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ORCIDSantosh S. Vempala
Santosh Srinivas Vempala
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- affiliation: Georgia Institute of Technology, School of Computer Science, Atlanta, GA, USA
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2020 – today
- 2024
[j68]Richard Peng, Santosh S. Vempala:
Solving Sparse Linear Systems Faster than Matrix Multiplication. Commun. ACM 67(7): 79-86 (2024)- [c151]Max Dabagia, Christos H. Papadimitriou, Santosh S. Vempala:
Computation with Sequences of Assemblies in a Model of the Brain. ALT 2024: 499-504 - [c150]Khashayar Gatmiry, Jonathan A. Kelner, Santosh S. Vempala:
Sampling Polytopes with Riemannian HMC: Faster Mixing via the Lewis Weights Barrier. COLT 2024: 1796-1881 - [c149]Yunbum Kook, Santosh S. Vempala:
Gaussian Cooling and Dikin Walks: The Interior-Point Method for Logconcave Sampling. COLT 2024: 3137-3240 - [c148]Adam Tauman Kalai
, Santosh S. Vempala:
Calibrated Language Models Must Hallucinate. STOC 2024: 160-171 - [i92]Yunbum Kook, Santosh S. Vempala, Matthew Shunshi Zhang:
In-and-Out: Algorithmic Diffusion for Sampling Convex Bodies. CoRR abs/2405.01425 (2024) - [i91]Max Dabagia, Daniel Mitropolsky, Christos H. Papadimitriou, Santosh S. Vempala:
Coin-Flipping In The Brain: Statistical Learning with Neuronal Assemblies. CoRR abs/2406.07715 (2024) - [i90]Mirabel Reid, Santosh S. Vempala:
Does GPT Really Get It? A Hierarchical Scale to Quantify Human vs AI's Understanding of Algorithms. CoRR abs/2406.14722 (2024) - [i89]Yunbum Kook, Santosh S. Vempala:
Sampling and Integration of Logconcave Functions by Algorithmic Diffusion. CoRR abs/2411.13462 (2024) - 2023
- [j67]Aditi Laddha, Santosh S. Vempala:
Convergence of Gibbs Sampling: Coordinate Hit-and-Run Mixes Fast. Discret. Comput. Geom. 70(2): 406-425 (2023) - [c147]Mirabel E. Reid, Santosh S. Vempala:
The k-Cap Process on Geometric Random Graphs. COLT 2023: 3469-3509 - [c146]Yunbum Kook, Yin Tat Lee, Ruoqi Shen, Santosh S. Vempala:
Condition-number-independent Convergence Rate of Riemannian Hamiltonian Monte Carlo with Numerical Integrators. COLT 2023: 4504-4569 - [c145]Pravesh Kothari, Santosh S. Vempala, Alexander S. Wein, Jeff Xu:
Is Planted Coloring Easier than Planted Clique? COLT 2023: 5343-5372 - [c144]Mehrdad Ghadiri, Richard Peng, Santosh S. Vempala:
The Bit Complexity of Efficient Continuous Optimization. FOCS 2023: 2059-2070 - [c143]He Jia, Pravesh K. Kothari, Santosh S. Vempala:
Beyond Moments: Robustly Learning Affine Transformations with Asymptotically Optimal Error. FOCS 2023: 2408-2429 - [c142]Xinyuan Cao, Santosh S. Vempala:
Contrastive Moments: Unsupervised Halfspace Learning in Polynomial Time. NeurIPS 2023 - [i88]He Jia, Pravesh Kothari, Santosh S. Vempala:
Beyond Moments: Robustly Learning Affine Transformations with Asymptotically Optimal Error. CoRR abs/2302.12289 (2023) - [i87]Pravesh K. Kothari, Santosh S. Vempala, Alexander S. Wein, Jeff Xu:
Is Planted Coloring Easier than Planted Clique? CoRR abs/2303.00252 (2023) - [i86]Khashayar Gatmiry, Jonathan A. Kelner, Santosh S. Vempala:
Sampling with Barriers: Faster Mixing via Lewis Weights. CoRR abs/2303.00480 (2023) - [i85]Mehrdad Ghadiri, Richard Peng, Santosh S. Vempala:
The Bit Complexity of Efficient Continuous Optimization. CoRR abs/2304.02124 (2023) - [i84]Max Dabagia, Christos H. Papadimitriou, Santosh S. Vempala:
Computation with Sequences in the Brain. CoRR abs/2306.03812 (2023) - [i83]Yunbum Kook, Santosh S. Vempala:
Efficiently Sampling the PSD Cone with the Metric Dikin Walk. CoRR abs/2307.12943 (2023) - [i82]Xinyuan Cao, Santosh S. Vempala:
Contrastive Moments: Unsupervised Halfspace Learning in Polynomial Time. CoRR abs/2311.01435 (2023) - [i81]Adam Tauman Kalai, Santosh S. Vempala:
Calibrated Language Models Must Hallucinate. CoRR abs/2311.14648 (2023) - 2022
- [j66]Aditi Laddha, Mohit Singh, Santosh S. Vempala:
Socially fair network design via iterative rounding. Oper. Res. Lett. 50(5): 536-540 (2022) - [j65]Greg Bodwin, Santosh S. Vempala:
A unified view of graph regularity via matrix decompositions. Random Struct. Algorithms 61(1): 62-83 (2022) - [j64]Samantha Petti, Santosh S. Vempala:
Approximating sparse graphs: The random overlapping communities model. Random Struct. Algorithms 61(4): 844-908 (2022) - [j63]Yin Tat Lee, Santosh S. Vempala:
Geodesic Walks in Polytopes. SIAM J. Comput. 51(2): 17-400 (2022) - [j62]Zongchen Chen, Santosh S. Vempala:
Optimal Convergence Rate of Hamiltonian Monte Carlo for Strongly Logconcave Distributions. Adv. Math. Commun. 18: 1-18 (2022) - [c141]Shivam Garg, Santosh S. Vempala:
How and When Random Feedback Works: A Case Study of Low-Rank Matrix Factorization. AISTATS 2022: 4070-4108 - [c140]Xinyuan Cao, Weiyang Liu, Santosh S. Vempala:
Provable Lifelong Learning of Representations. AISTATS 2022: 6334-6356 - [c139]Ruilin Li, Molei Tao, Santosh S. Vempala, Andre Wibisono:
The Mirror Langevin Algorithm Converges with Vanishing Bias. ALT 2022: 718-742 - [c138]Nikhil Bansal, Aditi Laddha, Santosh S. Vempala:
A Unified Approach to Discrepancy Minimization. APPROX/RANDOM 2022: 1:1-1:22 - [c137]Max Dabagia, Santosh S. Vempala, Christos H. Papadimitriou:
Assemblies of neurons learn to classify well-separated distributions. COLT 2022: 3685-3717 - [c136]Yin Tat Lee, Santosh S. Vempala:
The Manifold Joys of Sampling (Invited Talk). ICALP 2022: 4:1-4:20 - [c135]Yunbum Kook, Yin Tat Lee, Ruoqi Shen, Santosh S. Vempala:
Sampling with Riemannian Hamiltonian Monte Carlo in a Constrained Space. NeurIPS 2022 - [c134]Ainesh Bakshi, Ilias Diakonikolas, He Jia, Daniel M. Kane, Pravesh K. Kothari, Santosh S. Vempala:
Robustly learning mixtures of k arbitrary Gaussians. STOC 2022: 1234-1247 - [i80]Yunbum Kook, Yin Tat Lee, Ruoqi Shen, Santosh S. Vempala:
Sampling with Riemannian Hamiltonian Monte Carlo in a Constrained Space. CoRR abs/2202.01908 (2022) - [i79]Mirabel Reid, Santosh S. Vempala:
The k-Cap Process on Geometric Random Graphs. CoRR abs/2203.12680 (2022) - [i78]Khashayar Gatmiry, Santosh S. Vempala:
Convergence of the Riemannian Langevin Algorithm. CoRR abs/2204.10818 (2022) - [i77]Nikhil Bansal, Aditi Laddha, Santosh S. Vempala:
A Unified Approach to Discrepancy Minimization. CoRR abs/2205.01023 (2022) - [i76]Mehrdad Ghadiri, Mohit Singh, Santosh S. Vempala:
Constant-Factor Approximation Algorithms for Socially Fair k-Clustering. CoRR abs/2206.11210 (2022) - [i75]Arun Jambulapati, Yin Tat Lee, Santosh S. Vempala:
A Slightly Improved Bound for the KLS Constant. CoRR abs/2208.11644 (2022) - [i74]Yunbum Kook, Yin Tat Lee, Ruoqi Shen, Santosh S. Vempala:
Condition-number-independent Convergence Rate of Riemannian Hamiltonian Monte Carlo with Numerical Integrators. CoRR abs/2210.07219 (2022) - 2021
- [j61]Vitaly Feldman, Cristóbal Guzmán, Santosh Srinivas Vempala:
Statistical Query Algorithms for Mean Vector Estimation and Stochastic Convex Optimization. Math. Oper. Res. 46(3): 912-945 (2021) - [c133]Aditi Laddha, Santosh S. Vempala:
Convergence of Gibbs Sampling: Coordinate Hit-And-Run Mixes Fast. SoCG 2021: 51:1-51:12 - [c132]Mehrdad Ghadiri, Samira Samadi, Santosh S. Vempala:
Socially Fair k-Means Clustering. FAccT 2021: 438-448 - [c131]Richard Peng, Santosh S. Vempala:
Solving Sparse Linear Systems Faster than Matrix Multiplication. SODA 2021: 504-521 - [c130]He Jia, Aditi Laddha, Yin Tat Lee, Santosh S. Vempala:
Reducing isotropy and volume to KLS: an o*(n3ψ2) volume algorithm. STOC 2021: 961-974 - [i73]Yin Tat Lee, Santosh S. Vempala:
Tutorial on the Robust Interior Point Method. CoRR abs/2108.04734 (2021) - [i72]Mehrdad Ghadiri, Richard Peng, Santosh S. Vempala:
Sparse Regression Faster than dω. CoRR abs/2109.11537 (2021) - [i71]Ruilin Li, Molei Tao, Santosh S. Vempala, Andre Wibisono:
The Mirror Langevin Algorithm Converges with Vanishing Bias. CoRR abs/2109.12077 (2021) - [i70]Max Dabagia, Christos H. Papadimitriou, Santosh S. Vempala:
Assemblies of neurons can learn to classify well-separated distributions. CoRR abs/2110.03171 (2021) - [i69]Xinyuan Cao, Weiyang Liu, Santosh S. Vempala:
Provable Lifelong Learning of Representations. CoRR abs/2110.14098 (2021) - [i68]Shivam Garg, Santosh S. Vempala:
How and When Random Feedback Works: A Case Study of Low-Rank Matrix Factorization. CoRR abs/2111.08706 (2021) - 2020
- [j60]Manuel Blum, Santosh S. Vempala:
The complexity of human computation via a concrete model with an application to passwords. Proc. Natl. Acad. Sci. USA 117(17): 9208-9215 (2020) - [c129]Santosh S. Vempala, Ruosong Wang, David P. Woodruff:
The Communication Complexity of Optimization. SODA 2020: 1733-1752 - [c128]Aditi Laddha, Yin Tat Lee, Santosh S. Vempala:
Strong self-concordance and sampling. STOC 2020: 1212-1222 - [i67]Mehrdad Ghadiri, Samira Samadi, Santosh S. Vempala:
Fair k-Means Clustering. CoRR abs/2006.10085 (2020) - [i66]Richard Peng, Santosh S. Vempala:
Solving Sparse Linear Systems Faster than Matrix Multiplication. CoRR abs/2007.10254 (2020) - [i65]He Jia, Aditi Laddha, Yin Tat Lee, Santosh S. Vempala:
Reducing Isotropy and Volume to KLS: An O(n3ψ2) Volume Algorithm. CoRR abs/2008.02146 (2020) - [i64]Aditi Laddha, Santosh S. Vempala:
Convergence of Gibbs Sampling: Coordinate Hit-and-Run Mixes Fast. CoRR abs/2009.11338 (2020) - [i63]Ainesh Bakshi, Ilias Diakonikolas, He Jia, Daniel M. Kane, Pravesh K. Kothari, Santosh S. Vempala:
Robustly Learning Mixtures of k Arbitrary Gaussians. CoRR abs/2012.02119 (2020)
2010 – 2019
- 2019
- [j59]Christoph Hunkenschröder, Santosh S. Vempala, Adrian Vetta:
A 4/3-Approximation Algorithm for the Minimum 2-Edge Connected Subgraph Problem. ACM Trans. Algorithms 15(4): 55:1-55:28 (2019) - [c127]Zongchen Chen, Santosh S. Vempala:
Optimal Convergence Rate of Hamiltonian Monte Carlo for Strongly Logconcave Distributions. APPROX-RANDOM 2019: 64:1-64:12 - [c126]Santosh S. Vempala, John Wilmes:
Gradient Descent for One-Hidden-Layer Neural Networks: Polynomial Convergence and SQ Lower Bounds. COLT 2019: 3115-3117 - [c125]Christos H. Papadimitriou, Santosh S. Vempala:
Random Projection in the Brain and Computation with Assemblies of Neurons. ITCS 2019: 57:1-57:19 - [c124]Jung Wook Park, Aditi Shah, Rosa I. Arriaga, Santosh S. Vempala:
Redesigning a Basic Laboratory Information System for the Global South. ITU Kaleidoscope 2019: 1-8 - [c123]Santosh S. Vempala, Andre Wibisono:
Rapid Convergence of the Unadjusted Langevin Algorithm: Isoperimetry Suffices. NeurIPS 2019: 8092-8104 - [c122]Uthaipon Tantipongpipat, Samira Samadi, Mohit Singh, Jamie Morgenstern, Santosh S. Vempala:
Multi-Criteria Dimensionality Reduction with Applications to Fairness. NeurIPS 2019: 15135-15145 - [p1]Wolfgang Maass, Christos H. Papadimitriou, Santosh S. Vempala, Robert Legenstein:
Brain Computation: A Computer Science Perspective. Computing and Software Science 2019: 184-199 - [i62]Jamie Morgenstern, Samira Samadi, Mohit Singh, Uthaipon Tao Tantipongpipat, Santosh S. Vempala:
Fair Dimensionality Reduction and Iterative Rounding for SDPs. CoRR abs/1902.11281 (2019) - [i61]Santosh S. Vempala, Andre Wibisono:
Rapid Convergence of the Unadjusted Langevin Algorithm: Log-Sobolev Suffices. CoRR abs/1903.08568 (2019) - [i60]Zongchen Chen, Santosh S. Vempala:
Optimal Convergence Rate of Hamiltonian Monte Carlo for Strongly Logconcave Distributions. CoRR abs/1905.02313 (2019) - [i59]Elan Rosenfeld, Santosh S. Vempala, Manuel Blum:
Human-Usable Password Schemas: Beyond Information-Theoretic Security. CoRR abs/1906.00029 (2019) - [i58]Santosh S. Vempala, Ruosong Wang, David P. Woodruff:
