Caching with expiration times. - Parikshit Gopalan; Howard J. Karloff; Aranyak Mehta; Milena Mihail; Nisheeth K. Vishnoi (SODA, 2002)

Non Uniform Random Walks. - Nisheeth K. Vishnoi (DRW, 2003)

Who's The Weakest Link? - Nikhil R. Devanur; Richard J. Lipton; Nisheeth K. Vishnoi (SAGA, 2003)

Deterministic identity testing for multivariate polynomials. - Richard J. Lipton; Nisheeth K. Vishnoi (SODA, 2003)

On the Complexity of Hilbert's 17th Problem. - Nikhil R. Devanur; Richard J. Lipton; Nisheeth K. Vishnoi (FSTTCS, 2004)

Theoretical Aspects of Randomization in Computation. - Nisheeth K. Vishnoi (2004)

On the Fourier Spectrum of Symmetric Boolean Functions with Applications to Learning Symmetric Juntas. - Richard J. Lipton; Evangelos Markakis; Aranyak Mehta; Nisheeth K. Vishnoi (CCC, 2005)

The Impact of Noise on the Scaling of Collectives: A Theoretical Approach. - Saurabh Agarwal; Rahul Garg 001; Nisheeth K. Vishnoi (HiPC, 2005)

Caching with Expiration Times for Internet Applications. - Parikshit Gopalan; Howard J. Karloff; Aranyak Mehta; Milena Mihail; Nisheeth K. Vishnoi (Internet Math., 2005)

Integrality gaps for sparsest cut and minimum linear arrangement problems. - Nikhil R. Devanur; Subhash Khot; Rishi Saket; Nisheeth K. Vishnoi (STOC, 2006)

The Impact of Noise on the Scaling of Collectives: The Nearest Neighbor Model [Extended Abstract]. - Nisheeth K. Vishnoi (HiPC, 2007)

Unique games on expanding constraint graphs are easy: extended abstract. - Sanjeev Arora; Subhash Khot; Alexandra Kolla; David Steurer; Madhur Tulsiani; Nisheeth K. Vishnoi (STOC, 2008)

On partitioning graphs via single commodity flows. - Lorenzo Orecchia; Leonard J. Schulman; Umesh V. Vazirani; Nisheeth K. Vishnoi (STOC, 2008)

On the Fourier spectrum of symmetric Boolean functions. - Mihail N. Kolountzakis; Richard J. Lipton; Evangelos Markakis; Aranyak Mehta; Nisheeth K. Vishnoi (Comb., 2009)

A Spectral Algorithm for Improving Graph Partitions - Michael W. Mahoney; Lorenzo Orecchia; Nisheeth K. Vishnoi (CoRR, 2009)

Algorithms and Hardness for Subspace Approximation - Amit Deshpande 001; Kasturi R. Varadarajan; Madhur Tulsiani; Nisheeth K. Vishnoi (CoRR, 2009)

On the Optimality of a Class of LP-based Algorithms. - Amit Kumar 001; Rajsekar Manokaran; Madhur Tulsiani; Nisheeth K. Vishnoi (Electron. Colloquium Comput. Complex., 2009)

Connections Between Unique Games and Multicut. - David Steurer; Nisheeth K. Vishnoi (Electron. Colloquium Comput. Complex., 2009)

Deterministically testing sparse polynomial identities of unbounded degree. - Markus Bläser; Moritz Hardt; Richard J. Lipton; Nisheeth K. Vishnoi (Inf. Process. Lett., 2009)

Improved Algorithm for Degree Bounded Survivable Network Design Problem. - Anand Louis; Nisheeth K. Vishnoi (SWAT, 2010)

Biased normalized cuts. - Subhransu Maji; Nisheeth K. Vishnoi; Jitendra Malik (CVPR, 2011)

Algorithms and Hardness for Subspace Approximation. - Amit Deshpande 001; Madhur Tulsiani; Nisheeth K. Vishnoi (SODA, 2011)

On LP-Based Approximability for Strict CSPs. - Amit Kumar 001; Rajsekar Manokaran; Madhur Tulsiani; Nisheeth K. Vishnoi (SODA, 2011)

