PUBLICATIONS
Books, Monographs and Surveys
Optimization and Sampling Under Continuous Symmetry: Examples and Lie Theory. [arxiv]
Jonathan Leake and Nisheeth K. Vishnoi
An Introduction to Hamiltonian Monte Carlo Method for Sampling. [arxiv]
Nisheeth K. Vishnoi
The Dynamics of Lagrange and Hamilton. [pdf]
Nisheeth K. Vishnoi
Geodesic Convex Optimization: Differentiation on Manifolds, Geodesics, and Convexity. [arXiv]
Nisheeth K. Vishnoi
Algorithms for Convex Optimization. [book]
Nisheeth K. Vishnoi
Cambridge University Press, 2021.
Faster Algorithms via Approximation Theory. [pdf]
Sushant Sachdeva, Nisheeth K. Vishnoi
Foundations and Trends in Theoretical Computer Science, Volume 9, Issue 2, 2013.
Lx=b (Laplacian Solvers and Their Algorithmic Applications)
Nisheeth K. Vishnoi
Foundations and Trends in Theoretical Computer Science, Volume 8, Issue 1-2, 2012.
Zeros of Polynomials and their Applications to Theory: A Primer. [pdf]
Nisheeth K. Vishnoi
Evolution without sex, drugs and Boolean functions. [pdf]
Nisheeth K. Vishnoi
All Papers (in reverse chronological order)
Faster Sampling from Log-Concave Distributions over Polytopes via a Soft-Threshold Dikin Walk. [arxiv]
Oren Mangoubi, Nisheeth K. Vishnoi
On the Computability of Continuous Maximum Entropy Distributions: Adjoint Orbits of Lie Groups. [arxiv]
Jonathan Leake, Nisheeth K. Vishnoi
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.
Sampling from Log-Concave Distributions with Infinity-Distance Guarantees. [arxiv]
Oren Mangoubi, Nisheeth K. Vishnoi
NeurIPS 2022.
Iteratively reweighted least squares and slime mold dynamics: connection and convergence. [pdf]
Damian Straszak, Nisheeth K. Vishnoi
Mathematical Programming, Series A, 2022.
A Convergent and Dimension-Independent First-Order Algorithm for Min-Max Optimization. [arxiv]
Vijay Keswani, Oren Mangoubi, Sushant Sachdeva, Nisheeth K. Vishnoi
ICML 2022.
Private Matrix Approximation and Geometry of Unitary Orbits. [arxiv]
Oren Mangoubi, Yikai Wu, Satyen Kale, Abhradeep Thakurta, Nisheeth K. Vishnoi
COLT 2022.
Selection in the Presence of Implicit Bias: The Advantage of Intersectional Constraints. [arxiv]
Anay Mehrotra, Bary R. Pradleski, Nisheeth K. Vishnoi
ACM FAccT 2022.
Fairness for AUC via Feature Augmentation. [arxiv]
Hortense Fong, Vineet Kumar, Anay Mehrotra, Nisheeth K. Vishnoi
ACM FAccT 2022.
Coresets for Time Series Clustering. [arxiv]
K. Sudhir, Lingxiao Huang, Nisheeth K. Vishnoi
NeurIPS 2021.
Fair Classification with Adversarial Perturbations. [arxiv]
L. Elisa Celis, Anay Mehrotra, Nisheeth K. Vishnoi
NeurIPS 2021.
Fair Classification with Noisy Protected Attributes: A Framework with Provable Guarantees. [arxiv]
L. Elisa Celis, Vijay Keswani, Lingxiao Huang, Nisheeth K. Vishnoi
ICML 2021.
On the Number of Circuits in Regular Matroids (with Connections to Lattices and Codes). [arXiv]
Rohit Gurjar, Nisheeth K. Vishnoi
SIAM J. Discrete Math, 2021.
Isolating a Vertex via Lattices: Polytopes with Totally Unimodular Faces.
[journal]
Rohit Gurjar, Thomas Thierauf, Nisheeth K. Vishnoi
SIAM J. Computing, 2021.
Dynamic Sampling from Graphical Models.
[journal]
Weiming Feng, Nisheeth K. Vishnoi, Yitong Yin
SIAM J. Computing, 2021.
Sampling Matrices from Harish-Chandra--Itzykson-Zuber Densities with Application to Quantum Inference and Differential Privacy. [conf] [arxiv]
Jonathan Leake, Colin McSwiggen, Nisheeth K. Vishnoi
STOC 2021.
Greedy Adversarial Equilibrium: An Efficient Alternative to Nonconvex-Nonconcave Min-Max Optimization. [arxiv]
Oren Mangoubi, Nisheeth K. Vishnoi
STOC 2021.
