandrasekaran, Venkat and Parrilo, Pablo A., et el. (2012) Convex Graph Invariants; SIAM Review; Vol. 54; No. 3; 513-541; 10.1137/100816900
• Chandrasekaran, Venkat and Parrilo, Pablo A., et el. (2012) Rejoinder: Latent variable graphical model selection via convex optimization; Annals of Statistics; Vol. 40; No. 4; 2005-2013; 10.1214/12-AOS1020
• Liu, Ying and Chandrasekaran, Venkat, et el. (2012) Feedback Message Passing for Inference in Gaussian Graphical Models; IEEE Transactions on Signal Processing; Vol. 60; No. 8; 4135-4150; 10.1109/TSP.2012.2195656
• Chandrasekaran, Venkat and Parrilo, Pablo A., et el. (2012) Latent Variable Graphical Model Selection via Convex Optimization; Annals of Statistics; Vol. 40; No. 4; 1935-1967; 10.1214/11-AOS949
• Shah, Parikshit and Chandrasekaran, Venkat (2012) Group Symmetry and Covariance Regularization; Electronic Journal of Statistics; Vol. 6; 1600-1640; 10.1214/12-EJS723
• Chandrasekaran, Venkat and Sanghavi, Sujay, et el. (2011) Rank-Sparsity Incoherence for Matrix Decomposition; SIAM Journal of Optimization; Vol. 21; No. 2; 572-596; 10.1137/090761793
• Chandrasekaran, Venkat and Chertkov, Misha, et el. (2011) Counting Independent Sets Using the Bethe Approximation; SIAM Journal on Discrete Mathematics; Vol. 25; No. 2; 1012-1034; 10.1137/090767145
• Choi, Myung Jin and Chandrasekaran, Venkat (2010) Gaussian Multiresolution Models: Exploiting Sparse Markov and Covariance Structure; IEEE Transactions on Signal Processing; Vol. 58; No. 3; 1012-1024; 10.1109/TSP.2009.2036042
• Rich, Rebecca L. and Papalia, Giuseppe A., et el. (2009) A global benchmark study using affinity-based biosensors; Analytical Biochemistry; Vol. 386; No. 2; 194-216; PMCID PMC3793259; 10.1016/j.ab.2008.11.021
• Chandrasekaran, Venkat and Wakin, Michael B., et el. (2009) Representation and Compression of Multidimensional Piecewise Functions Using Surflets; IEEE Transactions on Information Theory; Vol. 55; No. 1; 374-400; 10.1109/TIT.2008.2008153
• Choi, Myung Jin and Chandrasekaran, Venkat, et el. (2008) Multiscale stochastic modeling for tractable inference and data assimilation; Computer Methods in Applied Mechanics and Engineering; Vol. 197; No. 43-44; 3492-3515; 10.1016/j.cma.2007.12.021
• Chandrasekaran, Venkat and Johnson, Jason K., et el. (2008) Estimation in Gaussian Graphical Models Using Tractable Subgraphs: A Walk-Sum Analysis; IEEE Transactions on Signal Processing; Vol. 56; No. 5; 1916-1930; 10.1109/TSP.2007.912280
• Johnson, Jason K. and Chandrasekaran, Venkat, et el. (2007) Learning Markov Structure by Maximum Entropy Relaxation; Proceedings of Machine Learning Research; Vol. 2; 203-210