| 2025 | ICML | A Mathematical Framework for AI-Human Integration in Work. | L. Elisa Celis, Lingxiao Huang, Nisheeth K. Vishnoi |
| 2025 | ICML | Efficient Diffusion Models for Symmetric Manifolds. | Oren Mangoubi, Neil He, Nisheeth K. Vishnoi |
| 2024 | ICLR | Faster Sampling from Log-Concave Densities over Polytopes via Efficient Linear Solvers. | Oren Mangoubi, Nisheeth K. Vishnoi |
| 2024 | ICML | Centralized Selection with Preferences in the Presence of Biases. | L. Elisa Celis, Amit Kumar, Nisheeth K. Vishnoi, Andrew Xu |
| 2023 | COLT | Private Covariance Approximation and Eigenvalue-Gap Bounds for Complex Gaussian Perturbations. | Oren Mangoubi, Nisheeth K. Vishnoi |
| 2023 | ICML | 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 |
| 2023 | WWW | Maximizing Submodular Functions for Recommendation in the Presence of Biases. | Anay Mehrotra, Nisheeth K. Vishnoi |
| 2022 | COLT | Private Matrix Approximation and Geometry of Unitary Orbits. | Oren Mangoubi, Yikai Wu, Satyen Kale, Abhradeep Thakurta, Nisheeth K. Vishnoi |
| 2022 | ICML | A Convergent and Dimension-Independent Min-Max Optimization Algorithm. | Vijay Keswani, Oren Mangoubi, Sushant Sachdeva, Nisheeth K. Vishnoi |
| 2021 | FOCS | FOCS 2021 Preface. | Nisheeth K. Vishnoi |
| 2021 | ICML | Fair Classification with Noisy Protected Attributes: A Framework with Provable Guarantees. | L. Elisa Celis, Lingxiao Huang, Vijay Keswani, Nisheeth K. Vishnoi |
| 2021 | STOC | Sampling matrices from Harish-Chandra-Itzykson-Zuber densities with applications to Quantum inference and differential privacy. | Jonathan Leake, Colin S. McSwiggen, Nisheeth K. Vishnoi |
| 2021 | STOC | Greedy adversarial equilibrium: an efficient alternative to nonconvex-nonconcave min-max optimization. | Oren Mangoubi, Nisheeth K. Vishnoi |
| 2020 | ICML | Data preprocessing to mitigate bias: A maximum entropy based approach. | L. Elisa Celis, Vijay Keswani, Nisheeth K. Vishnoi |
| 2020 | STOC | Coresets for clustering in Euclidean spaces: importance sampling is nearly optimal. | Lingxiao Huang, Nisheeth K. Vishnoi |
| 2020 | STOC | On the computability of continuous maximum entropy distributions with applications. | Jonathan Leake, Nisheeth K. Vishnoi |
| 2019 | COLT | Nonconvex sampling with the Metropolis-adjusted Langevin algorithm. | Oren Mangoubi, Nisheeth K. Vishnoi |
| 2019 | COLT | Maximum Entropy Distributions: Bit Complexity and Stability. | Damian Straszak, Nisheeth K. Vishnoi |
| 2019 | FOCS | Faster Polytope Rounding, Sampling, and Volume Computation via a Sub-Linear Ball Walk. | Oren Mangoubi, Nisheeth K. Vishnoi |
| 2019 | ICML | Stable and Fair Classification. | Lingxiao Huang, Nisheeth K. Vishnoi |
| 2019 | ICML | Toward Controlling Discrimination in Online Ad Auctions. | L. Elisa Celis, Anay Mehrotra, Nisheeth K. Vishnoi |
| 2019 | SODA | On the Number of Circuits in Regular Matroids (with Connections to Lattices and Codes). | Rohit Gurjar, Nisheeth K. Vishnoi |
| 2019 | STOC | Dynamic sampling from graphical models. | Weiming Feng, Nisheeth K. Vishnoi, Yitong Yin |
| 2018 | COLT | Convex Optimization with Unbounded Nonconvex Oracles using Simulated Annealing. | Oren Mangoubi, Nisheeth K. Vishnoi |
| 2018 | ICALP | Ranking with Fairness Constraints. | L. Elisa Celis, Damian Straszak, Nisheeth K. Vishnoi |
| 2018 | ICALP | Isolating a Vertex via Lattices: Polytopes with Totally Unimodular Faces. | Rohit Gurjar, Thomas Thierauf, Nisheeth K. Vishnoi |
| 2018 | ICML | Fair and Diverse DPP-Based Data Summarization. | L. Elisa Celis, Vijay Keswani, Damian Straszak, Amit Deshpande, Tarun Kathuria, Nisheeth K. Vishnoi |