The Effect of the Rooney Rule on Implicit Bias in the Long Term. [arxiv]
L. Elisa Celis, Chris Hays, Anay Mehrotra, Nisheeth K. Vishnoi
ACM FAccT 2021.
Subdeterminant maximization via nonconvex relaxations and anticoncentration. [journal]
Javad Ebrahimi, Damian Straszak, Nisheeth K. Vishnoi
SIAM J. Computing, 2020.
Coresets for Regressions with Panel Data. [arxiv]
Lingxiao Huang, K. Sudhir, Nisheeth K. Vishnoi
NeurIPS 2020.
Data preprocessing to mitigate bias: A maximum entropy based approach. [pdf]
L. Elisa Celis, Vijay Keswani, Nisheeth K. Vishnoi
ICML 2020.
On the Computability of Continuous Maximum Entropy
Distributions with Applications. [arxiv]
Jonathan Leake, Nisheeth K. Vishnoi
STOC 2020.
Coresets for Clustering in Euclidean Spaces: Importance Sampling is Nearly Optimal. [arxiv]
Lingxiao Huang, Nisheeth K. Vishnoi
STOC 2020.
Interventions for Ranking in the Presence of Implicit Bias. [arxiv]
L. Elisa Celis, Anay Mehrotra, Nisheeth K. Vishnoi
ACM FAT* 2020.
Coresets for clustering with fairness constraints. [arxiv]
Lingxiao Huang, Shaofeng Jiang, Nisheeth K. Vishnoi
NeurIPS 2019.
Online Sampling from Log-Concave Distributions. [arxiv]
Holden Lee, Oren Mangoubi, Nisheeth K. Vishnoi
NeurIPS 2019.
Faster algorithms for polytope rounding, sampling, and volume computation via a sublinear "Ball Walk''. [arxiv]
Oren Mangoubi, Nisheeth K. Vishnoi
FOCS 2019.
Towards controlling discrimination in online ad auctions. [arxiv]
L. Elisa Celis, Anay Mehrotra, Nisheeth K. Vishnoi
ICML 2019.
Stable and Fair Classification. [arxiv]
Lingxiao Huang, Nisheeth K. Vishnoi
ICML 2019.
Nonconvex Sampling with the Metropolis-Adjusted Langevin Algorithm. [arxiv]
Oren Mangoubi, Nisheeth K. Vishnoi
COLT 2019.
Maximum entropy distributions: Bit complexity and stability. [arXiv]
Damian Straszak, Nisheeth K. Vishnoi
COLT 2019.
Dynamic Sampling from Graphical Models. [arxiv]
Weiming Feng, Yitong Yin, Nisheeth K. Vishnoi
STOC 2019.
Isolating a Matching When Your Coins Go Missing.
Nisheeth K. Vishnoi
Communications of the ACM, 2019.
Invited Technical perspective.
A Dashboard for Controlling Polarization in Personalization.
L. Elisa Celis, Sayash Kapoor, Farnood Salehi, Vijay Keswani, Nisheeth K. Vishnoi
AI Communications, 2019.
Invited publication.
Belief Propagation, Bethe Approximation and Polynomials. [arxiv]
Damian Straszak, Nisheeth K. Vishnoi
IEEE Transactions on Information Theory, 2019.
Classification with Fairness Constraints: A Meta-Algorithm with Provable Guarantees. [arXiv]
L. Elisa Celis, Lingxiao Huang, Vijay Keswani, Nisheeth K. Vishnoi
ACM FAT* 2019.
Controlling polarization in personalization. [pdf]
L. Elisa Celis, Sayash Kapoor, Farnood Salehi, Nisheeth K. Vishnoi
ACM FAT* 2019.
Awarded the Best Technical Paper at ACM FAT* 2019.
On the Number of Circuits in Regular Matroids (with Connections to Lattices and Codes). [arXiv]
Rohit Gurjar, Nisheeth K. Vishnoi
SODA 2019.
Dimensionally tight running time bounds for second-order Hamiltonian
Monte Carlo. [arXiv]
Oren Mangoubi, Nisheeth K. Vishnoi
NeurIPS 2018.
On geodesically convex formulations for the Brascamp-Lieb constant. [arXiv]
Suvrit Sra, Nisheeth K. Vishnoi, Ozan Yildiz
APPROX 2018.
Fair and Diverse Data Summarization. [arXiv]
L. Elisa Celis, Vijay Keswani, Damian Straszak, Amit Deshpande, Tarun
Kathuria, Nisheeth K. Vishnoi
ICML 2018.