The Communication Complexity of Optimization. CoRR abs/1906.05832 (2019) - [i57]Aditi Laddha, Yin Tat Lee, Santosh S. Vempala:
Strong Self-Concordance and Sampling. CoRR abs/1911.05656 (2019) - [i56]Greg Bodwin, Santosh S. Vempala:
Matrix Decompositions and Sparse Graph Regularity. CoRR abs/1911.11868 (2019) - 2018
- [j58]Ben Cousins, Santosh S. Vempala:
Gaussian Cooling and O*(n3) Algorithms for Volume and Gaussian Volume. SIAM J. Comput. 47(3): 1237-1273 (2018) - [j57]Vitaly Feldman, Will Perkins, Santosh S. Vempala:
On the Complexity of Random Satisfiability Problems with Planted Solutions. SIAM J. Comput. 47(4): 1294-1338 (2018) - [j56]Cristopher Moore, Santosh S. Vempala:
Special Section on the Fifty-Sixth Annual IEEE Symposium on Foundations of Computer Science (FOCS 2015). SIAM J. Comput. 47(6): 2237 (2018) - [c121]Yin Tat Lee, Aaron Sidford, Santosh S. Vempala:
Efficient Convex Optimization with Membership Oracles. COLT 2018: 1292-1294 - [c120]Santosh S. Vempala:
Continuous Algorithms (Invited Paper). FSTTCS 2018: 4:1-4:1 - [c119]Samira Samadi, Santosh S. Vempala, Adam Tauman Kalai:
Usability of Humanly Computable Passwords. HCOMP 2018: 174-183 - [c118]Robert Legenstein, Wolfgang Maass, Christos H. Papadimitriou, Santosh S. Vempala:
Long Term Memory and the Densest K-Subgraph Problem. ITCS 2018: 57:1-57:15 - [c117]Nima Anari, Constantinos Daskalakis, Wolfgang Maass, Christos H. Papadimitriou, Amin Saberi, Santosh S. Vempala:
Smoothed Analysis of Discrete Tensor Decomposition and Assemblies of Neurons. NeurIPS 2018: 10880-10890 - [c116]Samira Samadi, Uthaipon Tao Tantipongpipat, Jamie Morgenstern, Mohit Singh, Santosh S. Vempala:
The Price of Fair PCA: One Extra dimension. NeurIPS 2018: 10999-11010 - [c115]Yin Tat Lee, Santosh S. Vempala:
Convergence rate of riemannian Hamiltonian Monte Carlo and faster polytope volume computation. STOC 2018: 1115-1121 - [c114]Yin Tat Lee, Santosh S. Vempala:
Stochastic localization + Stieltjes barrier = tight bound for log-Sobolev. STOC 2018: 1122-1129 - [i55]Samantha Petti, Santosh S. Vempala:
Approximating Sparse Graphs: The Random Overlapping Communities Model. CoRR abs/1802.03652 (2018) - [i54]Santosh S. Vempala, John Wilmes:
Polynomial Convergence of Gradient Descent for Training One-Hidden-Layer Neural Networks. CoRR abs/1805.02677 (2018) - [i53]Yin Tat Lee, Santosh S. Vempala:
The Kannan-Lovász-Simonovits Conjecture. CoRR abs/1807.03465 (2018) - [i52]Nima Anari, Constantinos Daskalakis, Wolfgang Maass, Christos H. Papadimitriou, Amin Saberi, Santosh S. Vempala:
Smoothed Analysis of Discrete Tensor Decomposition and Assemblies of Neurons. CoRR abs/1810.11896 (2018) - [i51]Samira Samadi, Uthaipon Tao Tantipongpipat, Jamie Morgenstern, Mohit Singh, Santosh S. Vempala:
The Price of Fair PCA: One Extra Dimension. CoRR abs/1811.00103 (2018) - [i50]Yin Tat Lee, Zhao Song, Santosh S. Vempala:
Algorithmic Theory of ODEs and Sampling from Well-conditioned Logconcave Densities. CoRR abs/1812.06243 (2018) - 2017
- [j55]Ravindran Kannan, Santosh S. Vempala:
Randomized algorithms in numerical linear algebra. Acta Numer. 26: 95-135 (2017) - [j54]Hulda S. Haraldsdóttir, Ben Cousins, Ines Thiele, Ronan M. T. Fleming, Santosh S. Vempala:
CHRR: coordinate hit-and-run with rounding for uniform sampling of constraint-based models. Bioinform. 33(11): 1741-1743 (2017) - [j53]Vitaly Feldman, Elena Grigorescu, Lev Reyzin, Santosh S. Vempala, Ying Xiao:
Statistical Algorithms and a Lower Bound for Detecting Planted Cliques. J. ACM 64(2): 8:1-8:37 (2017) - [j52]Friedrich Eisenbrand, Santosh S. Vempala:
Geometric random edge. Math. Program. 164(1-2): 325-339 (2017) - [c113]Ravindran Kannan, Santosh S. Vempala:
The Hidden Hubs Problem. COLT 2017: 1190-1213 - [c112]Yin Tat Lee, Santosh Srinivas Vempala:
Eldan's Stochastic Localization and the KLS Hyperplane Conjecture: An Improved Lower Bound for Expansion. FOCS 2017: 998-1007 - [c111]Jeremiah Blocki, Manuel Blum, Anupam Datta, Santosh S. Vempala:
Towards Human Computable Passwords. ITCS 2017: 10:1-10:47 - [c110]Le Song, Santosh S. Vempala, John Wilmes, Bo Xie:
On the Complexity of Learning Neural Networks. NIPS 2017: 5514-5522 - [c109]Vitaly Feldman, Cristóbal Guzmán, Santosh S. Vempala:
Statistical Query Algorithms for Mean Vector Estimation and Stochastic Convex Optimization. SODA 2017: 1265-1277 - [c108]Santosh S. Vempala, David P. Woodruff:
Adaptive Matrix Vector Product. SODA 2017: 2044-2060 - [c107]Yin Tat Lee, Santosh S. Vempala:
Geodesic walks in polytopes. STOC 2017: 927-940 - [e1]Klaus Jansen, José D. P. Rolim, David Williamson, Santosh S. Vempala:
Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, APPROX/RANDOM 2017, August 16-18, 2017, Berkeley, CA, USA. LIPIcs 81, Schloss Dagstuhl - Leibniz-Zentrum für Informatik 2017, ISBN 978-3-95977-044-6 [contents] - [i49]Yin Tat Lee, Aaron Sidford, Santosh S. Vempala:
Efficient Convex Optimization with Membership Oracles. CoRR abs/1706.07357 (2017) - [i48]Manuel Blum, Santosh S. Vempala:
The Complexity of Human Computation: A Concrete Model with an Application to Passwords. CoRR abs/1707.01204 (2017) - [i47]Le Song, Santosh S. Vempala, John Wilmes, Bo Xie:
On the Complexity of Learning Neural Networks. CoRR abs/1707.04615 (2017) - [i46]Samantha Petti, Santosh S. Vempala:
Random Overlapping Communities: Approximating Motif Densities of Large Graphs. CoRR abs/1709.09477 (2017) - [i45]Yin Tat Lee, Santosh Srinivas Vempala:
Convergence Rate of Riemannian Hamiltonian Monte Carlo and Faster Polytope Volume Computation. CoRR abs/1710.06261 (2017) - [i44]Samira Samadi, Santosh S. Vempala, Adam Tauman Kalai:
Usability of Humanly Computable Passwords. CoRR abs/1712.03650 (2017) - 2016