Towards an SDP-based Approach to Spectral Methods: A Nearly-Linear-Time Algorithm for Graph Partitioning and Decomposition. - Lorenzo Orecchia; Nisheeth K. Vishnoi (SODA, 2011)

Hardness of Approximating the Closest Vector Problem with Pre-Processing. - Mikhail Alekhnovich; Subhash Khot; Guy Kindler; Nisheeth K. Vishnoi (Comput. Complex., 2011)

$2^{ log^{1- eps} n}$ Hardness for Closest Vector Problem with Preprocessing - Subhash Khot; Preyas Popat; Nisheeth K. Vishnoi (CoRR, 2011)

Approximating the Exponential, the Lanczos Method and an tilde{O}(m)-Time Spectral Algorithm for Balanced Separator - Lorenzo Orecchia; Sushant Sachdeva; Nisheeth K. Vishnoi (CoRR, 2011)

2log1-έn Hardness for Closest Vector Problem with Preprocessing. - Subhash Khot; Preyas Popat; Nisheeth K. Vishnoi (Electron. Colloquium Comput. Complex., 2011)

A Permanent Approach to the Traveling Salesman Problem. - Nisheeth K. Vishnoi (FOCS, 2012)

2log1-ε n hardness for the closest vector problem with preprocessing. - Subhash Khot; Preyas Popat; Nisheeth K. Vishnoi (STOC, 2012)

Approximating the exponential, the lanczos method and an Õ(m)-time spectral algorithm for balanced separator. - Lorenzo Orecchia; Sushant Sachdeva; Nisheeth K. Vishnoi (STOC, 2012)

A Finite Population Model of Molecular Evolution: Theory and Computation. - Narendra M. Dixit; Piyush Srivastava 001; Nisheeth K. Vishnoi (J. Comput. Biol., 2012)

A local spectral method for graphs: with applications to improving graph partitions and exploring data graphs locally. - Michael W. Mahoney; Lorenzo Orecchia; Nisheeth K. Vishnoi (J. Mach. Learn. Res., 2012)

Stochastic Simulations Suggest that HIV-1 Survives Close to Its Error Threshold. - Kushal Tripathi; Rajesh Balagam; Nisheeth K. Vishnoi; Narendra M. Dixit (PLoS Comput. Biol., 2012)

Making evolution rigorous: the error threshold. - Nisheeth K. Vishnoi (ITCS, 2013)

Towards Polynomial Simplex-Like Algorithms for Market Equlibria. - Jugal Garg; Ruta Mehta; Milind A. Sohoni; Nisheeth K. Vishnoi (SODA, 2013)

Approximation Theory and the Design of Fast Algorithms. - Sushant Sachdeva; Nisheeth K. Vishnoi (CoRR, 2013)

Matrix Inversion Is As Easy As Exponentiation - Sushant Sachdeva; Nisheeth K. Vishnoi (CoRR, 2013)

Lx = b. - Nisheeth K. Vishnoi (Found. Trends Theor. Comput. Sci., 2013)

Entropy, optimization and counting. - Mohit Singh; Nisheeth K. Vishnoi (STOC, 2014)

A quadratically tight partition bound for classical communication complexity and query complexity. - Rahul Jain 001; Troy Lee; Nisheeth K. Vishnoi (CoRR, 2014)

Faster Algorithms via Approximation Theory. - Sushant Sachdeva; Nisheeth K. Vishnoi (Found. Trends Theor. Comput. Sci., 2014)

Almost Polynomial Factor Hardness for Closest Vector Problem with Preprocessing. - Subhash Khot; Preyas Popat; Nisheeth K. Vishnoi (SIAM J. Comput., 2014)

The Speed of Evolution. - Nisheeth K. Vishnoi (SODA, 2015)

A Simple Analysis of the Dikin Walk. - Sushant Sachdeva; Nisheeth K. Vishnoi (CoRR, 2015)

The Unique Games Conjecture, Integrality Gap for Cut Problems and Embeddability of Negative-Type Metrics into ℓ1. - Subhash Khot; Nisheeth K. Vishnoi (J. ACM, 2015)

