Convexity, Optimization and Data Science

Head:
Venkat Chandrasekaran

Homepage

Phone:
+49 (0) 341 - 9959 - 50

Fax:
+49 (0) 341 - 9959 - 658

Address:
Inselstr. 22
04103 Leipzig

Publications Group Venkat Chandrasekaran

Preprints

Eliza O'Reilly and Venkat Chandrasekaran: Spectrahedral regression
Repository Open Access

Yong Sheng Soh and Venkat Chandrasekaran: A matrix factorization approach for learning semidefinite-representable regularizers
Repository Open Access

James Francis Saunderson and Venkat Chandrasekaran: Terracini convexity
Repository Open Access

Armeen Taeb ; Parikshit Shah and Venkat Chandrasekaran: Learning exponential family graphical models with latent variables using regularized conditional likelihood
Repository Open Access

Juba Ziani ; Venkat Chandrasekaran and Katrina Ligett: Efficiently characterizing games consistent with perturbed equilibrium observations
Repository Open Access

Armeen Taeb and Venkat Chandrasekaran: Sufficient dimension reduction and modeling responses conditioned on covariates : an integrated approach via convex optimization
Repository Open Access

Venkat Chandrasekaran ; Michael B. Wakin ; Dror Baron and Richard G. Baraniuk: Compressing piecewise smooth multidimensional functions using surflets : rate-distortion analysis
Repository Open Access

Publications

Utkan Onur Candogan ; Yong Sheng Soh and Venkat Chandrasekaran: A note on convex relaxations for the inverse eigenvalue problem
In: Optimization letters, 15 (2021), p. 2757-2772
Bibtex DOI: 10.1007/s11590-021-01708-1 ARXIV: https://arxiv.org/abs/1911.02225
Repository Open Access

Riley Murray ; Venkat Chandrasekaran and Adam Wierman: Signomial and polynomial optimization via relative entropy and partial dualization
In: Mathematical programming computation, 13 (2021) 2, p. 257-295
Bibtex DOI: 10.1007/s12532-020-00193-4 ARXIV: https://arxiv.org/abs/1907.00814
Repository Open Access

Riley Murray ; Venkat Chandrasekaran and Adam Wierman: Newton polytopes and relative entropy optimization
In: Foundations of computational mathematics, 21 (2021) 6, p. 1703-1737
Bibtex DOI: 10.1007/s10208-021-09497-w ARXIV: https://arxiv.org/abs/1810.01614
Repository Open Access

Riley Murray ; Venkat Chandrasekaran and Adam Wierman: Publisher correction to: 'Signomial and polynomial optimization via relative entropy and partial dualization' [In: Mathematical programming computation 13(2021)2, 257-295]
In: Mathematical programming computation, 13 (2021) 2, p. 297-299
Bibtex DOI: 10.1007/s12532-021-00201-1 ARXIV: https://arxiv.org/abs/1907.00814
Repository Open Access

Yong Sheng Soh and Venkat Chandrasekaran: Fitting tractable convex sets to support function evaluations
In: Discrete and computational geometry, 66 (2021) 2, p. 510-551
Bibtex DOI: 10.1007/s00454-020-00258-0 ARXIV: https://arxiv.org/abs/1903.04194
Repository Open Access

Utkan Onur Candogan and Venkat Chandrasekaran: Convex graph invariant relaxations for graph edit distance
In: Mathematical programming, Vol. not yet known, pp. not yet known
Bibtex DOI: 10.1007/s10107-020-01564-4 ARXIV: https://arxiv.org/abs/1904.08934
Repository Open Access

Armeen Taeb ; Parikshit Shah and Venkat Chandrasekaran: False discovery and its control in low rank estimation
In: Journal of the Royal Statistical Society / B, 82 (2020) 4, p. 997-1027
Bibtex DOI: 10.1111/rssb.12387 ARXIV: https://arxiv.org/abs/1810.08595
Repository Open Access

