Santosh S. Vempala

321 papers A* 108A 8B 13C 3Misc 3Journal 165Unranked 18

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	The Geometry of Efficient Nonconvex Sampling. CoRR Santosh S. Vempala, Andre Wibisono
2025	A*	`conf`	Does GPT Really Get It? A Hierarchical Scale to Quantify Human and AI's Understanding of Algorithms. AAAI Mirabel Reid, Santosh S. Vempala
2025	A*	`conf`	Faster Logconcave Sampling from a Cold Start in High Dimension. FOCS Yunbum Kook, Santosh S. Vempala
2025	J	`jnl`	Faster logconcave sampling from a cold start in high dimension. CoRR Yunbum Kook, Santosh S. Vempala
2025	J	`jnl`	Provable Long-Range Benefits of Next-Token Prediction. CoRR Xinyuan Cao, Santosh S. Vempala
2025	A*	`conf`	Sampling and Integration of Logconcave Functions by Algorithmic Diffusion. STOC Yunbum Kook, Santosh S. Vempala
2025	J	`jnl`	Solving Sparse Linear Systems Faster than Matrix Multiplication. J. ACM Richard Peng, Santosh S. Vempala
2025	J	`jnl`	The Localization Method for High-Dimensional Inequalities. CoRR Yunbum Kook, Santosh S. Vempala
2025	J	`jnl`	Why Language Models Hallucinate. CoRR Adam Tauman Kalai, Ofir Nachum, Santosh S. Vempala, Edwin Zhang
2024	A*	`conf`	Calibrated Language Models Must Hallucinate. STOC Adam Tauman Kalai, Santosh S. Vempala
2024	J	`jnl`	Coin-Flipping In The Brain: Statistical Learning with Neuronal Assemblies. CoRR Max Dabagia, Daniel Mitropolsky, Christos H. Papadimitriou, Santosh S. Vempala
2024	J	`jnl`	Computation With Sequences of Assemblies in a Model of the Brain. Neural Comput. Max Dabagia, Christos H. Papadimitriou, Santosh S. Vempala
2024	B	`conf`	Computation with Sequences of Assemblies in a Model of the Brain. ALT Max Dabagia, Christos H. Papadimitriou, Santosh S. Vempala
2024	J	`jnl`	Does GPT Really Get It? A Hierarchical Scale to Quantify Human vs AI's Understanding of Algorithms. CoRR Mirabel Reid, Santosh S. Vempala
2024	A*	`conf`	Gaussian Cooling and Dikin Walks: The Interior-Point Method for Logconcave Sampling. COLT Yunbum Kook, Santosh S. Vempala
2024	A*	`conf`	In-and-Out: Algorithmic Diffusion for Sampling Convex Bodies. NeurIPS Yunbum Kook, Santosh S. Vempala, Matthew Shunshi Zhang
2024	J	`jnl`	In-and-Out: Algorithmic Diffusion for Sampling Convex Bodies. CoRR Yunbum Kook, Santosh S. Vempala, Matthew Shunshi Zhang
2024	A*	`conf`	Sampling Polytopes with Riemannian HMC: Faster Mixing via the Lewis Weights Barrier. COLT Khashayar Gatmiry, Jonathan A. Kelner, Santosh S. Vempala
2024	J	`jnl`	Sampling and Integration of Logconcave Functions by Algorithmic Diffusion. CoRR Yunbum Kook, Santosh S. Vempala
2024	J	`jnl`	Solving Sparse Linear Systems Faster than Matrix Multiplication. Commun. ACM Richard Peng, Santosh S. Vempala
2023	A*	`conf`	Beyond Moments: Robustly Learning Affine Transformations with Asymptotically Optimal Error. FOCS He Jia, Pravesh K. Kothari, Santosh S. Vempala
2023	J	`jnl`	Beyond Moments: Robustly Learning Affine Transformations with Asymptotically Optimal Error. CoRR He Jia, Pravesh Kothari, Santosh S. Vempala
2023	J	`jnl`	Calibrated Language Models Must Hallucinate. CoRR Adam Tauman Kalai, Santosh S. Vempala
2023	J	`jnl`	Computation with Sequences in the Brain. CoRR Max Dabagia, Christos H. Papadimitriou, Santosh S. Vempala
2023	A*	`conf`	Condition-number-independent Convergence Rate of Riemannian Hamiltonian Monte Carlo with Numerical Integrators. COLT Yunbum Kook, Yin Tat Lee, Ruoqi Shen, Santosh S. Vempala
2023	A*	`conf`	Contrastive Moments: Unsupervised Halfspace Learning in Polynomial Time. NeurIPS Xinyuan Cao, Santosh S. Vempala
2023	J	`jnl`	Contrastive Moments: Unsupervised Halfspace Learning in Polynomial Time. CoRR Xinyuan Cao, Santosh S. Vempala
2023	J	`jnl`	Convergence of Gibbs Sampling: Coordinate Hit-and-Run Mixes Fast. Discret. Comput. Geom. Aditi Laddha, Santosh S. Vempala
2023	J	`jnl`	Efficiently Sampling the PSD Cone with the Metric Dikin Walk. CoRR Yunbum Kook, Santosh S. Vempala
2023	A*	`conf`	Is Planted Coloring Easier than Planted Clique? COLT Pravesh Kothari, Santosh S. Vempala, Alexander S. Wein, Jeff Xu
2023	J	`jnl`	Is Planted Coloring Easier than Planted Clique? CoRR Pravesh K. Kothari, Santosh S. Vempala, Alexander S. Wein, Jeff Xu
2023	J	`jnl`	Sampling with Barriers: Faster Mixing via Lewis Weights. CoRR Khashayar Gatmiry, Jonathan A. Kelner, Santosh S. Vempala
2023	A*	`conf`	The Bit Complexity of Efficient Continuous Optimization. FOCS Mehrdad Ghadiri, Richard Peng, Santosh S. Vempala
2023	J	`jnl`	The Bit Complexity of Efficient Continuous Optimization. CoRR Mehrdad Ghadiri, Richard Peng, Santosh S. Vempala
2023	A*	`conf`	The k-Cap Process on Geometric Random Graphs. COLT Mirabel E. Reid, Santosh S. Vempala
2022	J	`jnl`	A Slightly Improved Bound for the KLS Constant. CoRR Arun Jambulapati, Yin Tat Lee, Santosh S. Vempala
2022	A	`conf`	A Unified Approach to Discrepancy Minimization. APPROX/RANDOM Nikhil Bansal, Aditi Laddha, Santosh S. Vempala
2022	J	`jnl`	A Unified Approach to Discrepancy Minimization. CoRR Nikhil Bansal, Aditi Laddha, Santosh S. Vempala
2022	J	`jnl`	A unified view of graph regularity via matrix decompositions. Random Struct. Algorithms Greg Bodwin, Santosh S. Vempala
2022	J	`jnl`	Approximating sparse graphs: The random overlapping communities model. Random Struct. Algorithms Samantha Petti, Santosh S. Vempala