Evolution and Computation (Invited Talk). - Nisheeth K. Vishnoi (CCC, 2016)

Mixing Time of Markov Chains, Dynamical Systems and Evolution. - Ioannis Panageas; Nisheeth K. Vishnoi (ICALP, 2016)

On the Computational Complexity of Limit Cycles in Dynamical Systems. - Christos H. Papadimitriou; Nisheeth K. Vishnoi (ITCS, 2016)

On a Natural Dynamics for Linear Programming. - Damian Straszak; Nisheeth K. Vishnoi (ITCS, 2016)

Evolutionary Dynamics in Finite Populations Mix Rapidly. - Ioannis Panageas; Piyush Srivastava 001; Nisheeth K. Vishnoi (SODA, 2016)

Natural Algorithms for Flow Problems. - Damian Straszak; Nisheeth K. Vishnoi (SODA, 2016)

How to be Fair and Diverse? - L. Elisa Celis; Amit Deshpande 001; Tarun Kathuria; Nisheeth K. Vishnoi (CoRR, 2016)

IRLS and Slime Mold: Equivalence and Convergence. - Damian Straszak; Nisheeth K. Vishnoi (CoRR, 2016)

Generalized Determinantal Point Processes: The Linear Case. - Damian Straszak; Nisheeth K. Vishnoi (CoRR, 2016)

Evolution and Computing (Dagstuhl Seminar 16011). - Nick Barton; Per Kristian Lehre; Nisheeth K. Vishnoi (Dagstuhl Reports, 2016)

The mixing time of the Dikin walk in a polytope - A simple proof. - Sushant Sachdeva; Nisheeth K. Vishnoi (Oper. Res. Lett., 2016)

On the Complexity of Constrained Determinantal Point Processes. - L. Elisa Celis; Amit Deshpande 001; Tarun Kathuria; Damian Straszak; Nisheeth K. Vishnoi (APPROX-RANDOM, 2017)

Random Walks in Polytopes and Negative Dependence. - Yuval Peres; Mohit Singh; Nisheeth K. Vishnoi (ITCS, 2017)

A Distributed Learning Dynamics in Social Groups. - L. Elisa Celis; Peter M. Krafft; Nisheeth K. Vishnoi (PODC, 2017)

Real stable polynomials and matroids: optimization and counting. - Damian Straszak; Nisheeth K. Vishnoi (STOC, 2017)

A Dynamics for Advertising on Networks. - L. Elisa Celis; Mina Dalirrooyfard; Nisheeth K. Vishnoi (WINE, 2017)

Fair Personalization. - L. Elisa Celis; Nisheeth K. Vishnoi (CoRR, 2017)

On Convex Programming Relaxations for the Permanent. - Damian Straszak; Nisheeth K. Vishnoi (CoRR, 2017)

Group Fairness in Multiwinner Voting. - L. Elisa Celis; Lingxiao Huang; Nisheeth K. Vishnoi (CoRR, 2017)

Computing Maximum Entropy Distributions Everywhere. - Damian Straszak; Nisheeth K. Vishnoi (CoRR, 2017)

Convex Optimization with Nonconvex Oracles. - Oren Mangoubi; Nisheeth K. Vishnoi (CoRR, 2017)

On Geodesically Convex Formulations for the Brascamp-Lieb Constant. - Suvrit Sra; Nisheeth K. Vishnoi; Ozan Yildiz (APPROX-RANDOM, 2018)

Convex Optimization with Unbounded Nonconvex Oracles using Simulated Annealing. - Oren Mangoubi; Nisheeth K. Vishnoi (COLT, 2018)

Ranking with Fairness Constraints. - L. Elisa Celis; Damian Straszak; Nisheeth K. Vishnoi (ICALP, 2018)

Fair and Diverse DPP-Based Data Summarization. - L. Elisa Celis; Vijay Keswani; Damian Straszak; Amit Deshpande 001; Tarun Kathuria; Nisheeth K. Vishnoi (ICML, 2018)

