- 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
- Soh, Yong Sheng and Chandrasekaran, Venkat (2020) A
Matrix Factorization Approach for Learning Semidefinite-Representable
Regularizers; 10.48550/arXiv.1701.01207
- Saunderson, James and Chandrasekaran, Venkat (2020) Terracini
convexity; Mathematical Programming; 10.1007/s10107-022-01774-y
- Taeb, Armeen; 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
- Berthet, Quentin and Chandrasekaran, Venkat (2019) Resource
Allocation for Statistical Estimation; 10.48550/arXiv.1412.6613
- Ziani, Juba; Chandrasekaran, Venkat; et el. (2019) Efficiently
characterizing games consistent with perturbed equilibrium
observations; 10.48550/arXiv.1603.01318
- 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.; 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
- Taeb, Armeen and Chandrasekaran, Venkat (2017) Sufficient
Dimension Reduction and Modeling Responses Conditioned on Covariates: An
Integrated Approach via Convex Optimization; 10.48550/arXiv.1508.03852
- 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; 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
- Soh, Yong Sheng and Chandrasekaran, Venkat (2015) High-dimensional
change-point estimation: Combining filtering with convex
optimization; ISBN 978-1-4673-7704-1; 151-155; 10.1109/ISIT.2015.7282435
- Chandrasekaran, Venkat and Shah, Parikshit (2014) Conic
Geometric Programming; ISBN 978-1-4799-3001-2; 1-4; 10.1109/CISS.2014.6814151
- 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.; 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
- Pilanci, Mert; El Ghaoui, Laurent; et el. (2012) Recovery
of Sparse Probability Measures via Convex Programming
- Chandrasekaran, Venkat; 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; Wakin, Michael B.; et el. (2012) Surflets:
a sparse representation for multidimensional functions containing smooth
discontinuities; ISBN 0-7803-8280-3; 565-565; 10.1109/ISIT.2004.1365602
- Chandrasekaran, Venkat; Johnson, Jason K.; et el. (2012) Maximum
Entropy Relaxation for Graphical Model Selection given Inconsistent
Statistics; ISBN 978-1-4244-1197-9; 625-629; 10.1109/SSP.2007.4301334
- Chandrasekaran, Venkat; Johnson, Jason K.; et el. (2012) Adaptive
Embedded Subgraph Algorithms using Walk-Sum Analysis
- Chandrasekaran, Venkat (2012) Convex
Optimization Methods for Graphs and Statistical Modeling
- Chandrasekaran, Venkat; Parrilo, Pablo A.; et el. (2012) Convex
Graph Invariants; SIAM Review; Vol. 54; No. 3; 513-541; 10.1137/100816900
- Liu, Ying; 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; 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
- Chandrasekaran, Venkat; 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
- 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; 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; 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
- Liu, Ying; Chandrasekaran, Venkat; et el. (2010) Feedback
Message Passing for Inference in Gaussian Graphical Models; ISBN
978-1-4244-6960-4; 1683-1687; 10.1109/ISIT.2010.5513321
- Chandrasekaran, Venkat; Srebro, Nathan; et el. (2010) Complexity
of Inference in Graphical Models
- 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
- Chandrasekaran, Venkat; Sanghavi, Sujay; et el. (2009) Sparse
and low-rank matrix decompositions; ISBN 978-1-4244-5870-7; 962-967;
10.1109/ALLERTON.2009.5394889
- Rich, Rebecca L.; 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; 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; Chandrasekaran, Venkat; et el. (2009) Exploiting
Sparse Markov and Covariance Structure in Multiresolution Models;
ISBN 978-1-60558-516-1; 177-184; 10.1145/1553374.1553397
- Choi, Myung Jin; 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; Srebro, Nathan; et el. (2008) Complexity
of Inference in Graphical Models; ISBN 974903949; 70-78; 10.48550/arXiv.1206.3240
- Chandrasekaran, Venkat; 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.; Chandrasekaran, Venkat; et el. (2007) Learning
Markov Structure by Maximum Entropy Relaxation; Proceedings of
Machine Learning Research; Vol. 2; 203-210