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Santosh 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) - [c152]Max Dabagia, Christos H. Papadimitriou, Santosh S. Vempala:
Computation with Sequences of Assemblies in a Model of the Brain. ALT 2024: 499-504 - [c151]Khashayar Gatmiry, Jonathan A. Kelner, Santosh S. Vempala:
Sampling Polytopes with Riemannian HMC: Faster Mixing via the Lewis Weights Barrier. COLT 2024: 1796-1881 - [c150]Yunbum Kook, Santosh S. Vempala:
Gaussian Cooling and Dikin Walks: The Interior-Point Method for Logconcave Sampling. COLT 2024: 3137-3240 - [c149]Yunbum Kook, Santosh S. Vempala, Matthew Shunshi Zhang:
In-and-Out: Algorithmic Diffusion for Sampling Convex Bodies. NeurIPS 2024 - [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)