Multiwinner Voting with Fairness Constraints. - L. Elisa Celis; Lingxiao Huang; Nisheeth K. Vishnoi (IJCAI, 2018)

Balanced News Using Constrained Bandit-based Personalization. - Sayash Kapoor; Vijay Keswani; Nisheeth K. Vishnoi; L. Elisa Celis (IJCAI, 2018)

Dimensionally Tight Bounds for Second-Order Hamiltonian Monte Carlo. - Oren Mangoubi; Nisheeth K. Vishnoi (NeurIPS, 2018)

An Algorithmic Framework to Control Bias in Bandit-based Personalization. - L. Elisa Celis; Sayash Kapoor; Farnood Salehi; Nisheeth K. Vishnoi (CoRR, 2018)

Dimensionally Tight Running Time Bounds for Second-Order Hamiltonian Monte Carlo. - Oren Mangoubi; Nisheeth K. Vishnoi (CoRR, 2018)

On Geodesically Convex Formulations for the Brascamp-Lieb Constant. - Nisheeth K. Vishnoi; Ozan Yildiz (CoRR, 2018)

Geodesic Convex Optimization: Differentiation on Manifolds, Geodesics, and Convexity. - Nisheeth K. Vishnoi (CoRR, 2018)

Nonconvex sampling with the Metropolis-adjusted Langevin algorithm. - Oren Mangoubi; Nisheeth K. Vishnoi (COLT, 2019)

Maximum Entropy Distributions: Bit Complexity and Stability. - Damian Straszak; Nisheeth K. Vishnoi (COLT, 2019)

Classification with Fairness Constraints: A Meta-Algorithm with Provable Guarantees. - L. Elisa Celis; Lingxiao Huang; Vijay Keswani; Nisheeth K. Vishnoi (FAT, 2019)

Controlling Polarization in Personalization: An Algorithmic Framework. - L. Elisa Celis; Sayash Kapoor; Farnood Salehi; Nisheeth K. Vishnoi (FAT, 2019)

Faster Polytope Rounding, Sampling, and Volume Computation via a Sub-Linear Ball Walk. - Oren Mangoubi; Nisheeth K. Vishnoi (FOCS, 2019)

Stable and Fair Classification. - Lingxiao Huang; Nisheeth K. Vishnoi (ICML, 2019)

Toward Controlling Discrimination in Online Ad Auctions. - L. Elisa Celis; Anay Mehrotra; Nisheeth K. Vishnoi (ICML, 2019)

Coresets for Clustering with Fairness Constraints. - Lingxiao Huang; Shaofeng H.-C. Jiang; Nisheeth K. Vishnoi (NeurIPS, 2019)

Online sampling from log-concave distributions. - Holden Lee; Oren Mangoubi; Nisheeth K. Vishnoi (NeurIPS, 2019)

A dashboard for controlling polarization in personalization. - L. Elisa Celis; Sayash Kapoor; Farnood Salehi; Vijay Keswani; Nisheeth K. Vishnoi (AI Commun., 2019)

Technical perspective: Isolating a matching when your coins go missing. - Nisheeth K. Vishnoi (Commun. ACM, 2019)

Fair Online Advertising. - L. Elisa Celis; Anay Mehrotra; Nisheeth K. Vishnoi (CoRR, 2019)

Faster algorithms for polytope rounding, sampling, and volume computation via a sublinear "Ball Walk". - Oren Mangoubi; Nisheeth K. Vishnoi (CoRR, 2019)

Fair Distributions from Biased Samples: A Maximum Entropy Optimization Framework. - L. Elisa Celis; Vijay Keswani; Ozan Yildiz; Nisheeth K. Vishnoi (CoRR, 2019)

Belief Propagation, Bethe Approximation and Polynomials. - Damian Straszak; Nisheeth K. Vishnoi (IEEE Trans. Inf. Theory, 2019)

Interventions for ranking in the presence of implicit bias. - L. Elisa Celis; Anay Mehrotra; Nisheeth K. Vishnoi (FAT*, 2020)