2022	A*	`conf`	Assemblies of neurons learn to classify well-separated distributions. COLT Max Dabagia, Santosh S. Vempala, Christos H. Papadimitriou
2022	J	`jnl`	Condition-number-independent Convergence Rate of Riemannian Hamiltonian Monte Carlo with Numerical Integrators. CoRR Yunbum Kook, Yin Tat Lee, Ruoqi Shen, Santosh S. Vempala
2022	J	`jnl`	Constant-Factor Approximation Algorithms for Socially Fair k-Clustering. CoRR Mehrdad Ghadiri, Mohit Singh, Santosh S. Vempala
2022	J	`jnl`	Convergence of the Riemannian Langevin Algorithm. CoRR Khashayar Gatmiry, Santosh S. Vempala
2022	J	`jnl`	Geodesic Walks in Polytopes. SIAM J. Comput. Yin Tat Lee, Santosh S. Vempala
2022	A	`conf`	How and When Random Feedback Works: A Case Study of Low-Rank Matrix Factorization. AISTATS Shivam Garg, Santosh S. Vempala
2022	J	`jnl`	Optimal Convergence Rate of Hamiltonian Monte Carlo for Strongly Logconcave Distributions. Theory Comput. Zongchen Chen, Santosh S. Vempala
2022	A	`conf`	Provable Lifelong Learning of Representations. AISTATS Xinyuan Cao, Weiyang Liu, Santosh S. Vempala
2022	A*	`conf`	Robustly learning mixtures of STOC Ainesh Bakshi, Ilias Diakonikolas, He Jia, Daniel M. Kane, Pravesh K. Kothari, Santosh S. Vempala
2022	A*	`conf`	Sampling with Riemannian Hamiltonian Monte Carlo in a Constrained Space. NeurIPS Yunbum Kook, Yin Tat Lee, Ruoqi Shen, Santosh S. Vempala
2022	J	`jnl`	Sampling with Riemannian Hamiltonian Monte Carlo in a Constrained Space. CoRR Yunbum Kook, Yin Tat Lee, Ruoqi Shen, Santosh S. Vempala
2022	J	`jnl`	Socially fair network design via iterative rounding. Oper. Res. Lett. Aditi Laddha, Mohit Singh, Santosh S. Vempala
2022	A*	`conf`	The Manifold Joys of Sampling (Invited Talk). ICALP Yin Tat Lee, Santosh S. Vempala
2022	B	`conf`	The Mirror Langevin Algorithm Converges with Vanishing Bias. ALT Ruilin Li, Molei Tao, Santosh S. Vempala, Andre Wibisono
2022	J	`jnl`	The k-Cap Process on Geometric Random Graphs. CoRR Mirabel Reid, Santosh S. Vempala
2021	J	`jnl`	Assemblies of neurons can learn to classify well-separated distributions. CoRR Max Dabagia, Christos H. Papadimitriou, Santosh S. Vempala
2021	A*	`conf`	Convergence of Gibbs Sampling: Coordinate Hit-And-Run Mixes Fast. SoCG Aditi Laddha, Santosh S. Vempala
2021	J	`jnl`	How and When Random Feedback Works: A Case Study of Low-Rank Matrix Factorization. CoRR Shivam Garg, Santosh S. Vempala
2021	J	`jnl`	Provable Lifelong Learning of Representations. CoRR Xinyuan Cao, Weiyang Liu, Santosh S. Vempala
2021	A*	`conf`	Reducing isotropy and volume to KLS: an STOC He Jia, Aditi Laddha, Yin Tat Lee, Santosh S. Vempala
2021	—	`conf`	Socially Fair k-Means Clustering. FAccT Mehrdad Ghadiri, Samira Samadi, Santosh S. Vempala
2021	A*	`conf`	Solving Sparse Linear Systems Faster than Matrix Multiplication. SODA Richard Peng, Santosh S. Vempala
2021	J	`jnl`	Sparse Regression Faster than d CoRR Mehrdad Ghadiri, Richard Peng, Santosh S. Vempala
2021	J	`jnl`	The Mirror Langevin Algorithm Converges with Vanishing Bias. CoRR Ruilin Li, Molei Tao, Santosh S. Vempala, Andre Wibisono
2021	J	`jnl`	Tutorial on the Robust Interior Point Method. CoRR Yin Tat Lee, Santosh S. Vempala
2020	J	`jnl`	Convergence of Gibbs Sampling: Coordinate Hit-and-Run Mixes Fast. CoRR Aditi Laddha, Santosh S. Vempala
2020	J	`jnl`	Fair k-Means Clustering. CoRR Mehrdad Ghadiri, Samira Samadi, Santosh S. Vempala
2020	J	`jnl`	Reducing Isotropy and Volume to KLS: An O(n CoRR He Jia, Aditi Laddha, Yin Tat Lee, Santosh S. Vempala
2020	J	`jnl`	Robustly Learning Mixtures of k Arbitrary Gaussians. CoRR Ainesh Bakshi, Ilias Diakonikolas, He Jia, Daniel M. Kane, Pravesh K. Kothari, Santosh S. Vempala
2020	J	`jnl`	Solving Sparse Linear Systems Faster than Matrix Multiplication. CoRR Richard Peng, Santosh S. Vempala
2020	A*	`conf`	Strong self-concordance and sampling. STOC Aditi Laddha, Yin Tat Lee, Santosh S. Vempala
2020	A*	`conf`	The Communication Complexity of Optimization. SODA Santosh S. Vempala, Ruosong Wang, David P. Woodruff
2020	J	`jnl`	The complexity of human computation via a concrete model with an application to passwords. Proc. Natl. Acad. Sci. USA Manuel Blum, Santosh S. Vempala
2019	J	`jnl`	A 4/3-Approximation Algorithm for the Minimum 2-Edge Connected Subgraph Problem. ACM Trans. Algorithms Christoph Hunkenschröder, Santosh S. Vempala, Adrian Vetta
2019	—	`ch.`	Brain Computation: A Computer Science Perspective. Computing and Software Science Wolfgang Maass, Christos H. Papadimitriou, Santosh S. Vempala, Robert Legenstein
2019	J	`jnl`	Fair Dimensionality Reduction and Iterative Rounding for SDPs. CoRR Jamie Morgenstern, Samira Samadi, Mohit Singh, Uthaipon Tao Tantipongpipat, Santosh S. Vempala
2019	A*	`conf`	Gradient Descent for One-Hidden-Layer Neural Networks: Polynomial Convergence and SQ Lower Bounds. COLT Santosh S. Vempala, John Wilmes
2019	J	`jnl`	Human-Usable Password Schemas: Beyond Information-Theoretic Security. CoRR Elan Rosenfeld, Santosh S. Vempala, Manuel Blum
2019	J	`jnl`	Matrix Decompositions and Sparse Graph Regularity. CoRR Greg Bodwin, Santosh S. Vempala
2019	A*	`conf`	Multi-Criteria Dimensionality Reduction with Applications to Fairness. NeurIPS Uthaipon Tantipongpipat, Samira Samadi, Mohit Singh, Jamie Morgenstern, Santosh S. Vempala