Yong Sheng Soh and Venkat Chandrasekaran: Learning semidefinite regularizers
In: Foundations of computational mathematics, 19 (2019) 2, p. 375-434
Bibtex DOI: 10.1007/s10208-018-9386-z ARXIV: https://arxiv.org/abs/1701.01207
Repository Open Access

Utkan Onur Candogan and Venkat Chandrasekaran: Finding planted subgraphs with few eigenvalues using the Schur-Horn relaxation
In: SIAM journal on optimization, 28 (2018) 1, p. 735-759
Bibtex DOI: 10.1137/16M1075144 ARXIV: https://arxiv.org/abs/1605.04008
Repository Open Access

Armeen Taeb and Venkat Chandrasekaran: Interpreting latent variables in factor models via convex optimization
In: Mathematical programming, 167 (2018) 1, p. 129-154
Bibtex DOI: 10.1007/s10107-017-1187-7 ARXIV: https://arxiv.org/abs/1601.00389
Repository Open Access

Venkat Chandrasekaran and Parikshit Shah: Relative entropy optimization and its applications
In: Mathematical programming, 161 (2017) 1/2, p. 1-32
Bibtex DOI: 10.1007/s10107-016-0998-2

Yong Sheng Soh and Venkat Chandrasekaran: High-dimensional change-point estimation : combining filtering with convex optimization
In: Applied and computational harmonic analysis, 43 (2017) 1, p. 122-147
Bibtex DOI: 10.1016/j.acha.2015.11.003 ARXIV: https://arxiv.org/abs/1412.3731
Repository Open Access

Armeen Taeb ; John T. Reager ; Michael Turmon and Venkat Chandrasekaran: A statistical graphical model of the California reservoir system
In: Water resources research, 53 (2017) 11, p. 9721-9739
Bibtex DOI: 10.1002/2017WR020412 ARXIV: https://arxiv.org/abs/1606.08098
Repository Open Access

Quentin Berthet and Venkat Chandrasekaran: Resource allocation for statistical estimation
In: Proceedings of the IEEE, 104 (2016) 1, p. 111-125
Bibtex DOI: 10.1109/JPROC.2015.2494098 ARXIV: https://arxiv.org/abs/1412.6613
Repository Open Access

Venkat Chandrasekaran and Parikshit Shah: Relative entropy relaxations for signomial optimization
In: SIAM journal on optimization, 26 (2016) 2, p. 1147-1173
Bibtex DOI: 10.1137/140988978 ARXIV: https://arxiv.org/abs/1409.7640
Repository Open Access

Nikolai Matni and Venkat Chandrasekaran: Regularization for design
In: IEEE transactions on automatic control, 61 (2016) 12, p. 3991-4006
Bibtex DOI: 10.1109/TAC.2016.2517570 ARXIV: https://arxiv.org/abs/1404.1972
Repository Open Access

Yong Sheng Soh and Venkat Chandrasekaran: High-dimensional change-point estimation : combining filtering with convex optimization
In: IEEE international symposium on information theory proceedings (ISIT) 2015 : Hong Kong Convention and Exhibition Centre, Hong Kong, 14-19 June 2015
Piscataway, NY : IEEE, 2015. - P. 151-155
Bibtex DOI: 10.1109/ISIT.2015.7282435 ARXIV: https://arxiv.org/abs/1412.3731
Repository Open Access

Venkat Chandrasekaran and Parikshit Shah: Conic geometric programming
In: 48th annual conference on information sciences and systems (CISS) 19-21 March 2014, Princeton, NJ
Piscataway, NJ : IEEE, 2014. - P. 1-4
Bibtex DOI: 10.1109/CISS.2014.6814151 ARXIV: https://arxiv.org/abs/1310.0899
Repository Open Access