Convex optimization with nonconvex oracles. [arXiv]
Oren Mangoubi, Nisheeth K. Vishnoi
COLT 2018.
Balanced News Using Constrained Bandit-based Personalization. [Demo Website] [Demo Video]
Sayash Kapoor, Vijay Keswani, Nisheeth K. Vishnoi, L. Elisa Celis
IJCAI-ECAI (Demo track) 2018.
Multiwinner voting with fairness constraints. [arxiv]
L. Elisa Celis, Lingxiao Huang, Nisheeth K. Vishnoi
IJCAI-ECAI 2018.
Isolating a vertex via lattices: Polytopes with totally unimodular faces. [arxiv]
Rohit Gurjar, Thomas Thierauf, Nisheeth K. Vishnoi
ICALP 2018.
Ranking with Fairness Constraints. [arxiv]
L. Elisa Celis, Damian Straszak, Nisheeth K. Vishnoi
ICALP 2018.
A dynamics for advertising on networks. [pdf]
L. Elisa Celis, Mina Dalirrooyfard, Nisheeth K. Vishnoi
WINE 2017.
Belief Propagation, Bethe Approximation and Polynomials. [arxiv]
Damian Straszak, Nisheeth K. Vishnoi
Invited to ALLERTON 2017.
Subdeterminant maximization via nonconvex relaxations and anticoncentration. [arXiv]
Javad Ebrahimi, Damian Straszak, Nisheeth K. Vishnoi
FOCS 2017.
Fair Personalization. [arxiv]
L. Elisa Celis, Nisheeth K. Vishnoi
Fairness, Accountability and Transparency in ML, 2017.
On the Complexity of Constrained Determinantal Point Processes. [arxiv]
L. Elisa Celis, Amit Deshpande, Tarun Kathuria, Damian Straszak, Nisheeth K. Vishnoi
RANDOM 2017.
A distributed learning dynamics in social groups. [arxiv]
L. Elisa Celis, Peter M. Krafft, Nisheeth K. Vishnoi
PODC 2017.
Real stable polynomials and matroids: optimization and counting. [arxiv]
Damian Straszak, Nisheeth K. Vishnoi
STOC 2017.
IRLS and Slime Mold: Equivalence and Convergence. [arXiv]
Damian Straszak, Nisheeth K. Vishnoi
Invited to ITCS 2017.
Random walks in polytopes and negative dependence
Yuval Peres, Mohit Singh, Nisheeth K. Vishnoi
ITCS 2017.
How to be fair and diverse? [arxiv]
L. Elisa Celis, Amit Deshpande, Tarun Kathuria, Nisheeth K. Vishnoi
Fairness, Accountability and Transparency in ML, 2016 (Selected for presentation).
The Mixing time of the Dikin walk in polytopes -- a simple proof. [journal]
Sushant Sachdeva, Nisheeth K. Vishnoi
Operations Research Letters 2016.
Mixing time of Markov chains, dynamical systems and evolution. [pdf]
Ioannis Panageas, Nisheeth K. Vishnoi
ICALP 2016.
On the computational complexity of limit cycles in dynamical systems. [arxiv]
Christos H. Papadimitriou, Nisheeth K. Vishnoi
ITCS 2016.
On a natural dynamics for linear programming. [arxiv]
Damian Straszak, Nisheeth K. Vishnoi
ITCS 2016.
Natural algorithms for flow problems. [journal]
Damian Straszak, Nisheeth K. Vishnoi
SODA 2016.
Evolutionary dynamics in finite populations mix rapidly. [pdf]
Ioannis Panageas, Piyush Srivastava, Nisheeth K. Vishnoi
SODA 2016.
The unique games conjecture, integrality gap for cut problems and the embeddability of negative type metrics into l_1. [journal]
Subhash Khot, Nisheeth K. Vishnoi
Journal of the ACM, 62(1), 2015.
The speed of evolution. [pdf]
Nisheeth K. Vishnoi
SODA 2015.
Entropy, optimization and counting. [arxiv]
Mohit Singh, Nisheeth K. Vishnoi
STOC 2014.
Almost polynomial factor hardness for Closest Vector Problem with Preprocessing. [journal]
Subhash Khot, Preyas Popat, Nisheeth K. Vishnoi
SIAM Journal of Computing, 43(3), 1184–1205, 2014.
Towards polynomial simlpex-like algorithms for market equilibria. [pdf]
Jugal Garg, Ruta Mehta, Milind Sohoni, Nisheeth K. Vishnoi
SODA 2013.
Making evolution rigorous- the error threshold. [pdf]
Nisheeth K. Vishnoi
ITCS 2013.