2019	—	`conf`	Optimal Convergence Rate of Hamiltonian Monte Carlo for Strongly Logconcave Distributions. APPROX-RANDOM Zongchen Chen, Santosh S. Vempala
2019	J	`jnl`	Optimal Convergence Rate of Hamiltonian Monte Carlo for Strongly Logconcave Distributions. CoRR Zongchen Chen, Santosh S. Vempala
2019	A	`conf`	Random Projection in the Brain and Computation with Assemblies of Neurons. ITCS Christos H. Papadimitriou, Santosh S. Vempala
2019	A*	`conf`	Rapid Convergence of the Unadjusted Langevin Algorithm: Isoperimetry Suffices. NeurIPS Santosh S. Vempala, Andre Wibisono
2019	J	`jnl`	Rapid Convergence of the Unadjusted Langevin Algorithm: Log-Sobolev Suffices. CoRR Santosh S. Vempala, Andre Wibisono
2019	—	`conf`	Redesigning a Basic Laboratory Information System for the Global South. ITU Kaleidoscope Jung Wook Park, Aditi Shah, Rosa I. Arriaga, Santosh S. Vempala
2019	J	`jnl`	Strong Self-Concordance and Sampling. CoRR Aditi Laddha, Yin Tat Lee, Santosh S. Vempala
2019	J	`jnl`	The Communication Complexity of Optimization. CoRR Santosh S. Vempala, Ruosong Wang, David P. Woodruff
2018	J	`jnl`	Algorithmic Theory of ODEs and Sampling from Well-conditioned Logconcave Densities. CoRR Yin Tat Lee, Zhao Song, Santosh S. Vempala
2018	J	`jnl`	Approximating Sparse Graphs: The Random Overlapping Communities Model. CoRR Samantha Petti, Santosh S. Vempala
2018	—	`conf`	Continuous Algorithms (Invited Paper). FSTTCS Santosh S. Vempala
2018	A*	`conf`	Convergence rate of riemannian Hamiltonian Monte Carlo and faster polytope volume computation. STOC Yin Tat Lee, Santosh S. Vempala
2018	A*	`conf`	Efficient Convex Optimization with Membership Oracles. COLT Yin Tat Lee, Aaron Sidford, Santosh S. Vempala
2018	J	`jnl`	Gaussian Cooling and O SIAM J. Comput. Ben Cousins, Santosh S. Vempala
2018	A	`conf`	Long Term Memory and the Densest K-Subgraph Problem. ITCS Robert Legenstein, Wolfgang Maass, Christos H. Papadimitriou, Santosh S. Vempala
2018	J	`jnl`	On the Complexity of Random Satisfiability Problems with Planted Solutions. SIAM J. Comput. Vitaly Feldman, Will Perkins, Santosh S. Vempala
2018	J	`jnl`	Polynomial Convergence of Gradient Descent for Training One-Hidden-Layer Neural Networks. CoRR Santosh S. Vempala, John Wilmes
2018	A*	`conf`	Smoothed Analysis of Discrete Tensor Decomposition and Assemblies of Neurons. NeurIPS Nima Anari, Constantinos Daskalakis, Wolfgang Maass, Christos H. Papadimitriou, Amin Saberi, Santosh S. Vempala
2018	J	`jnl`	Smoothed Analysis of Discrete Tensor Decomposition and Assemblies of Neurons. CoRR Nima Anari, Constantinos Daskalakis, Wolfgang Maass, Christos H. Papadimitriou, Amin Saberi, Santosh S. Vempala
2018	J	`jnl`	Special Section on the Fifty-Sixth Annual IEEE Symposium on Foundations of Computer Science (FOCS 2015). SIAM J. Comput. Cristopher Moore, Santosh S. Vempala
2018	A*	`conf`	Stochastic localization + Stieltjes barrier = tight bound for log-Sobolev. STOC Yin Tat Lee, Santosh S. Vempala
2018	J	`jnl`	The Kannan-Lovász-Simonovits Conjecture. CoRR Yin Tat Lee, Santosh S. Vempala
2018	J	`jnl`	The Price of Fair PCA: One Extra Dimension. CoRR Samira Samadi, Uthaipon Tao Tantipongpipat, Jamie Morgenstern, Mohit Singh, Santosh S. Vempala
2018	A*	`conf`	The Price of Fair PCA: One Extra dimension. NeurIPS Samira Samadi, Uthaipon Tao Tantipongpipat, Jamie Morgenstern, Mohit Singh, Santosh S. Vempala
2018	B	`conf`	Usability of Humanly Computable Passwords. HCOMP Samira Samadi, Santosh S. Vempala, Adam Tauman Kalai
2017	A*	`conf`	Adaptive Matrix Vector Product. SODA Santosh S. Vempala, David P. Woodruff
2017	—	`ed.`	Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, APPROX/RANDOM 2017, Berkeley, CA, USA, August 16-18, 2017 APPROX-RANDOM Klaus Jansen, José D. P. Rolim, David Williamson, Santosh S. Vempala
2017	J	`jnl`	CHRR: coordinate hit-and-run with rounding for uniform sampling of constraint-based models. Bioinform. Hulda S. Haraldsdóttir, Ben Cousins, Ines Thiele, Ronan M. T. Fleming, Santosh S. Vempala
2017	J	`jnl`	Efficient Convex Optimization with Membership Oracles. CoRR Yin Tat Lee, Aaron Sidford, Santosh S. Vempala
2017	A*	`conf`	Geodesic walks in polytopes. STOC Yin Tat Lee, Santosh S. Vempala
2017	J	`jnl`	Geometric random edge. Math. Program. Friedrich Eisenbrand, Santosh S. Vempala
2017	—	`conf`	On the Complexity of Learning Neural Networks. NIPS Le Song, Santosh S. Vempala, John Wilmes, Bo Xie
2017	J	`jnl`	On the Complexity of Learning Neural Networks. CoRR Le Song, Santosh S. Vempala, John Wilmes, Bo Xie
2017	J	`jnl`	Random Overlapping Communities: Approximating Motif Densities of Large Graphs. CoRR Samantha Petti, Santosh S. Vempala
2017	J	`jnl`	Randomized algorithms in numerical linear algebra. Acta Numer. Ravindran Kannan, Santosh S. Vempala
2017	J	`jnl`	Statistical Algorithms and a Lower Bound for Detecting Planted Cliques. J. ACM Vitaly Feldman, Elena Grigorescu, Lev Reyzin, Santosh S. Vempala, Ying Xiao
2017	A*	`conf`	Statistical Query Algorithms for Mean Vector Estimation and Stochastic Convex Optimization. SODA Vitaly Feldman, Cristóbal Guzmán, Santosh S. Vempala
2017	J	`jnl`	The Complexity of Human Computation: A Concrete Model with an Application to Passwords. CoRR Manuel Blum, Santosh S. Vempala