Nikolai Matni and Venkat Chandrasekaran: Regularization for design
In: 53rd IEEE annual conference on decision and control (CDC), 2014 15-17 Dec. 2014, Los Angeles, California, USA
Piscataway, NY : IEEE, 2014. - P. 1111-1118
Bibtex DOI: 10.1109/CDC.2014.7039530 ARXIV: https://arxiv.org/abs/1404.1972
Repository Open Access

Venkat Chandrasekaran and Michael I. Jordan: Computational and statistical tradeoffs via convex relaxation
In: Proceedings of the National Academy of Sciences of the United States of America, 110 (2013) 13, p. E1181-E1190
Bibtex DOI: 10.1073/pnas.1302293110 ARXIV: https://arxiv.org/abs/1211.1073
Repository Open Access

Parikshit Shah and Venkat Chandrasekaran: Erratum: 'Group symmetry and covariance regularization' [In: Electron. J. Statist. 6(2012),1600-1640]
In: Electronic journal of statistics, 7 (2013), p. 3057-3058
Bibtex DOI: 10.1214/13-EJS871
Journal Open Access

Venkat Chandrasekaran ; Pablo A. Parrilo and Alan S. Willsky: Latent variable graphical model selection via convex optimization
In: The annals of statistics, 40 (2012) 4, p. 1935-1967
Bibtex DOI: 10.1214/11-AOS949 ARXIV: https://arxiv.org/abs/1008.1290
Repository Open Access

Venkat Chandrasekaran ; Pablo A. Parrilo and Alan S. Willsky: Convex graph invariants
In: SIAM review, 54 (2012) 3, p. 513-541
Bibtex DOI: 10.1137/100816900 ARXIV: https://arxiv.org/abs/1012.0623
Repository Open Access

Venkat Chandrasekaran ; Pablo A. Parrilo and Alan S. Willsky: Convex graph invariants
In: 46th annual conference on information sciences and systems (CISS) : 21-23 March 2012, Princeton University, Princeton, NJ, USA
Piscataway, NJ : IEEE, 2012. - P. 1-6
Bibtex DOI: 10.1109/CISS.2012.6310764 ARXIV: https://arxiv.org/abs/1012.0623
Repository Open Access

Venkat Chandrasekaran ; Benjamin Recht ; Pablo A. Parrilo and Alan S. Willsky: The convex geometry of linear inverse problems
In: Foundations of computational mathematics, 12 (2012) 6, p. 805-849
Bibtex DOI: 10.1007/s10208-012-9135-7 ARXIV: https://arxiv.org/abs/1012.0621
Repository Open Access

Ying Liu ; Venkat Chandrasekaran ; Animashree Anandkumar and Alan S. Willsky: Feedback message passing for inference in Gaussian graphical models
In: IEEE transactions on signal processing, 60 (2012) 8, p. 4135-4150
Bibtex DOI: 10.1109/TSP.2012.2195656 ARXIV: https://arxiv.org/abs/1105.1853
Repository Open Access

Pablo A. Parrilo ; Alan S. Willsky and Venkat Chandrasekaran: Rejoinder: Latent variable graphical model selection via convex optimization
In: The annals of statistics, 40 (2012) 4, p. 2005-2013
Bibtex DOI: 10.1214/12-AOS1020 ARXIV: https://arxiv.org/abs/1211.0835
Repository Open Access

Mert Pilanci ; Laurent el Ghaoui and Venkat Chandrasekaran: Recovery of sparse probability measures via convex programming
In: Advances in neural information processing systems 25 : NIPS 2012 ; 26th annual conference on neural information processing systems 2012, held December 3-6, 2012, Lake Tahoe, Nevada, United States / Peter L. Bartlett (ed.)
La Jolla, CA : Neural Information Processing Systems, 2012. - P. 2429-2437
Bibtex LINK: https://openreview.net/forum?id=HJNTNwWO-S
Repository Open Access