Data preprocessing to mitigate bias: A maximum entropy based approach. - L. Elisa Celis; Vijay Keswani; Nisheeth K. Vishnoi (ICML, 2020)

Coresets for Regressions with Panel Data. - Lingxiao Huang; K. Sudhir; Nisheeth K. Vishnoi (NeurIPS, 2020)

Coresets for clustering in Euclidean spaces: importance sampling is nearly optimal. - Lingxiao Huang; Nisheeth K. Vishnoi (STOC, 2020)

Fair Classification with Noisy Protected Attributes. - L. Elisa Celis; Lingxiao Huang; Nisheeth K. Vishnoi (CoRR, 2020)

A Second-order Equilibrium in Nonconvex-Nonconcave Min-max Optimization: Existence and Algorithm. - Oren Mangoubi; Nisheeth K. Vishnoi (CoRR, 2020)

A Provably Convergent and Practical Algorithm for Min-max Optimization with Applications to GANs. - Oren Mangoubi; Sushant Sachdeva; Nisheeth K. Vishnoi (CoRR, 2020)

On the Computability of Continuous Maximum Entropy Distributions: Adjoint Orbits of Lie Groups. - Jonathan Leake; Nisheeth K. Vishnoi (CoRR, 2020)

A Polynomial-Time Algorithm and Applications for Matrix Sampling from Harish-Chandra-Itzykson-Zuber Densities. - Jonathan Leake; Colin S. McSwiggen; Nisheeth K. Vishnoi (CoRR, 2020)

Subdeterminant Maximization via Nonconvex Relaxations and Anti-Concentration. - Javad B. Ebrahimi; Damian Straszak; Nisheeth K. Vishnoi (SIAM J. Comput., 2020)

The Effect of the Rooney Rule on Implicit Bias in the Long Term. - L. Elisa Celis; Chris Hays; Anay Mehrotra; Nisheeth K. Vishnoi (FAccT, 2021)

FOCS 2021 Preface. - Nisheeth K. Vishnoi (FOCS, 2021)

Fair Classification with Noisy Protected Attributes: A Framework with Provable Guarantees. - L. Elisa Celis; Lingxiao Huang; Vijay Keswani; Nisheeth K. Vishnoi (ICML, 2021)

Fair Classification with Adversarial Perturbations. - L. Elisa Celis; Anay Mehrotra; Nisheeth K. Vishnoi (NeurIPS, 2021)

Coresets for Time Series Clustering. - Lingxiao Huang; K. Sudhir; Nisheeth K. Vishnoi (NeurIPS, 2021)

Sampling matrices from Harish-Chandra-Itzykson-Zuber densities with applications to Quantum inference and differential privacy. - Jonathan Leake; Colin S. McSwiggen; Nisheeth K. Vishnoi (STOC, 2021)

Greedy adversarial equilibrium: an efficient alternative to nonconvex-nonconcave min-max optimization. - Oren Mangoubi; Nisheeth K. Vishnoi (STOC, 2021)

An Introduction to Hamiltonian Monte Carlo Method for Sampling. - Nisheeth K. Vishnoi (CoRR, 2021)

Optimization and Sampling Under Continuous Symmetry: Examples and Lie Theory. - Jonathan Leake; Nisheeth K. Vishnoi (CoRR, 2021)

Sampling from Log-Concave Distributions with Infinity-Distance Guarantees and Applications to Differentially Private Optimization. - Oren Mangoubi; Nisheeth K. Vishnoi (CoRR, 2021)

Dynamic Sampling from Graphical Models. - Weiming Feng 001; Nisheeth K. Vishnoi; Yitong Yin (SIAM J. Comput., 2021)

Isolating a Vertex via Lattices: Polytopes with Totally Unimodular Faces. - Rohit Gurjar; Thomas Thierauf; Nisheeth K. Vishnoi (SIAM J. Comput., 2021)

On the Number of Circuits in Regular Matroids (with Connections to Lattices and Codes). - Rohit Gurjar; Nisheeth K. Vishnoi (SIAM J. Discret. Math., 2021)