2017	A*	`conf`	The Hidden Hubs Problem. COLT Ravindran Kannan, Santosh S. Vempala
2017	A	`conf`	Towards Human Computable Passwords. ITCS Jeremiah Blocki, Manuel Blum, Anupam Datta, Santosh S. Vempala
2017	J	`jnl`	Usability of Humanly Computable Passwords. CoRR Samira Samadi, Santosh S. Vempala, Adam Tauman Kalai
2016	J	`jnl`	A note on non-degenerate integer programs with small sub-determinants. Oper. Res. Lett. Stephan Artmann, Friedrich Eisenbrand, Christoph Glanzer, Timm Oertel, Santosh S. Vempala, Robert Weismantel
2016	J	`jnl`	A practical volume algorithm. Math. Program. Comput. Ben Cousins, Santosh S. Vempala
2016	A*	`conf`	Accelerated Newton Iteration for Roots of Black Box Polynomials. FOCS Anand Louis, Santosh S. Vempala
2016	A*	`conf`	Agnostic Estimation of Mean and Covariance. FOCS Kevin A. Lai, Anup B. Rao, Santosh S. Vempala
2016	J	`jnl`	Agnostic Estimation of Mean and Covariance. CoRR Kevin A. Lai, Anup B. Rao, Santosh S. Vempala
2016	J	`jnl`	Beyond Spectral: Tight Bounds for Planted Gaussians. CoRR Ravi Kannan, Santosh S. Vempala
2016	C	`conf`	C4G BLIS: Health Care Delivery via Iterative Collaborative Design in Resource-constrained Settings. ICTD Santosh S. Vempala, Naomi Chopra, Aishwarya Rajagopal, John Nkengasong, Sidney Akuro
2016	A*	`conf`	Cortical Computation via Iterative Constructions. COLT Christos H. Papadimitriou, Samantha Petti, Santosh S. Vempala
2016	J	`jnl`	Cortical Computation via Iterative Constructions. CoRR Christos H. Papadimitriou, Samantha Petti, Santosh S. Vempala
2016	J	`jnl`	Eldan's Stochastic Localization and the KLS Hyperplane Conjecture: An Improved Lower Bound for Expansion. CoRR Yin Tat Lee, Santosh S. Vempala
2016	J	`jnl`	Geodesic Walks on Polytopes. CoRR Yin Tat Lee, Santosh S. Vempala
2016	J	`jnl`	The Cutting Plane Method is Polynomial for Perfect Matchings. Math. Oper. Res. Karthekeyan Chandrasekaran, László A. Végh, Santosh S. Vempala
2016	—	`conf`	Variable Binding through Assemblies in Spiking Neural Networks. CoCo@NIPS Robert Legenstein, Christos H. Papadimitriou, Santosh S. Vempala, Wolfgang Maass
2015	J	`jnl`	Accelerated Newton Iteration: Roots of Black Box Polynomials and Matrix Eigenvalues. CoRR Anand Louis, Santosh S. Vempala
2015	A*	`conf`	Bypassing KLS: Gaussian Cooling and an O^*(n3) Volume Algorithm. STOC Benjamin Cousins, Santosh S. Vempala
2015	A*	`conf`	Cortical Computation. PODC Christos H. Papadimitriou, Santosh S. Vempala
2015	A*	`conf`	Cortical Learning via Prediction. COLT Christos H. Papadimitriou, Santosh S. Vempala
2015	A*	`conf`	Efficient Representations for Lifelong Learning and Autoencoding. COLT Maria-Florina Balcan, Avrim Blum, Santosh S. Vempala
2015	A*	`conf`	Max vs Min: Tensor Decomposition and ICA with nearly Linear Sample Complexity. COLT Santosh S. Vempala, Ying Xiao
2015	A*	`conf`	On the Complexity of Random Satisfiability Problems with Planted Solutions. STOC Vitaly Feldman, Will Perkins, Santosh S. Vempala
2015	J	`jnl`	Query Complexity of Sampling and Small Geometric Partitions. Comb. Probab. Comput. Navin Goyal, Luis Rademacher, Santosh S. Vempala
2015	J	`jnl`	Statistical Query Algorithms for Stochastic Convex Optimization. CoRR Vitaly Feldman, Cristóbal Guzmán, Santosh S. Vempala
2015	J	`jnl`	Stochastic Billiards for Sampling from the Boundary of a Convex Set. Math. Oper. Res. A. B. Dieker, Santosh S. Vempala
2015	—	`conf`	Subsampled Power Iteration: a Unified Algorithm for Block Models and Planted CSP's. NIPS Vitaly Feldman, Will Perkins, Santosh S. Vempala
2015	J	`jnl`	Visual Categorization with Random Projection. Neural Comput. Rosa I. Arriaga, David Rutter, Maya Cakmak, Santosh S. Vempala
2014	A*	`conf`	A Cubic Algorithm for Computing Gaussian Volume. SODA Ben Cousins, Santosh S. Vempala
2014	J	`jnl`	Bypassing KLS: Gaussian Cooling and an O*(n^3) Volume Algorithm. CoRR Ben Cousins, Santosh S. Vempala
2014	J	`jnl`	Efficient Representations for Life-Long Learning and Autoencoding. CoRR Maria-Florina Balcan, Avrim Blum, Santosh S. Vempala
2014	J	`jnl`	Expanders via Random Spanning Trees. SIAM J. Comput. Alan M. Frieze, Navin Goyal, Luis Rademacher, Santosh S. Vempala
2014	A*	`conf`	Fourier PCA and robust tensor decomposition. STOC Navin Goyal, Santosh S. Vempala, Ying Xiao
2014	J	`jnl`	Geometric Random Edge. CoRR Friedrich Eisenbrand, Santosh S. Vempala
2014	A	`conf`	Integer feasibility of random polytopes: random integer programs. ITCS Karthekeyan Chandrasekaran, Santosh S. Vempala
2014	J	`jnl`	Max vs Min: Independent Component Analysis with nearly Linear Sample Complexity. CoRR Santosh S. Vempala, Ying Xiao
2014	J	`jnl`	On the Complexity of Random Satisfiability Problems with Planted Solutions. Electron. Colloquium Comput. Complex. Vitaly Feldman, Will Perkins, Santosh S. Vempala
2014	A*	`conf`	Principal Component Analysis and Higher Correlations for Distributed Data. COLT Ravi Kannan, Santosh S. Vempala, David P. Woodruff
2014	J	`jnl`	Query complexity of sampling and small geometric partitions. CoRR Navin Goyal, Luis Rademacher, Santosh S. Vempala
2014	J	`jnl`	Stochastic billiards for sampling from the boundary of a convex set. CoRR A. B. Dieker, Santosh S. Vempala
2014	J	`jnl`	Subsampled Power Iteration: a New Algorithm for Block Models and Planted CSP's. CoRR Vitaly Feldman, Will Perkins, Santosh S. Vempala