- [j51]Karthekeyan Chandrasekaran, László A. Végh, Santosh S. Vempala:
The Cutting Plane Method is Polynomial for Perfect Matchings. Math. Oper. Res. 41(1): 23-48 (2016) - [j50]Ben Cousins, Santosh S. Vempala:
A practical volume algorithm. Math. Program. Comput. 8(2): 133-160 (2016) - [j49]Stephan Artmann, Friedrich Eisenbrand, Christoph Glanzer, Timm Oertel, Santosh S. Vempala, Robert Weismantel:
A note on non-degenerate integer programs with small sub-determinants. Oper. Res. Lett. 44(5): 635-639 (2016) - [c106]Christos H. Papadimitriou, Samantha Petti, Santosh S. Vempala:
Cortical Computation via Iterative Constructions. COLT 2016: 1357-1375 - [c105]Kevin A. Lai, Anup B. Rao, Santosh S. Vempala:
Agnostic Estimation of Mean and Covariance. FOCS 2016: 665-674 - [c104]Anand Louis, Santosh S. Vempala:
Accelerated Newton Iteration for Roots of Black Box Polynomials. FOCS 2016: 732-740 - [c103]Santosh S. Vempala, Naomi Chopra, Aishwarya Rajagopal, John Nkengasong, Sidney Akuro:
C4G BLIS: Health Care Delivery via Iterative Collaborative Design in Resource-constrained Settings. ICTD 2016: 21 - [c102]Robert Legenstein, Christos H. Papadimitriou, Santosh S. Vempala, Wolfgang Maass:
Variable Binding through Assemblies in Spiking Neural Networks. CoCo@NIPS 2016 - [i43]Christos H. Papadimitriou, Samantha Petti, Santosh S. Vempala:
Cortical Computation via Iterative Constructions. CoRR abs/1602.08357 (2016) - [i42]Kevin A. Lai, Anup B. Rao, Santosh S. Vempala:
Agnostic Estimation of Mean and Covariance. CoRR abs/1604.06968 (2016) - [i41]Yin Tat Lee, Santosh S. Vempala:
Geodesic Walks on Polytopes. CoRR abs/1606.04696 (2016) - [i40]Ravi Kannan, Santosh S. Vempala:
Beyond Spectral: Tight Bounds for Planted Gaussians. CoRR abs/1608.03643 (2016) - [i39]Yin Tat Lee, Santosh S. Vempala:
Eldan's Stochastic Localization and the KLS Hyperplane Conjecture: An Improved Lower Bound for Expansion. CoRR abs/1612.01507 (2016) - 2015
- [j48]Navin Goyal, Luis Rademacher, Santosh S. Vempala:
Query Complexity of Sampling and Small Geometric Partitions. Comb. Probab. Comput. 24(5): 733-753 (2015) - [j47]A. B. Dieker, Santosh S. Vempala:
Stochastic Billiards for Sampling from the Boundary of a Convex Set. Math. Oper. Res. 40(4): 888-901 (2015) - [j46]Rosa I. Arriaga, David Rutter, Maya Cakmak, Santosh S. Vempala:
Visual Categorization with Random Projection. Neural Comput. 27(10): 2132-2147 (2015) - [c101]Maria-Florina Balcan, Avrim Blum, Santosh S. Vempala:
Efficient Representations for Lifelong Learning and Autoencoding. COLT 2015: 191-210 - [c100]Christos H. Papadimitriou, Santosh S. Vempala:
Cortical Learning via Prediction. COLT 2015: 1402-1422 - [c99]Santosh S. Vempala, Ying Xiao:
Max vs Min: Tensor Decomposition and ICA with nearly Linear Sample Complexity. COLT 2015: 1710-1723 - [c98]Manuel Blum, Santosh Srinivas Vempala:
Publishable Humanly Usable Secure Password Creation Schemas. HCOMP 2015: 32-41 - [c97]Vitaly Feldman, Will Perkins, Santosh S. Vempala:
Subsampled Power Iteration: a Unified Algorithm for Block Models and Planted CSP's. NIPS 2015: 2836-2844 - [c96]Christos H. Papadimitriou, Santosh S. Vempala:
Cortical Computation. PODC 2015: 1-2 - [c95]Vitaly Feldman, Will Perkins, Santosh S. Vempala:
On the Complexity of Random Satisfiability Problems with Planted Solutions. STOC 2015: 77-86 - [c94]Benjamin Cousins, Santosh S. Vempala:
Bypassing KLS: Gaussian Cooling and an O^*(n3) Volume Algorithm. STOC 2015: 539-548 - [i38]Anand Louis, Santosh S. Vempala:
Accelerated Newton Iteration: Roots of Black Box Polynomials and Matrix Eigenvalues. CoRR abs/1511.03186 (2015) - [i37]Vitaly Feldman, Cristóbal Guzmán, Santosh S. Vempala:
Statistical Query Algorithms for Stochastic Convex Optimization. CoRR abs/1512.09170 (2015) - 2014
- [j45]Alan M. Frieze, Navin Goyal, Luis Rademacher, Santosh S. Vempala:
Expanders via Random Spanning Trees. SIAM J. Comput. 43(2): 497-513 (2014) - [c93]Ravi Kannan, Santosh S. Vempala, David P. Woodruff:
Principal Component Analysis and Higher Correlations for Distributed Data. COLT 2014: 1040-1057 - [c92]Karthekeyan Chandrasekaran, Santosh S. Vempala:
Integer feasibility of random polytopes: random integer programs. ITCS 2014: 449-458 - [c91]Ben Cousins, Santosh S. Vempala:
A Cubic Algorithm for Computing Gaussian Volume. SODA 2014: 1215-1228 - [c90]Navin Goyal, Santosh S. Vempala, Ying Xiao:
Fourier PCA and robust tensor decomposition. STOC 2014: 584-593 - [i36]Friedrich Eisenbrand, Santosh S. Vempala:
Geometric Random Edge. CoRR abs/1404.1568 (2014) - [i35]Vitaly Feldman, Will Perkins, Santosh S. Vempala:
Subsampled Power Iteration: a New Algorithm for Block Models and Planted CSP's. CoRR abs/1407.2774 (2014) - [i34]Ben Cousins, Santosh S. Vempala:
Bypassing KLS: Gaussian Cooling and an O*(n^3) Volume Algorithm. CoRR abs/1409.6011 (2014) - [i33]A. B. Dieker, Santosh S. Vempala:
Stochastic billiards for sampling from the boundary of a convex set. CoRR abs/1410.5775 (2014) - [i32]Maria-Florina Balcan, Avrim Blum, Santosh S. Vempala:
Efficient Representations for Life-Long Learning and Autoencoding. CoRR abs/1411.1490 (2014) - [i31]Navin Goyal, Luis Rademacher, Santosh S. Vempala:
Query complexity of sampling and small geometric partitions. CoRR abs/1411.3799 (2014) - [i30]Santosh S. Vempala, Ying Xiao:
Max vs Min: Independent Component Analysis with nearly Linear Sample Complexity. CoRR abs/1412.2954 (2014) - [i29]Christos H. Papadimitriou, Santosh S. Vempala:
Unsupervised Learning through Prediction in a Model of Cortex. CoRR abs/1412.7955 (2014) - [i28]Vitaly Feldman, Will Perkins, Santosh S. Vempala:
On the Complexity of Random Satisfiability Problems with Planted Solutions. Electron. Colloquium Comput. Complex. TR14 (2014) - 2013
- [j44]Daniel Dadush, Santosh S. Vempala:
Near-optimal deterministic algorithms for volume computation via M-ellipsoids. Proc. Natl. Acad. Sci. USA 110(48): 19237-19245 (2013) - [c89]Santosh S. Vempala, Ying Xiao:
Complexity of learning subspace juntas and ICA. ACSSC 2013: 320-324 - [c88]Anand Louis, Prasad Raghavendra, Santosh S. Vempala:
The Complexity of Approximating Vertex Expansion. FOCS 2013: 360-369 - [c87]Vitaly Feldman, Elena Grigorescu, Lev Reyzin, Santosh S. Vempala, Ying Xiao:
Statistical algorithms and a lower bound for detecting planted cliques. STOC 2013: 655-664 - [c86]Noga Alon, Troy Lee, Adi Shraibman, Santosh S. Vempala:
The approximate rank of a matrix and its algorithmic applications: approximate rank. STOC 2013: 675-684 - [i27]Anand Louis, Prasad Raghavendra, Santosh S. Vempala:
The Complexity of Approximating Vertex Expansion. CoRR abs/1304.3139 (2013) - [i26]Ravindran Kannan, Santosh S. Vempala:
Nimble Algorithms for Cloud Computing. CoRR abs/1304.3162 (2013) - [i25]Navin Goyal, Santosh S. Vempala, Ying Xiao:
Fourier PCA. CoRR abs/1306.5825 (2013) - [i24]Ben Cousins, Santosh S. Vempala:
A Cubic Algorithm for Computing Gaussian Volume. CoRR abs/1306.5829 (2013) - [i23]Vitaly Feldman, Will Perkins, Santosh S. Vempala:
On the Complexity of Random Satisfiability Problems with Planted Solutions. CoRR abs/1311.4821 (2013) - 2012
- [j43]Santosh S. Vempala:
Modeling high-dimensional data: technical perspective. Commun. ACM 55(2): 112 (2012) - [j42]Sanjeev Arora, László Lovász, Ilan Newman, Yuval Rabani, Yuri Rabinovich, Santosh S. Vempala:
Local Versus Global Properties of Metric Spaces. SIAM J. Comput. 41(1): 250-271 (2012) - [j41]Daniel Stefankovic, Santosh S. Vempala, Eric Vigoda:
A Deterministic Polynomial-Time Approximation Scheme for Counting Knapsack Solutions. SIAM J. Comput. 41(2): 356-366 (2012) - [c85]Karthekeyan Chandrasekaran, László A. Végh, Santosh S. Vempala:
The Cutting Plane Method Is Polynomial for Perfect Matchings. FOCS 2012: 571-580 - [c84]Santosh S. Vempala:
Randomly-oriented k-d Trees Adapt to Intrinsic Dimension. FSTTCS 2012: 48-57 - [c83]Santosh S. Vempala:
Effective Principal Component Analysis. SISAP 2012: 1-7 - [c82]Daniel Dadush, Santosh S. Vempala:
Deterministic construction of an approximate M-ellipsoid and its applications to derandomizing lattice algorithms. SODA 2012: 1445-1456 - [c81]Anand Louis, Prasad Raghavendra, Prasad Tetali, Santosh S. Vempala:
Many sparse cuts via higher eigenvalues. STOC 2012: 1131-1140 - [i22]Vitaly Feldman, Elena Grigorescu, Lev Reyzin, Santosh S. Vempala:
The Complexity of Statistical Algorithms. CoRR abs/1201.1214 (2012) - [i21]Daniel Dadush, Santosh S. Vempala:
Deterministic 2^{O(n)} Algorithms for M-Ellipsoids, Lattice Problems and Volume Estimation. CoRR abs/1201.5972 (2012) - [i20]Karthekeyan Chandrasekaran, László A. Végh, Santosh S. Vempala:
The Cutting Plane Method is Polynomial for Perfect Matchings. CoRR abs/1207.5813 (2012) - [i19]Noga Alon, Santosh S. Vempala:
The Approximate Rank of a Matrix and its Algorithmic Applications. Electron. Colloquium Comput. Complex. TR12 (2012) - [i18]Vitaly Feldman, Elena Grigorescu, Lev Reyzin, Santosh S. Vempala, Ying Xiao:
Statistical Algorithms and a Lower Bound for Planted Clique. Electron. Colloquium Comput. Complex. TR12 (2012) - 2011
- [c80]Brendan Juba, Santosh S. Vempala:
Semantic Communication for Simple Goals Is Equivalent to On-line Learning. ALT 2011: 277-291 - [c79]Elena Grigorescu, Lev Reyzin, Santosh S. Vempala:
On Noise-Tolerant Learning of Sparse Parities and Related Problems. ALT 2011: 413-424 - [c78]Anand Louis, Prasad Raghavendra, Prasad Tetali, Santosh S. Vempala:
Algorithmic Extensions of Cheeger's Inequality to Higher Eigenvalues and Partitions. APPROX-RANDOM 2011: 315-326 - [c77]Daniel Dadush, Chris Peikert, Santosh S. Vempala:
Enumerative Lattice Algorithms in any Norm Via M-ellipsoid Coverings. FOCS 2011: 580-589 - [c76]Parikshit Gopalan, Adam R. Klivans, Raghu Meka, Daniel Stefankovic, Santosh S. Vempala, Eric Vigoda:
An FPTAS for #Knapsack and Related Counting Problems. FOCS 2011: 817-826 - [c75]Hrushikesh Mehendale, Ashwin Paranjpe, Santosh S. Vempala:
LifeNet: a flexible ad hoc networking solution for transient environments. SIGCOMM 2011: 446-447 - [c74]Karthekeyan Chandrasekaran, Richard M. Karp, Erick Moreno-Centeno, Santosh S. Vempala:
Algorithms for Implicit Hitting Set Problems. SODA 2011: 614-629 - [i17]Karthekeyan Chandrasekaran, Richard M. Karp, Erick Moreno-Centeno, Santosh S. Vempala:
Algorithms for Implicit Hitting Set Problems. CoRR abs/1102.1472 (2011) - [i16]Daniel Dadush, Santosh S. Vempala:
Deterministic Construction of an Approximate M-Ellipsoid and its Application to Derandomizing Lattice Algorithms. CoRR abs/1107.5478 (2011) - [i15]Santosh S. Vempala, Ying Xiao:
Structure from Local Optima: Learning Subspace Juntas via Higher Order PCA. CoRR abs/1108.3329 (2011) - [i14]Anand Louis, Prasad Raghavendra, Prasad Tetali, Santosh S. Vempala:
Many Sparse Cuts via Higher Eigenvalues. CoRR abs/1111.0965 (2011) - [i13]Karthekeyan Chandrasekaran, Santosh S. Vempala:
A Discrepancy based Approach to Integer Programming. CoRR abs/1111.4649 (2011) - 2010
- [j40]Alan M. Frieze, Santosh S. Vempala, Juan Vera:
Logconcave Random Graphs. Electron. J. Comb. 17(1) (2010) - [j39]Santosh S. Vempala:
A random-sampling-based algorithm for learning intersections of halfspaces. J. ACM 57(6): 32:1-32:14 (2010) - [c73]Santosh S. Vempala:
Corrigendum: A Random Sampling Algorithm for Learning an Intersection of Halfspaces. FOCS 2010: 123 - [c72]Santosh S. Vempala:
Learning Convex Concepts from Gaussian Distributions with PCA. FOCS 2010: 124-130 - [c71]Santosh S. Vempala:
Recent Progress and Open Problems in Algorithmic Convex Geometry. FSTTCS 2010: 42-64 - [c70]Mihály Bárász, Santosh S. Vempala:
A New Approach to Strongly Polynomial Linear Programming. ICS 2010: 42-48 - [c69]Pranjal Awasthi, Maria-Florina Balcan, Avrim Blum, Or Sheffet, Santosh S. Vempala:
On Nash-Equilibria of Approximation-Stable Games. SAGT 2010: 78-89 - [c68]Sam Burnett, Nick Feamster, Santosh S. Vempala:
Circumventing censorship with collage. SIGCOMM 2010: 471-472 - [c67]Karthekeyan Chandrasekaran, Daniel Dadush, Santosh S. Vempala:
Thin Partitions: Isoperimetric Inequalities and a Sampling Algorithm for Star Shaped Bodies. SODA 2010: 1630-1645 - [c66]Sam Burnett, Nick Feamster, Santosh S. Vempala:
Chipping Away at Censorship Firewalls with User-Generated Content. USENIX Security Symposium 2010: 463-468 - [i12]Daniel Stefankovic, Santosh S. Vempala, Eric Vigoda:
A Deterministic Polynomial-time Approximation Scheme for Counting Knapsack Solutions. CoRR abs/1008.1687 (2010) - [i11]Daniel Dadush, Chris Peikert, Santosh S. Vempala:
Enumerative Algorithms for the Shortest and Closest Lattice Vector Problems in Any Norm via M-Ellipsoid Coverings. CoRR abs/1011.5666 (2010)
2000 – 2009
- 2009
- [j38]Ravi Kannan, Santosh S. Vempala:
Spectral Algorithms. Found. Trends Theor. Comput. Sci. 4(3-4): 157-288 (2009) - [j37]Daniel Stefankovic, Santosh S. Vempala, Eric Vigoda:
Adaptive simulated annealing: A near-optimal connection between sampling and counting. J. ACM 56(3): 18:1-18:36 (2009) - [j36]Alexandre Belloni, Robert M. Freund, Santosh S. Vempala:
An Efficient Rescaled Perceptron Algorithm for Conic Systems. Math. Oper. Res. 34(3): 621-641 (2009) - [c65]S. Charles Brubaker, Santosh S. Vempala:
Random Tensors and Planted Cliques. APPROX-RANDOM 2009: 406-419 - [c64]Karthekeyan Chandrasekaran, Amit Deshpande, Santosh S. Vempala:
Sampling s-Concave Functions: The Limit of Convexity Based Isoperimetry. APPROX-RANDOM 2009: 420-433 - [c63]Stephen Thomas, Adebola Osuntogun, John Pitman, Bright Mulenga, Santosh S. Vempala:
Design and deployment of a blood safety monitoring tool. ICTD 2009: 280-287 - [c62]Adebola Osuntogun, Stephen Thomas, John Pitman, Sridhar Basavaraju, Bright Mulenga, Santosh S. Vempala:
Design of a blood flow system. ICTD 2009: 481 - [c61]Navin Goyal, Luis Rademacher, Santosh S. Vempala:
Expanders via random spanning trees. SODA 2009: 576-585 - [i10]Karthekeyan Chandrasekaran, Daniel Dadush, Santosh S. Vempala:
Thin Partitions: Isoperimetric Inequalities and Sampling Algorithms for some Nonconvex Families. CoRR abs/0904.0583 (2009) - [i9]S. Charles Brubaker, Santosh S. Vempala:
Random Tensors and Planted Cliques. CoRR abs/0905.2381 (2009) - [i8]Karthekeyan Chandrasekaran, Amit Deshpande, Santosh S. Vempala:
The Limit of Convexity Based Isoperimetry: Sampling Harmonic-Concave Functions. CoRR abs/0906.2448 (2009) - 2008
- [j35]Dimitris Bertsimas, Margrét V. Bjarnadóttir, Michael A. Kane, J. Christian Kryder, Rudra Pandey, Santosh S. Vempala, Grant Wang:
Algorithmic Prediction of Health-Care Costs. Oper. Res. 56(6): 1382-1392 (2008) - [j34]John Dunagan, Santosh S. Vempala:
A simple polynomial-time rescaling algorithm for solving linear programs. Math. Program. 114(1): 101-114 (2008) - [j33]Ravindran Kannan, Hadi Salmasian, Santosh S. Vempala:
The Spectral Method for General Mixture Models. SIAM J. Comput. 38(3): 1141-1156 (2008) - [c60]S. Charles Brubaker, Santosh S. Vempala:
Isotropic PCA and Affine-Invariant Clustering. FOCS 2008: 551-560 - [c59]Murtaza Motiwala, Megan Elmore, Nick Feamster, Santosh S. Vempala:
Path splicing. SIGCOMM 2008: 27-38 - [c58]Maria-Florina Balcan, Avrim Blum, Santosh S. Vempala:
A discriminative framework for clustering via similarity functions. STOC 2008: 671-680 - [c57]Alan M. Frieze, Santosh S. Vempala, Juan Vera:
Logconcave random graphs. STOC 2008: 779-788 - [i7]S. Charles Brubaker, Santosh S. Vempala:
Isotropic PCA and Affine-Invariant Clustering. CoRR abs/0804.3575 (2008) - [i6]Navin Goyal, Luis Rademacher, Santosh S. Vempala:
Expanders via Random Spanning Trees. CoRR abs/0807.1496 (2008) - 2007
- [j32]László Lovász, Santosh S. Vempala:
The geometry of logconcave functions and sampling algorithms. Random Struct. Algorithms 30(3): 307-358 (2007) - [j31]Imre Bárány, Santosh S. Vempala, Adrian Vetta:
Nash equilibria in random games. Random Struct. Algorithms 31(4): 391-405 (2007) - [c56]Anirudh Ramachandran, Nick Feamster, Santosh S. Vempala:
Filtering spam with behavioral blacklisting. CCS 2007: 342-351 - [c55]Santosh S. Vempala:
Spectral Algorithms for Learning and Clustering. COLT 2007: 3-4 - [c54]Alexandre Belloni, Robert M. Freund, Santosh S. Vempala:
An Efficient Re-scaled Perceptron Algorithm for Conic Systems. COLT 2007: 393-408 - [c53]Daniel Stefankovic, Santosh S. Vempala, Eric Vigoda:
Adaptive Simulated Annealing: A Near-optimal Connection between Sampling and Counting. FOCS 2007: 183-193 - [c52]Varun Kanade, Santosh S. Vempala:
Life (and routing) on the Wireless Manifold. HotNets 2007 - [c51]Murtaza Motiwala, Nick Feamster, Santosh S. Vempala:
Path Splicing: Reliable Connectivity with Rapid Recovery. HotNets 2007 - 2006
- [j30]Christos H. Papadimitriou, Santosh S. Vempala:
On The Approximability Of The Traveling Salesman Problem. Comb. 26(1): 101-120 (2006) - [j29]Joseph Cheriyan, Santosh S. Vempala, Adrian Vetta:
Network Design Via Iterative Rounding Of Setpair Relaxations. Comb. 26(3): 255-275 (2006) - [j28]László Lovász, Santosh S. Vempala:
Simulated annealing in convex bodies and an O*(n4) volume algorithm. J. Comput. Syst. Sci. 72(2): 392-417 (2006) - [j27]Rosa I. Arriaga, Santosh S. Vempala:
An algorithmic theory of learning: Robust concepts and random projection. Mach. Learn. 63(2): 161-182 (2006) - [j26]Maria-Florina Balcan, Avrim Blum, Santosh S. Vempala:
Kernels as features: On kernels, margins, and low-dimensional mappings. Mach. Learn. 65(1): 79-94 (2006) - [j25]Adam Tauman Kalai, Santosh S. Vempala:
Simulated Annealing for Convex Optimization. Math. Oper. Res. 31(2): 253-266 (2006) - [j24]László Lovász, Santosh S. Vempala:
Hit-and-Run from a Corner. SIAM J. Comput. 35(4): 985-1005 (2006) - [j23]Amit Deshpande, Luis Rademacher, Santosh S. Vempala, Grant Wang:
Matrix Approximation and Projective Clustering via Volume Sampling. Theory Comput. 2(12): 225-247 (2006) - [j22]David Cheng, Ravi Kannan, Santosh S. Vempala, Grant Wang:
A divide-and-merge methodology for clustering. ACM Trans. Database Syst. 31(4): 1499-1525 (2006) - [c50]Amit Deshpande, Santosh S. Vempala:
Adaptive Sampling and Fast Low-Rank Matrix Approximation. APPROX-RANDOM 2006: 292-303 - [c49]László Lovász, Santosh S. Vempala:
Fast Algorithms for Logconcave Functions: Sampling, Rounding, Integration and Optimization. FOCS 2006: 57-68 - [c48]Luis Rademacher, Santosh S. Vempala:
Dispersion of Mass and the Complexity of Randomized Geometric Algorithms. FOCS 2006: 729-738 - [c47]Sanjeev Arora, László Lovász, Ilan Newman, Yuval Rabani, Yuri Rabinovich, Santosh S. Vempala:
Local versus global properties of metric spaces. SODA 2006: 41-50 - [c46]Amit Deshpande, Luis Rademacher, Santosh S. Vempala, Grant Wang:
Matrix approximation and projective clustering via volume sampling. SODA 2006: 1117-1126 - [c45]David Pritchard, Santosh S. Vempala:
Symmetric network computation. SPAA 2006: 261-270 - [i5]Luis Rademacher, Santosh S. Vempala:
Dispersion of Mass and the Complexity of Randomized Geometric Algorithms. CoRR abs/cs/0608054 (2006) - [i4]Daniel Stefankovic, Santosh S. Vempala, Eric Vigoda:
Adaptive Simulated Annealing: A Near-optimal Connection between Sampling and Counting. CoRR abs/cs/0612058 (2006) - [i3]Amit Deshpande, Santosh S. Vempala:
Adaptive Sampling and Fast Low-Rank Matrix Approximation. Electron. Colloquium Comput. Complex. TR06 (2006) - [i2]Luis Rademacher, Santosh S. Vempala:
Dispersion of Mass and the Complexity of Randomized Geometric Algorithms. Electron. Colloquium Comput. Complex. TR06 (2006) - 2005
- [j21]Adam Tauman Kalai, Santosh S. Vempala:
Efficient algorithms for online decision problems. J. Comput. Syst. Sci. 71(3): 291-307 (2005) - [c44]Ravindran Kannan, Hadi Salmasian, Santosh S. Vempala:
The Spectral Method for General Mixture Models. COLT 2005: 444-457 - [c43]Imre Bárány, Santosh S. Vempala, Adrian Vetta:
Nash Equilibria in Random Games. FOCS 2005: 123-131 - [c42]David Cheng, Santosh S. Vempala, Ravi Kannan, Grant Wang:
A divide-and-merge methodology for clustering. PODS 2005: 196-205 - [c41]Wenceslas Fernandez de la Vega, Marek Karpinski, Ravi Kannan, Santosh S. Vempala:
Tensor decomposition and approximation schemes for constraint satisfaction problems. STOC 2005: 747-754 - 2004
- [b1]Santosh S. Vempala:
The Random Projection Method. DIMACS Series in Discrete Mathematics and Theoretical Computer Science 65, DIMACS/AMS 2004, ISBN 978-0-8218-3793-1, pp. 1-103 - [j20]Ravi Kannan, Santosh S. Vempala, Adrian Vetta:
On clusterings: Good, bad and spectral. J. ACM 51(3): 497-515 (2004) - [j19]Dimitris Bertsimas, Santosh S. Vempala:
Solving convex programs by random walks. J. ACM 51(4): 540-556 (2004) - [j18]Alan M. Frieze, Ravi Kannan, Santosh S. Vempala:
Fast monte-carlo algorithms for finding low-rank approximations. J. ACM 51(6): 1025-1041 (2004) - [j17]John Dunagan, Santosh S. Vempala:
Optimal outlier removal in high-dimensional spaces. J. Comput. Syst. Sci. 68(2): 335-373 (2004) - [j16]Santosh S. Vempala, Grant Wang:
A spectral algorithm for learning mixture models. J. Comput. Syst. Sci. 68(4): 841-860 (2004) - [j15]Petros Drineas, Alan M. Frieze, Ravi Kannan, Santosh S. Vempala, V. Vinay:
Clustering Large Graphs via the Singular Value Decomposition. Mach. Learn. 56(1-3): 9-33 (2004) - [j14]Robert D. Carr, Santosh S. Vempala:
On the Held-Karp relaxation for the asymmetric and symmetric traveling salesman problems. Math. Program. 100(3): 569-587 (2004) - [j13]Claudson F. Bornstein, Santosh S. Vempala:
Flow metrics. Theor. Comput. Sci. 321(1): 13-24 (2004) - [c40]Maria-Florina Balcan, Avrim Blum, Santosh S. Vempala:
On Kernels, Margins, and Low-Dimensional Mappings. ALT 2004: 194-205 - [c39]Luis Rademacher, Santosh S. Vempala:
Testing Geometric Convexity. FSTTCS 2004: 469-480 - [c38]László Lovász, Santosh S. Vempala:
Hit-and-run from a corner. STOC 2004: 310-314 - [c37]John Dunagan, Santosh S. Vempala:
A simple polynomial-time rescaling algorithm for solving linear programs. STOC 2004: 315-320 - [i1]Hadi Salmasian, Ravindran Kannan, Santosh S. Vempala:
The Spectral Method for Mixture Models. Electron. Colloquium Comput. Complex. TR04 (2004) - 2003
- [j12]Joseph Cheriyan, Santosh S. Vempala, Adrian Vetta:
An Approximation Algorithm for the Minimum-Cost k-Vertex Connected Subgraph. SIAM J. Comput. 32(4): 1050-1055 (2003) - [c36]Adam Kalai, Santosh S. Vempala:
Efficient Algorithms for Online Decision Problems. COLT 2003: 26-40 - [c35]László Lovász, Santosh S. Vempala:
Logconcave Functions: Geometry and Efficient Sampling Algorithms. FOCS 2003: 640-649 - [c34]László Lovász, Santosh S. Vempala:
Simulated Annealing in Convex Bodies and an 0*(n4) Volume Algorithm. FOCS 2003: 650-659 - 2002
- [j11]Adam Kalai, Santosh S. Vempala:
Efficient Algorithms for Universal Portfolios. J. Mach. Learn. Res. 3: 423-440 (2002) - [j10]Robert D. Carr, Santosh S. Vempala:
Randomized metarounding. Random Struct. Algorithms 20(3): 343-352 (2002) - [c33]Santosh S. Vempala, Grant Wang:
A Spectral Algorithm for Learning Mixtures of Distributions. FOCS 2002: 113- - [c32]Claudson F. Bornstein, Santosh S. Vempala:
Flow Metrics. LATIN 2002: 516-527 - [c31]Dimitris Bertsimas, Santosh S. Vempala:
Solving convex programs by random walks. STOC 2002: 109-115 - [c30]Joseph Cheriyan, Santosh S. Vempala, Adrian Vetta:
Approximation algorithms for minimum-cost k-vertex connected subgraphs. STOC 2002: 306-312 - 2001
- [j9]Prasad Tetali, Santosh S. Vempala:
Random Sampling of Euler Tours. Algorithmica 30(3): 376-385 (2001) - [c29]Joseph Cheriyan, Santosh S. Vempala:
Edge Covers of Setpairs and the Iterative Rounding Method. IPCO 2001: 30-44 - [c28]Alantha Newman, Santosh S. Vempala:
Fences Are Futile: On Relaxations for the Linear Ordering Problem. IPCO 2001: 333-347 - [c27]John Dunagan, Santosh S. Vempala:
On Euclidean Embeddings and Bandwidth Minimization. RANDOM-APPROX 2001: 229-240 - [c26]John Dunagan, Santosh S. Vempala:
Optimal outlier removal in high-dimensional. STOC 2001: 627-636 - 2000
- [j8]Christos H. Papadimitriou, Prabhakar Raghavan, Hisao Tamaki, Santosh S. Vempala:
Latent Semantic Indexing: A Probabilistic Analysis. J. Comput. Syst. Sci. 61(2): 217-235 (2000) - [j7]Avrim Blum, Goran Konjevod, R. Ravi, Santosh S. Vempala:
Semi-definite relaxations for minimum bandwidth and other vertex-ordering problems. Theor. Comput. Sci. 235(1): 25-42 (2000) - [c25]Santosh S. Vempala, Adrian Vetta:
Factor 4/3 approximations for minimum 2-connected subgraphs. APPROX 2000: 262-273 - [c24]Ravi Kannan, Santosh S. Vempala, Adrian Vetta:
On Clusterings - Good, Bad and Spectral. FOCS 2000: 367-377 - [c23]Adam Kalai, Santosh S. Vempala:
Efficient Algorithms for Universal Portfolios. FOCS 2000: 486-491 - [c22]Robert D. Carr, Santosh S. Vempala, Jacques Mandler:
Towards a 4/3 approximation for the asymmetric traveling salesman problem. SODA 2000: 116-125 - [c21]Robert D. Carr, Santosh S. Vempala:
Randomized metarounding (extended abstract). STOC 2000: 58-62 - [c20]Christos H. Papadimitriou, Santosh S. Vempala:
On the approximability of the traveling salesman problem (extended abstract). STOC 2000: 126-133
1990 – 1999
- 1999
- [j6]Avrim Blum, R. Ravi, Santosh S. Vempala:
A Constant-Factor Approximation Algorithm for the k-MST Problem. J. Comput. Syst. Sci. 58(1): 101-108 (1999) - [j5]Ravi Kannan, Prasad Tetali, Santosh S. Vempala:
Simple Markov-chain algorithms for generating bipartite graphs and tournaments. Random Struct. Algorithms 14(4): 293-308 (1999) - [c19]Rosa I. Arriaga, Santosh S. Vempala:
An Algorithmic Theory of Learning: Robust Concepts and Random Projection. FOCS 1999: 616-623 - [c18]Santosh S. Vempala, Berthold Vöcking:
Approximating Multicast Congestion. ISAAC 1999: 367-372 - [c17]Petros Drineas, Alan M. Frieze, Ravi Kannan, Santosh S. Vempala, V. Vinay:
Clustering in Large Graphs and Matrices. SODA 1999: 291-299 - [c16]Santosh S. Vempala, Mihalis Yannakakis:
A Convex Relaxation for the Asymmetric TSP. SODA 1999: 975-976 - 1998
- [j4]Avrim Blum, Alan M. Frieze, Ravi Kannan, Santosh S. Vempala:
A Polynomial-Time Algorithm for Learning Noisy Linear Threshold Functions. Algorithmica 22(1/2): 35-52 (1998) - [j3]Baruch Awerbuch, Yossi Azar, Avrim Blum, Santosh S. Vempala:
New Approximation Guarantees for Minimum-Weight k-Trees and Prize-Collecting Salesmen. SIAM J. Comput. 28(1): 254-262 (1998) - [j2]Joseph S. B. Mitchell, Avrim Blum, Prasad Chalasani, Santosh S. Vempala:
A Constant-Factor Approximation Algorithm for the Geometric k-MST Problem in the Plane. SIAM J. Comput. 28(3): 771-781 (1998) - [c15]Alan M. Frieze, Ravi Kannan, Santosh S. Vempala:
Fast Monte-Carlo Algorithms for Finding Low-Rank Approximations. FOCS 1998: 370-378 - [c14]Santosh S. Vempala:
Random Projection: A New Approach to VLSI Layout. FOCS 1998: 389-395 - [c13]Christos H. Papadimitriou, Prabhakar Raghavan, Hisao Tamaki, Santosh S. Vempala:
Latent Semantic Indexing: A Probabilistic Analysis. PODS 1998: 159-168 - [c12]Avrim Blum, Goran Konjevod, R. Ravi, Santosh S. Vempala:
Semi-Definite Relaxations for Minimum Bandwidth and other Vertex-Ordering Problems. STOC 1998: 100-105 - 1997
- [j1]Andrew Kotlov, László Lovász, Santosh S. Vempala:
The Colin de Verdière Number and Sphere Representations of a Graph. Comb. 17(4): 483-521 (1997) - [c11]Santosh S. Vempala:
A Random Sampling Based Algorithm for Learning the Intersection of Half-spaces. FOCS 1997: 508-513 - [c10]Prasad Tetali, Santosh S. Vempala:
Random Sampling of Euler Tours. RANDOM 1997: 57-66 - [c9]Ravi Kannan, Prasad Tetali, Santosh S. Vempala:
Simple Markov-Chain Algorithms for Generating Bipartite Graphs and Tournaments (Extended Abstract). SODA 1997: 193-200 - [c8]Piotr Indyk, Rajeev Motwani, Prabhakar Raghavan, Santosh S. Vempala:
Locality-Preserving Hashing in Multidimensional Spaces. STOC 1997: 618-625 - [c7]Ravi Kannan, Santosh S. Vempala:
Sampling Lattice Points. STOC 1997: 696-700 - 1996
- [c6]Avrim Blum, Alan M. Frieze, Ravi Kannan, Santosh S. Vempala:
A Polynomial-Time Algorithm for Learning Noisy Linear Threshold Functions. FOCS 1996: 330-338 - [c5]Avrim Blum, R. Ravi, Santosh S. Vempala:
A Constant-factor Approximation Algorithm for the k MST Problem (Extended Abstract). STOC 1996: 442-448 - 1995
- [c4]Baruch Awerbuch, Yossi Azar, Avrim Blum, Santosh S. Vempala:
Improved approximation guarantees for minimum-weight k-trees and prize-collecting salesmen. STOC 1995: 277-283 - [c3]Avrim Blum, Prasad Chalasani, Santosh S. Vempala:
A constant-factor approximation for the k-MST problem in the plane. STOC 1995: 294-302 - 1994
- [c2]Vivek Arora, Santosh S. Vempala, Huzur Saran, Vijay V. Vazirani:
A Limited-Backtrack Greedy Schema for Approximation Algorithms. FSTTCS 1994: 318-329 - 1993
- [c1]Naveen Garg, Santosh S. Vempala, Aman Singla:
Improved Approximation Algorithms for Biconnected Subgraphs via Better Lower Bounding Techniques. SODA 1993: 103-111
Coauthor Index
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