James Francis Saunderson ; Venkat Chandrasekaran ; Pablo A. Parrilo and Alan S. Willsky: Diagonal and low-rank matrix decompositions, correlation matrices, and ellipsoid fitting
In: SIAM journal on matrix analysis and applications, 33 (2012) 4, p. 1395-1416
Bibtex DOI: 10.1137/120872516 ARXIV: https://arxiv.org/abs/1204.1220
Repository Open Access

James Francis Saunderson ; Venkat Chandrasekaran ; Pablo A. Parrilo and Alan S. Willsky: Tree-structured statistical modeling via convex optimization
In: 50th IEEE annual conference on decision and control (CDC), 2011
Piscataway, NY : IEEE, 2012. - P. 2883-2888
Bibtex DOI: 10.1109/CDC.2011.6161011

Parikshit Shah and Venkat Chandrasekaran: Group symmetry and covariance regularization
In: Electronic journal of statistics, 6 (2012), p. 1600-1640
Bibtex DOI: 10.1214/12-EJS723 ARXIV: https://arxiv.org/abs/1111.7061
Journal Open Access

Parikshit Shah and Venkat Chandrasekaran: Group symmetry and covariance regularization
In: 46th annual conference on information sciences and systems (CISS) : 21-23 March 2012, Princeton University, Princeton, NJ, USA
Piscataway, NJ : IEEE, 2012. - P. 1-6
Bibtex DOI: 10.1109/CISS.2012.6310765 ARXIV: https://arxiv.org/abs/1111.7061
Journal Open Access

Venkat Chandrasekaran ; Misha Chertkov ; David Gamarnik ; Devavrat Shah and Jinwoo Shin: Counting independent sets using the Bethe approximation
In: SIAM journal on discrete mathematics, 25 (2011) 2, p. 1012-1034
Bibtex DOI: 10.1137/090767145 LINK: https://www.researchgate.net/publication/220533068
Repository Open Access

Venkat Chandrasekaran ; Sujay Sanghavi ; Pablo A. Parrilo and Alan S. Willsky: Rank-sparsity incoherence for matrix decomposition
In: SIAM journal on optimization, 21 (2011) 2, p. 572-596
Bibtex DOI: 10.1137/090761793 ARXIV: https://arxiv.org/abs/0906.2220
Repository Open Access

Parikshit Shah and Venkat Chandrasekaran: Iterative projections for signal identification on manifolds : Global recovery guarantees
In: 2011 49th Annual Allerton conference on communication, control, and computing : Monticello, Illinois, USA, 28-30 September 2011
Piscataway, N.J. : IEEE, 2011. - P. 760-767
Bibtex DOI: 10.1109/Allerton.2011.6120244

Myung Jin Choi ; Venkat Chandrasekaran and Alan S. Willsky: Gaussian multiresolution models: exploiting sparse Markov and covariance structure
In: IEEE transactions on signal processing, 58 (2010) 3, p. 1012-1024
Bibtex DOI: 10.1109/TSP.2009.2036042 LINK: https://resolver.caltech.edu/CaltechAUTHORS:20121008-094406124
Repository Open Access

Ying Liu ; Venkat Chandrasekaran ; Animashree Anandkumar and Alan S. Willsky: Feedback message passing for inference in Gaussian graphical models
In: IEEE international symposium on information theory proceedings (ISIT) : 2010 Austin, Texas, USA, 13-18 June 2010
Piscataway, NY : IEEE, 2010. - P. 1683-1687
Bibtex DOI: 10.1109/ISIT.2010.5513321 ARXIV: https://arxiv.org/abs/1105.1853
Repository Open Access

Venkat Chandrasekaran ; Michael B. Wakin ; Dror Baron and Richard G. Baraniuk: Representation and compression of multidimensional piecewise functions using surflets
In: IEEE transactions on information theory, 55 (2009) 1, p. 374-400
Bibtex DOI: 10.1109/TIT.2008.2008153