2014	J	`jnl`	Unsupervised Learning through Prediction in a Model of Cortex. CoRR Christos H. Papadimitriou, Santosh S. Vempala
2013	J	`jnl`	A Cubic Algorithm for Computing Gaussian Volume. CoRR Ben Cousins, Santosh S. Vempala
2013	Misc	`conf`	Complexity of learning subspace juntas and ICA. ACSSC Santosh S. Vempala, Ying Xiao
2013	J	`jnl`	Fourier PCA. CoRR Navin Goyal, Santosh S. Vempala, Ying Xiao
2013	J	`jnl`	Near-optimal deterministic algorithms for volume computation via M-ellipsoids. Proc. Natl. Acad. Sci. USA Daniel Dadush, Santosh S. Vempala
2013	J	`jnl`	Nimble Algorithms for Cloud Computing CoRR Ravindran Kannan, Santosh S. Vempala
2013	J	`jnl`	On the Complexity of Random Satisfiability Problems with Planted Solutions. CoRR Vitaly Feldman, Will Perkins, Santosh S. Vempala
2013	A*	`conf`	Statistical algorithms and a lower bound for detecting planted cliques. STOC Vitaly Feldman, Elena Grigorescu, Lev Reyzin, Santosh S. Vempala, Ying Xiao
2013	J	`jnl`	The Complexity of Approximating Vertex Expansion CoRR Anand Louis, Prasad Raghavendra, Santosh S. Vempala
2013	A*	`conf`	The Complexity of Approximating Vertex Expansion. FOCS Anand Louis, Prasad Raghavendra, Santosh S. Vempala
2013	A*	`conf`	The approximate rank of a matrix and its algorithmic applications: approximate rank. STOC Noga Alon, Troy Lee, Adi Shraibman, Santosh S. Vempala
2012	J	`jnl`	A Deterministic Polynomial-Time Approximation Scheme for Counting Knapsack Solutions. SIAM J. Comput. Daniel Stefankovic, Santosh S. Vempala, Eric Vigoda
2012	J	`jnl`	Deterministic 2^{O(n)} Algorithms for M-Ellipsoids, Lattice Problems and Volume Estimation CoRR Daniel Dadush, Santosh S. Vempala
2012	A*	`conf`	Deterministic construction of an approximate M-ellipsoid and its applications to derandomizing lattice algorithms. SODA Daniel Dadush, Santosh S. Vempala
2012	B	`conf`	Effective Principal Component Analysis. SISAP Santosh S. Vempala
2012	J	`jnl`	Local Versus Global Properties of Metric Spaces. SIAM J. Comput. Sanjeev Arora, László Lovász, Ilan Newman, Yuval Rabani, Yuri Rabinovich, Santosh S. Vempala
2012	A*	`conf`	Many sparse cuts via higher eigenvalues. STOC Anand Louis, Prasad Raghavendra, Prasad Tetali, Santosh S. Vempala
2012	J	`jnl`	Modeling high-dimensional data: technical perspective. Commun. ACM Santosh S. Vempala
2012	—	`conf`	Randomly-oriented k-d Trees Adapt to Intrinsic Dimension. FSTTCS Santosh S. Vempala
2012	J	`jnl`	Statistical Algorithms and a Lower Bound for Planted Clique. Electron. Colloquium Comput. Complex. Vitaly Feldman, Elena Grigorescu, Lev Reyzin, Santosh S. Vempala, Ying Xiao
2012	J	`jnl`	The Approximate Rank of a Matrix and its Algorithmic Applications. Electron. Colloquium Comput. Complex. Noga Alon, Santosh S. Vempala
2012	J	`jnl`	The Complexity of Statistical Algorithms CoRR Vitaly Feldman, Elena Grigorescu, Lev Reyzin, Santosh S. Vempala
2012	A*	`conf`	The Cutting Plane Method Is Polynomial for Perfect Matchings. FOCS Karthekeyan Chandrasekaran, László A. Végh, Santosh S. Vempala
2012	J	`jnl`	The Cutting Plane Method is Polynomial for Perfect Matchings CoRR Karthekeyan Chandrasekaran, László A. Végh, Santosh S. Vempala
2011	J	`jnl`	A Discrepancy based Approach to Integer Programming CoRR Karthekeyan Chandrasekaran, Santosh S. Vempala
2011	—	`conf`	Algorithmic Extensions of Cheeger's Inequality to Higher Eigenvalues and Partitions. APPROX-RANDOM Anand Louis, Prasad Raghavendra, Prasad Tetali, Santosh S. Vempala
2011	J	`jnl`	Algorithms for Implicit Hitting Set Problems CoRR Karthekeyan Chandrasekaran, Richard M. Karp, Erick Moreno-Centeno, Santosh S. Vempala
2011	A*	`conf`	Algorithms for Implicit Hitting Set Problems. SODA Karthekeyan Chandrasekaran, Richard M. Karp, Erick Moreno-Centeno, Santosh S. Vempala
2011	A*	`conf`	An FPTAS for #Knapsack and Related Counting Problems. FOCS Parikshit Gopalan, Adam R. Klivans, Raghu Meka, Daniel Stefankovic, Santosh S. Vempala, Eric Vigoda
2011	J	`jnl`	Deterministic Construction of an Approximate M-Ellipsoid and its Application to Derandomizing Lattice Algorithms CoRR Daniel Dadush, Santosh S. Vempala
2011	A*	`conf`	Enumerative Lattice Algorithms in any Norm Via M-ellipsoid Coverings. FOCS Daniel Dadush, Chris Peikert, Santosh S. Vempala
2011	A*	`conf`	LifeNet: a flexible ad hoc networking solution for transient environments. SIGCOMM Hrushikesh Mehendale, Ashwin Paranjpe, Santosh S. Vempala
2011	J	`jnl`	Many Sparse Cuts via Higher Eigenvalues CoRR Anand Louis, Prasad Raghavendra, Prasad Tetali, Santosh S. Vempala
2011	B	`conf`	On Noise-Tolerant Learning of Sparse Parities and Related Problems. ALT Elena Grigorescu, Lev Reyzin, Santosh S. Vempala
2011	B	`conf`	Semantic Communication for Simple Goals Is Equivalent to On-line Learning. ALT Brendan Juba, Santosh S. Vempala
2011	J	`jnl`	Structure from Local Optima: Learning Subspace Juntas via Higher Order PCA CoRR Santosh S. Vempala, Ying Xiao
2010	J	`jnl`	A Deterministic Polynomial-time Approximation Scheme for Counting Knapsack Solutions CoRR Daniel Stefankovic, Santosh S. Vempala, Eric Vigoda
2010	A	`conf`	A New Approach to Strongly Polynomial Linear Programming. ICS Mihály Bárász, Santosh S. Vempala