Private Matrix Approximation and Geometry of Unitary Orbits. - Oren Mangoubi; Yikai Wu 001; Satyen Kale; Abhradeep Thakurta; Nisheeth K. Vishnoi (COLT, 2022)

Fairness for AUC via Feature Augmentation. - Hortense Fong; Vineet Kumar 006; Anay Mehrotra; Nisheeth K. Vishnoi (FAccT, 2022)

Selection in the Presence of Implicit Bias: The Advantage of Intersectional Constraints. - Anay Mehrotra; Bary S. R. Pradelski; Nisheeth K. Vishnoi (FAccT, 2022)

A Convergent and Dimension-Independent Min-Max Optimization Algorithm. - Vijay Keswani; Oren Mangoubi; Sushant Sachdeva; Nisheeth K. Vishnoi (ICML, 2022)

Sampling from Log-Concave Distributions with Infinity-Distance Guarantees. - Oren Mangoubi; Nisheeth K. Vishnoi (NeurIPS, 2022)

Re-Analyze Gauss: Bounds for Private Matrix Approximation via Dyson Brownian Motion. - Oren Mangoubi; Nisheeth K. Vishnoi (NeurIPS, 2022)

Fair Ranking with Noisy Protected Attributes. - Anay Mehrotra; Nisheeth K. Vishnoi (NeurIPS, 2022)

Faster Sampling from Log-Concave Distributions over Polytopes via a Soft-Threshold Dikin Walk. - Oren Mangoubi; Nisheeth K. Vishnoi (CoRR, 2022)

Iteratively reweighted least squares and slime mold dynamics: connection and convergence. - Damian Straszak; Nisheeth K. Vishnoi (Math. Program., 2022)

On the Computability of Continuous Maximum Entropy Distributions with Applications. - Jonathan Leake; Nisheeth K. Vishnoi (SIAM J. Comput., 2022)

Private Covariance Approximation and Eigenvalue-Gap Bounds for Complex Gaussian Perturbations. - Oren Mangoubi; Nisheeth K. Vishnoi (COLT, 2023)

Algorithms in the Presence of Biased Inputs (Invited Talk). - Nisheeth K. Vishnoi (FSTTCS, 2023)

Subset Selection Based On Multiple Rankings in the Presence of Bias: Effectiveness of Fairness Constraints for Multiwinner Voting Score Functions. - Niclas Boehmer; L. Elisa Celis; Lingxiao Huang; Anay Mehrotra; Nisheeth K. Vishnoi (ICML, 2023)

Bias in Evaluation Processes: An Optimization-Based Model. - L. Elisa Celis; Amit Kumar 001; Anay Mehrotra; Nisheeth K. Vishnoi (NeurIPS, 2023)

Sampling from Structured Log-Concave Distributions via a Soft-Threshold Dikin Walk. - Oren Mangoubi; Nisheeth K. Vishnoi (NeurIPS, 2023)

Maximizing Submodular Functions for Recommendation in the Presence of Biases. - Anay Mehrotra; Nisheeth K. Vishnoi (WWW, 2023)

On the works of Avi Wigderson. - Boaz Barak; Yael Kalai; Ran Raz; Salil P. Vadhan; Nisheeth K. Vishnoi (CoRR, 2023)

Faster Sampling from Log-Concave Densities over Polytopes via Efficient Linear Solvers. - Oren Mangoubi; Nisheeth K. Vishnoi (ICLR, 2024)

Centralized Selection with Preferences in the Presence of Biases. - L. Elisa Celis; Amit Kumar 001; Nisheeth K. Vishnoi; Andrew Xu (ICML, 2024)

Private Low-Rank Approximation for Covariance Matrices, Dyson Brownian Motion, and Eigenvalue-Gap Bounds for Gaussian Perturbations. - Oren Mangoubi; Nisheeth K. Vishnoi (J. ACM, 2025)

Efficient Diffusion Models for Symmetric Manifolds. - Oren Mangoubi; Neil He; Nisheeth K. Vishnoi (CoRR, 2025)

A Mathematical Framework for AI-Human Integration in Work. - L. Elisa Celis; Lingxiao Huang; Nisheeth K. Vishnoi (CoRR, 2025)