| 2018 | IJCAI | Multiwinner Voting with Fairness Constraints. | L. Elisa Celis, Lingxiao Huang, Nisheeth K. Vishnoi |
| 2018 | IJCAI | Balanced News Using Constrained Bandit-based Personalization. | Sayash Kapoor, Vijay Keswani, Nisheeth K. Vishnoi, L. Elisa Celis |
| 2017 | FOCS | Subdeterminant Maximization via Nonconvex Relaxations and Anti-Concentration. | Javad B. Ebrahimi, Damian Straszak, Nisheeth K. Vishnoi |
| 2017 | PODC | A Distributed Learning Dynamics in Social Groups. | L. Elisa Celis, Peter M. Krafft, Nisheeth K. Vishnoi |
| 2017 | STOC | Real stable polynomials and matroids: optimization and counting. | Damian Straszak, Nisheeth K. Vishnoi |
| 2016 | ICALP | Mixing Time of Markov Chains, Dynamical Systems and Evolution. | Ioannis Panageas, Nisheeth K. Vishnoi |
| 2016 | SODA | Evolutionary Dynamics in Finite Populations Mix Rapidly. | Ioannis Panageas, Piyush Srivastava, Nisheeth K. Vishnoi |
| 2016 | SODA | Natural Algorithms for Flow Problems. | Damian Straszak, Nisheeth K. Vishnoi |
| 2015 | SODA | The Speed of Evolution. | Nisheeth K. Vishnoi |
| 2014 | STOC | Entropy, optimization and counting. | Mohit Singh, Nisheeth K. Vishnoi |
| 2013 | SODA | Towards Polynomial Simplex-Like Algorithms for Market Equlibria. | Jugal Garg, Ruta Mehta, Milind A. Sohoni, Nisheeth K. Vishnoi |
| 2012 | FOCS | A Permanent Approach to the Traveling Salesman Problem. | Nisheeth K. Vishnoi |
| 2012 | STOC | 2 | Subhash Khot, Preyas Popat, Nisheeth K. Vishnoi |
| 2012 | STOC | Approximating the exponential, the lanczos method and an ( | Lorenzo Orecchia, Sushant Sachdeva, Nisheeth K. Vishnoi |
| 2011 | CVPR | Biased normalized cuts. | Subhransu Maji, Nisheeth K. Vishnoi, Jitendra Malik |
| 2011 | SODA | Algorithms and Hardness for Subspace Approximation. | Amit Deshpande, Madhur Tulsiani, Nisheeth K. Vishnoi |
| 2011 | SODA | On LP-Based Approximability for Strict CSPs. | Amit Kumar, Rajsekar Manokaran, Madhur Tulsiani, Nisheeth K. Vishnoi |
| 2011 | SODA | Towards an SDP-based Approach to Spectral Methods: A Nearly-Linear-Time Algorithm for Graph Partitioning and Decomposition. | Lorenzo Orecchia, Nisheeth K. Vishnoi |
| 2008 | STOC | Unique games on expanding constraint graphs are easy: extended abstract. | Sanjeev Arora, Subhash Khot, Alexandra Kolla, David Steurer, Madhur Tulsiani, Nisheeth K. Vishnoi |
| 2008 | STOC | On partitioning graphs via single commodity flows. | Lorenzo Orecchia, Leonard J. Schulman, Umesh V. Vazirani, Nisheeth K. Vishnoi |
| 2007 | HiPC | The Impact of Noise on the Scaling of Collectives: The Nearest Neighbor Model [Extended Abstract]. | Nisheeth K. Vishnoi |
| 2006 | STOC | Integrality gaps for sparsest cut and minimum linear arrangement problems. | Nikhil R. Devanur, Subhash Khot, Rishi Saket, Nisheeth K. Vishnoi |
| 2005 | FOCS | Hardness of Approximating the Closest Vector Problem with Pre-Processing. | Mikhail Alekhnovich, Subhash Khot, Guy Kindler, Nisheeth K. Vishnoi |
| 2005 | FOCS | The Unique Games Conjecture, Integrality Gap for Cut Problems and Embeddability of Negative Type Metrics into l | Subhash Khot, Nisheeth K. Vishnoi |
| 2005 | HiPC | The Impact of Noise on the Scaling of Collectives: A Theoretical Approach. | Saurabh Agarwal, Rahul Garg, Nisheeth K. Vishnoi |
| 2003 | SODA | Deterministic identity testing for multivariate polynomials. | Richard J. Lipton, Nisheeth K. Vishnoi |
| 2002 | SODA | Caching with expiration times. | Parikshit Gopalan, Howard J. Karloff, Aranyak Mehta, Milena Mihail, Nisheeth K. Vishnoi |