2010	J	`jnl`	A random-sampling-based algorithm for learning intersections of halfspaces. J. ACM Santosh S. Vempala
2010	A*	`conf`	Chipping Away at Censorship Firewalls with User-Generated Content. USENIX Security Symposium Sam Burnett, Nick Feamster, Santosh S. Vempala
2010	A*	`conf`	Circumventing censorship with collage. SIGCOMM Sam Burnett, Nick Feamster, Santosh S. Vempala
2010	A*	`conf`	Corrigendum: A Random Sampling Algorithm for Learning an Intersection of Halfspaces. FOCS Santosh S. Vempala
2010	J	`jnl`	Enumerative Algorithms for the Shortest and Closest Lattice Vector Problems in Any Norm via M-Ellipsoid Coverings CoRR Daniel Dadush, Chris Peikert, Santosh S. Vempala
2010	A*	`conf`	Learning Convex Concepts from Gaussian Distributions with PCA. FOCS Santosh S. Vempala
2010	J	`jnl`	Logconcave Random Graphs. Electron. J. Comb. Alan M. Frieze, Santosh S. Vempala, Juan Vera
2010	B	`conf`	On Nash-Equilibria of Approximation-Stable Games. SAGT Pranjal Awasthi, Maria-Florina Balcan, Avrim Blum, Or Sheffet, Santosh S. Vempala
2010	—	`conf`	Recent Progress and Open Problems in Algorithmic Convex Geometry. FSTTCS Santosh S. Vempala
2010	A*	`conf`	Thin Partitions: Isoperimetric Inequalities and a Sampling Algorithm for Star Shaped Bodies. SODA Karthekeyan Chandrasekaran, Daniel Dadush, Santosh S. Vempala
2009	J	`jnl`	Adaptive simulated annealing: A near-optimal connection between sampling and counting. J. ACM Daniel Stefankovic, Santosh S. Vempala, Eric Vigoda
2009	J	`jnl`	An Efficient Rescaled Perceptron Algorithm for Conic Systems. Math. Oper. Res. Alexandre Belloni, Robert M. Freund, Santosh S. Vempala
2009	C	`conf`	Design and deployment of a blood safety monitoring tool. ICTD Stephen Thomas, Adebola Osuntogun, John Pitman, Bright Mulenga, Santosh S. Vempala
2009	C	`conf`	Design of a blood flow system. ICTD Adebola Osuntogun, Stephen Thomas, John Pitman, Sridhar Basavaraju, Bright Mulenga, Santosh S. Vempala
2009	A*	`conf`	Expanders via random spanning trees. SODA Navin Goyal, Luis Rademacher, Santosh S. Vempala
2009	J	`jnl`	Random Tensors and Planted Cliques CoRR S. Charles Brubaker, Santosh S. Vempala
2009	—	`conf`	Random Tensors and Planted Cliques. APPROX-RANDOM S. Charles Brubaker, Santosh S. Vempala
2009	—	`conf`	Sampling s-Concave Functions: The Limit of Convexity Based Isoperimetry. APPROX-RANDOM Karthekeyan Chandrasekaran, Amit Deshpande, Santosh S. Vempala
2009	J	`jnl`	Spectral Algorithms. Found. Trends Theor. Comput. Sci. Ravi Kannan, Santosh S. Vempala
2009	J	`jnl`	The Limit of Convexity Based Isoperimetry: Sampling Harmonic-Concave Functions CoRR Karthekeyan Chandrasekaran, Amit Deshpande, Santosh S. Vempala
2009	J	`jnl`	Thin Partitions: Isoperimetric Inequalities and Sampling Algorithms for some Nonconvex Families CoRR Karthekeyan Chandrasekaran, Daniel Dadush, Santosh S. Vempala
2008	A*	`conf`	A discriminative framework for clustering via similarity functions. STOC Maria-Florina Balcan, Avrim Blum, Santosh S. Vempala
2008	J	`jnl`	A simple polynomial-time rescaling algorithm for solving linear programs. Math. Program. John Dunagan, Santosh S. Vempala
2008	J	`jnl`	Algorithmic Prediction of Health-Care Costs. Oper. Res. Dimitris Bertsimas, Margrét V. Bjarnadóttir, Michael A. Kane, J. Christian Kryder, Rudra Pandey, Santosh S. Vempala, Grant Wang
2008	J	`jnl`	Expanders via Random Spanning Trees CoRR Navin Goyal, Luis Rademacher, Santosh S. Vempala
2008	J	`jnl`	Isotropic PCA and Affine-Invariant Clustering CoRR S. Charles Brubaker, Santosh S. Vempala
2008	A*	`conf`	Isotropic PCA and Affine-Invariant Clustering. FOCS S. Charles Brubaker, Santosh S. Vempala
2008	A*	`conf`	Logconcave random graphs. STOC Alan M. Frieze, Santosh S. Vempala, Juan Vera
2008	A*	`conf`	Path splicing. SIGCOMM Murtaza Motiwala, Megan Elmore, Nick Feamster, Santosh S. Vempala
2008	J	`jnl`	The Spectral Method for General Mixture Models. SIAM J. Comput. Ravindran Kannan, Hadi Salmasian, Santosh S. Vempala
2007	A*	`conf`	Adaptive Simulated Annealing: A Near-optimal Connection between Sampling and Counting. FOCS Daniel Stefankovic, Santosh S. Vempala, Eric Vigoda
2007	A*	`conf`	An Efficient Re-scaled Perceptron Algorithm for Conic Systems. COLT Alexandre Belloni, Robert M. Freund, Santosh S. Vempala
2007	A*	`conf`	Filtering spam with behavioral blacklisting. CCS Anirudh Ramachandran, Nick Feamster, Santosh S. Vempala
2007	Misc	`conf`	Life (and routing) on the Wireless Manifold. HotNets Varun Kanade, Santosh S. Vempala
2007	J	`jnl`	Nash equilibria in random games. Random Struct. Algorithms Imre Bárány, Santosh S. Vempala, Adrian Vetta
2007	Misc	`conf`	Path Splicing: Reliable Connectivity with Rapid Recovery. HotNets Murtaza Motiwala, Nick Feamster, Santosh S. Vempala
2007	A*	`conf`	Spectral Algorithms for Learning and Clustering. COLT Santosh S. Vempala
2007	J	`jnl`	The geometry of logconcave functions and sampling algorithms. Random Struct. Algorithms László Lovász, Santosh S. Vempala
2006	J	`jnl`	A divide-and-merge methodology for clustering. ACM Trans. Database Syst. David Cheng, Ravi Kannan, Santosh S. Vempala, Grant Wang
2006	—	`conf`	Adaptive Sampling and Fast Low-Rank Matrix Approximation. APPROX-RANDOM Amit Deshpande, Santosh S. Vempala
2006	J	`jnl`	Adaptive Sampling and Fast Low-Rank Matrix Approximation. Electron. Colloquium Comput. Complex. Amit Deshpande, Santosh S. Vempala