Myung Jin Choi ; Venkat Chandrasekaran and Alan S. Willsky: Exploiting sparse Markov and covariance structure in multiresolution models
In: ICML 2009 : Proceedings of the 26th international conference on machine learning ; 14-18 June 2009
New York : Association for Computing Machinery, 2009. - P. 177-184
Bibtex DOI: 10.1145/1553374.1553397

Venkat Chandrasekaran ; Jason K. Johnson and Alan S. Willsky: Estimation in Gaussian graphical models using tractable subgraphs : a walk-sum analysis
In: IEEE transactions on signal processing, 56 (2008) 5, p. 1916-1930
Bibtex DOI: 10.1109/TSP.2007.912280 LINK: https://resolver.caltech.edu/CaltechAUTHORS:20121005-083046659
Repository Open Access

Venkat Chandrasekaran ; Jason K. Johnson and Alan S. Willsky: Adaptive embedded subgraph algorithms using walk-sum analysis
In: Advances in neural information processing systems 20 : NIPS 2007 ; 21st annual conference on neural information processing systems 2007, Vancouver, British Columbia, Canada, December 3-6, 2007
La Jolla, CA : Neural Information Processing Systems, 2008. - P. 249-256
Bibtex LINK: https://openreview.net/forum?id=rJVSoObuWS
Repository Open Access

Venkat Chandrasekaran ; Nathan Srebro and Prahladh Harsha: Complexity of inference in graphical models
In: UAI 2008 : proceedings of the 24th conference in uncertainty in artificial intelligence, Helsinki, Finland, July 9-12, 2008 / David McAllester (ed.)
Corvallis, Or. : AUAI Press, 2008. - P. 70-78
Bibtex ARXIV: https://arxiv.org/abs/1206.3240
Repository Open Access

Myung Jin Choi ; Venkat Chandrasekaran ; Dimitry M. Malioutov ; Jason K. Johnson and Alan S. Willsky: Multiscale stochastic modeling for tractable inference and data assimilation
In: Computer methods in applied mechanics and engineering, 197 (2008) 43-44, p. 3492-3515
Bibtex DOI: 10.1016/j.cma.2007.12.021

Myung Jin Choi ; Venkat Chandrasekaran and Alan S. Willsky: Maximum entropy relaxation for multiscale graphical model selection
In: 2008 IEEE international conference on acoustics, speech, and signal processing (ICASSP) : March 30 - April 4, 2008
Piscataway, NY : IEEE, 2008. - P. 1889-1892
Bibtex DOI: 10.1109/ICASSP.2008.4518003

Jason K. Johnson ; Venkat Chandrasekaran and Alan S. Willsky: Learning Markov structure by maximum entropy relaxation
In: Proceedings of the eleventh international conference on artificial intelligence and statistics : 21-24 March 2007, San Juan, Puerto Rico
Long Beach, California : PMLR, 2007. - P. 203-210
(Proceedings of machine learning research ; 2)
Bibtex LINK: http://proceedings.mlr.press/v2/johnson07a.html

Venkat Chandrasekaran ; Michael B. Wakin ; Dror Baron and Richard G. Baraniuk: Surflets : a sparse representation for multidimensional functions containing smooth discontinuities
In: IEEE international symposium on information theory proceedings (ISIT) : 2004 Chicago, Illinois, USA, June 27-July 2, 2004
Piscataway, NY : IEEE, 2004. - P. 563-563
Bibtex DOI: 10.1109/ISIT.2004.1365602 LINK: https://resolver.caltech.edu/CaltechAUTHORS:20121011-131626671
Repository Open Access

Thesis

Venkat Chandrasekaran: Convex optimization methods for graphs and statistical Modeling
Dissertation, Massachusetts Institute of Technology, 2011
Bibtex LINK: https://resolver.caltech.edu/CaltechAUTHORS:20121008-130644748
Repository Open Access
02.07.2022, 05:50