2006	J	`jnl`	Adaptive Simulated Annealing: A Near-optimal Connection between Sampling and Counting CoRR Daniel Stefankovic, Santosh S. Vempala, Eric Vigoda
2006	J	`jnl`	An algorithmic theory of learning: Robust concepts and random projection. Mach. Learn. Rosa I. Arriaga, Santosh S. Vempala
2006	J	`jnl`	Dispersion of Mass and the Complexity of Randomized Geometric Algorithms CoRR Luis Rademacher, Santosh S. Vempala
2006	A*	`conf`	Dispersion of Mass and the Complexity of Randomized Geometric Algorithms. FOCS Luis Rademacher, Santosh S. Vempala
2006	J	`jnl`	Dispersion of Mass and the Complexity of Randomized Geometric Algorithms. Electron. Colloquium Comput. Complex. Luis Rademacher, Santosh S. Vempala
2006	A*	`conf`	Fast Algorithms for Logconcave Functions: Sampling, Rounding, Integration and Optimization. FOCS László Lovász, Santosh S. Vempala
2006	J	`jnl`	Hit-and-Run from a Corner. SIAM J. Comput. László Lovász, Santosh S. Vempala
2006	J	`jnl`	Kernels as features: On kernels, margins, and low-dimensional mappings. Mach. Learn. Maria-Florina Balcan, Avrim Blum, Santosh S. Vempala
2006	A*	`conf`	Local versus global properties of metric spaces. SODA Sanjeev Arora, László Lovász, Ilan Newman, Yuval Rabani, Yuri Rabinovich, Santosh S. Vempala
2006	J	`jnl`	Matrix Approximation and Projective Clustering via Volume Sampling. Theory Comput. Amit Deshpande, Luis Rademacher, Santosh S. Vempala, Grant Wang
2006	A*	`conf`	Matrix approximation and projective clustering via volume sampling. SODA Amit Deshpande, Luis Rademacher, Santosh S. Vempala, Grant Wang
2006	J	`jnl`	Network Design Via Iterative Rounding Of Setpair Relaxations. Comb. Joseph Cheriyan, Santosh S. Vempala, Adrian Vetta
2006	J	`jnl`	On The Approximability Of The Traveling Salesman Problem. Comb. Christos H. Papadimitriou, Santosh S. Vempala
2006	J	`jnl`	Simulated Annealing for Convex Optimization. Math. Oper. Res. Adam Tauman Kalai, Santosh S. Vempala
2006	J	`jnl`	Simulated annealing in convex bodies and an J. Comput. Syst. Sci. László Lovász, Santosh S. Vempala
2006	B	`conf`	Symmetric network computation. SPAA David Pritchard, Santosh S. Vempala
2005	A*	`conf`	A divide-and-merge methodology for clustering. PODS David Cheng, Santosh S. Vempala, Ravi Kannan, Grant Wang
2005	J	`jnl`	Efficient algorithms for online decision problems. J. Comput. Syst. Sci. Adam Tauman Kalai, Santosh S. Vempala
2005	A*	`conf`	Nash Equilibria in Random Games. FOCS Imre Bárány, Santosh S. Vempala, Adrian Vetta
2005	A*	`conf`	Tensor decomposition and approximation schemes for constraint satisfaction problems. STOC Wenceslas Fernandez de la Vega, Marek Karpinski, Ravi Kannan, Santosh S. Vempala
2005	A*	`conf`	The Spectral Method for General Mixture Models. COLT Ravindran Kannan, Hadi Salmasian, Santosh S. Vempala
2004	A*	`conf`	A simple polynomial-time rescaling algorithm for solving linear programs. STOC John Dunagan, Santosh S. Vempala
2004	J	`jnl`	A spectral algorithm for learning mixture models. J. Comput. Syst. Sci. Santosh S. Vempala, Grant Wang
2004	J	`jnl`	Clustering Large Graphs via the Singular Value Decomposition. Mach. Learn. Petros Drineas, Alan M. Frieze, Ravi Kannan, Santosh S. Vempala, V. Vinay
2004	J	`jnl`	Fast monte-carlo algorithms for finding low-rank approximations. J. ACM Alan M. Frieze, Ravi Kannan, Santosh S. Vempala
2004	J	`jnl`	Flow metrics. Theor. Comput. Sci. Claudson F. Bornstein, Santosh S. Vempala
2004	A*	`conf`	Hit-and-run from a corner. STOC László Lovász, Santosh S. Vempala
2004	B	`conf`	On Kernels, Margins, and Low-Dimensional Mappings. ALT Maria-Florina Balcan, Avrim Blum, Santosh S. Vempala
2004	J	`jnl`	On clusterings: Good, bad and spectral. J. ACM Ravi Kannan, Santosh S. Vempala, Adrian Vetta
2004	J	`jnl`	On the Held-Karp relaxation for the asymmetric and symmetric traveling salesman problems. Math. Program. Robert D. Carr, Santosh S. Vempala
2004	J	`jnl`	Optimal outlier removal in high-dimensional spaces. J. Comput. Syst. Sci. John Dunagan, Santosh S. Vempala
2004	J	`jnl`	Solving convex programs by random walks. J. ACM Dimitris Bertsimas, Santosh S. Vempala
2004	—	`conf`	Testing Geometric Convexity. FSTTCS Luis Rademacher, Santosh S. Vempala
2004	—	`book`	The Random Projection Method Santosh S. Vempala
2004	J	`jnl`	The Spectral Method for Mixture Models Electron. Colloquium Comput. Complex. Hadi Salmasian, Ravindran Kannan, Santosh S. Vempala
2003	J	`jnl`	An Approximation Algorithm for the Minimum-Cost k-Vertex Connected Subgraph. SIAM J. Comput. Joseph Cheriyan, Santosh S. Vempala, Adrian Vetta
2003	A*	`conf`	Efficient Algorithms for Online Decision Problems. COLT Adam Kalai, Santosh S. Vempala
2003	A*	`conf`	Logconcave Functions: Geometry and Efficient Sampling Algorithms FOCS László Lovász, Santosh S. Vempala
2003	A*	`conf`	Simulated Annealing in Convex Bodies and an 0*(n4) Volume Algorithm. FOCS László Lovász, Santosh S. Vempala
2002	A*	`conf`	A Spectral Algorithm for Learning Mixtures of Distributions. FOCS Santosh S. Vempala, Grant Wang
2002	A*	`conf`	Approximation algorithms for minimum-cost k-vertex connected subgraphs. STOC Joseph Cheriyan, Santosh S. Vempala, Adrian Vetta
2002	J	`jnl`	Efficient Algorithms for Universal Portfolios. J. Mach. Learn. Res. Adam Kalai, Santosh S. Vempala
2002	B	`conf`	Flow Metrics. LATIN Claudson F. Bornstein, Santosh S. Vempala
2002	J	`jnl`	Randomized metarounding. Random Struct. Algorithms Robert D. Carr, Santosh S. Vempala
2002	A*	`conf`	Solving convex programs by random walks. STOC Dimitris Bertsimas, Santosh S. Vempala
2001	B	`conf`	Edge Covers of Setpairs and the Iterative Rounding Method. IPCO Joseph Cheriyan, Santosh S. Vempala
2001	B	`conf`	Fences Are Futile: On Relaxations for the Linear Ordering Problem. IPCO Alantha Newman, Santosh S. Vempala
2001	—	`conf`	On Euclidean Embeddings and Bandwidth Minimization. RANDOM-APPROX John Dunagan, Santosh S. Vempala
2001	A*	`conf`	Optimal outlier removal in high-dimensional. STOC John Dunagan, Santosh S. Vempala
2001	J	`jnl`	Random Sampling of Euler Tours. Algorithmica Prasad Tetali, Santosh S. Vempala
2000	A*	`conf`	Efficient Algorithms for Universal Portfolios. FOCS Adam Kalai, Santosh S. Vempala
2000	—	`conf`	Factor 4/3 approximations for minimum 2-connected subgraphs. APPROX Santosh S. Vempala, Adrian Vetta
2000	J	`jnl`	Latent Semantic Indexing: A Probabilistic Analysis. J. Comput. Syst. Sci. Christos H. Papadimitriou, Prabhakar Raghavan, Hisao Tamaki, Santosh S. Vempala
2000	A*	`conf`	On Clusterings - Good, Bad and Spectral. FOCS Ravi Kannan, Santosh S. Vempala, Adrian Vetta
2000	A*	`conf`	On the approximability of the traveling salesman problem (extended abstract). STOC Christos H. Papadimitriou, Santosh S. Vempala
2000	A*	`conf`	Randomized metarounding (extended abstract). STOC Robert D. Carr, Santosh S. Vempala
2000	J	`jnl`	Semi-definite relaxations for minimum bandwidth and other vertex-ordering problems. Theor. Comput. Sci. Avrim Blum, Goran Konjevod, R. Ravi, Santosh S. Vempala
2000	A*	`conf`	Towards a 4/3 approximation for the asymmetric traveling salesman problem. SODA Robert D. Carr, Santosh S. Vempala, Jacques Mandler
1999	J	`jnl`	A Constant-Factor Approximation Algorithm for the J. Comput. Syst. Sci. Avrim Blum, R. Ravi, Santosh S. Vempala
1999	A*	`conf`	A Convex Relaxation for the Asymmetric TSP. SODA Santosh S. Vempala, Mihalis Yannakakis
1999	A*	`conf`	An Algorithmic Theory of Learning: Robust Concepts and Random Projection. FOCS Rosa I. Arriaga, Santosh S. Vempala
1999	B	`conf`	Approximating Multicast Congestion. ISAAC Santosh S. Vempala, Berthold Vöcking
1999	A*	`conf`	Clustering in Large Graphs and Matrices. SODA Petros Drineas, Alan M. Frieze, Ravi Kannan, Santosh S. Vempala, V. Vinay
1999	J	`jnl`	Simple Markov-chain algorithms for generating bipartite graphs and tournaments. Random Struct. Algorithms Ravi Kannan, Prasad Tetali, Santosh S. Vempala
1998	J	`jnl`	A Constant-Factor Approximation Algorithm for the Geometric k-MST Problem in the Plane. SIAM J. Comput. Joseph S. B. Mitchell, Avrim Blum, Prasad Chalasani, Santosh S. Vempala
1998	J	`jnl`	A Polynomial-Time Algorithm for Learning Noisy Linear Threshold Functions. Algorithmica Avrim Blum, Alan M. Frieze, Ravi Kannan, Santosh S. Vempala
1998	A*	`conf`	Fast Monte-Carlo Algorithms for Finding Low-Rank Approximations. FOCS Alan M. Frieze, Ravi Kannan, Santosh S. Vempala
1998	A*	`conf`	Latent Semantic Indexing: A Probabilistic Analysis. PODS Christos H. Papadimitriou, Prabhakar Raghavan, Hisao Tamaki, Santosh S. Vempala
1998	J	`jnl`	New Approximation Guarantees for Minimum-Weight k-Trees and Prize-Collecting Salesmen. SIAM J. Comput. Baruch Awerbuch, Yossi Azar, Avrim Blum, Santosh S. Vempala
1998	A*	`conf`	Random Projection: A New Approach to VLSI Layout. FOCS Santosh S. Vempala
1998	A*	`conf`	Semi-Definite Relaxations for Minimum Bandwidth and other Vertex-Ordering Problems. STOC Avrim Blum, Goran Konjevod, R. Ravi, Santosh S. Vempala
1997	A*	`conf`	A Random Sampling Based Algorithm for Learning the Intersection of Half-spaces. FOCS Santosh S. Vempala
1997	A*	`conf`	Locality-Preserving Hashing in Multidimensional Spaces. STOC Piotr Indyk, Rajeev Motwani, Prabhakar Raghavan, Santosh S. Vempala
1997	—	`conf`	Random Sampling of Euler Tours. RANDOM Prasad Tetali, Santosh S. Vempala
1997	A*	`conf`	Sampling Lattice Points. STOC Ravi Kannan, Santosh S. Vempala
1997	A*	`conf`	Simple Markov-Chain Algorithms for Generating Bipartite Graphs and Tournaments (Extended Abstract). SODA Ravi Kannan, Prasad Tetali, Santosh S. Vempala
1997	J	`jnl`	The Colin de Verdière Number and Sphere Representations of a Graph. Comb. Andrew Kotlov, László Lovász, Santosh S. Vempala
1996	A*	`conf`	A Constant-factor Approximation Algorithm for the STOC Avrim Blum, R. Ravi, Santosh S. Vempala
1996	A*	`conf`	A Polynomial-Time Algorithm for Learning Noisy Linear Threshold Functions. FOCS Avrim Blum, Alan M. Frieze, Ravi Kannan, Santosh S. Vempala
1995	A*	`conf`	A constant-factor approximation for the STOC Avrim Blum, Prasad Chalasani, Santosh S. Vempala
1995	A*	`conf`	Improved approximation guarantees for minimum-weight STOC Baruch Awerbuch, Yossi Azar, Avrim Blum, Santosh S. Vempala
1994	—	`conf`	A Limited-Backtrack Greedy Schema for Approximation Algorithms. FSTTCS Vivek Arora, Santosh S. Vempala, Huzur Saran, Vijay V. Vazirani
1993	A*	`conf`	Improved Approximation Algorithms for Biconnected Subgraphs via Better Lower Bounding Techniques. SODA Naveen Garg, Santosh S. Vempala, Aman Singla