A finite population model of molecular evolution: theory and computation. [arxiv]
Narendra M. Dixit, Piyush Srivastava, Nisheeth K. Vishnoi
In Journal of Computational Biology, 19(10): 1176-1202, 2012.
Stochastic simulations suggest that HIV-1 survives close to its error threshold. [pdf]
Kushal Tripathi, Rajesh Balagam, Nisheeth K. Vishnoi, Narendra Dixit
In PLoS Computational Biology 8(9): e1002684, 2012.
A permanent approach to the traveling salesman problem. [conf]
Nisheeth K. Vishnoi
FOCS 2012.
A Local spectral method for graphs: with applications to improving graph partitions and exploring data graphs locally. [journal]
Michael W. Mahoney, Lorenzo Orecchia, Nisheeth K. Vishnoi
In Journal of Machine Learning Research (JMLR),Vol 13., pp. 2339-2365, 2012.
2^{\log^{1-\eps} n} hardness for closest vector problem with preprocessing. [arxiv]
Subhash Khot, Preyas Popat, Nisheeth K. Vishnoi
STOC 2012.
Approximating the exponential, the lanczos method and an \tilde{O}(m)-time spectral algorithm for balanced separator. [conf] [arxiv]
Lorenzo Orecchia, Sushant Sachdeva, Nisheeth K. Vishnoi
STOC 2012.
Hardness of approximating the closest vector problem with pre-processing. [journal]
Misha Alekhnovich, Subhash Khot, Guy Kindler, Nisheeth K. Vishnoi
Computational Complexity, 2012
Biased normalized cuts. [pdf]
Subhransu Maji, Nisheeth K. Vishnoi, Jitendra Malik
IEEE Computer Vision and Pattern Recognition, 2011.
Towards a SDP-based approach to spectral methods: A nearly-linear time algorithm for graph partitioning and decomposition. [pdf]
Lorenzo Orecchia, Nisheeth K. Vishnoi
ACM-SIAM Symposium on Discrete Algorithms, 2011.
On LP-based approximability for strict CSPs. [pdf]
Amit Kumar, Rajsekar Manokaran, Madhur Tulsiani, Nisheeth K. Vishnoi
ACM-SIAM Symposium on Discrete Algorithms, 2011.
Algorithms and hardness for subspace approximation. [pdf]
Amit Deshpande, Madhur Tulsiani, Nisheeth K. Vishnoi
ACM-SIAM Symposium on Discrete Algorithms, 2011.
Improved algorithm for degree bounded survivable network design problem. [pdf]
Anand Louis, Nisheeth K. Vishnoi
12th Scandinavian Symposium and Workshops on Algorithm Theory, 2010.
On the Fourier spectrum of symmetric Boolean functions.
[pdf]
Mihail N. Kolountzakis, Richard J. Lipton, Evangelos Markakis, Aranyak Mehta, Nisheeth K. Vishnoi
Combinatorica, Vol. 29, No. 3, pp. 363-387, 2009.
Deterministically testing sparse polynomial identities of unbounded degree. [pdf]
Markus Blaser, Moritz Hardt, Richard J. Lipton, Nisheeth K. Vishnoi
Information Processing Letters 109(3): 187-192, 2009.
Unique games on expanding constraint graphs are easy. (Extended Abstract) [ACM Digital Library]
Sanjeev Arora, Subhash A. Khot, Alexandra Kolla, David Steurer, Madhur Tulsiani, Nisheeth K. Vishnoi
In the 40th ACM Symposium on Theory of Computing, 2008.
On partitioning graphs via single commodity flows. (Extended Abstract) [pdf]
Lorenzo Orecchia, Leonard Schulman, Umesh V. Vazirani, Nisheeth K. Vishnoi
In the 40th ACM Symposium on Theory of Computing, 2008.
The impact of noise on the scaling of collectives: The nearest neighbor model. [pdf]
Nisheeth K. Vishnoi
In the 14th International Conference on High Performance Computing, 2007.
On the computational aspect of risk in playing non-cooperative games. [pdf]
Deeparnab Chakrabarty, Subhash A. Khot, Richard J. Lipton, Nisheeth K. Vishnoi
In the 18th International Conference on Game Theory, Stony Brook, 2007.
Integrality gaps for sparsest cut and minimum linear arrangement problems. (Extended abstract) [pdf]
Nikhil Devanur, Subhash Khot, Rishi Saket, Nisheeth K. Vishnoi
In the 38th ACM Symposium on Theory of Computing, 2006.
The impact of noise on the scaling of collectives: A theoretical approach. [pdf]
Saurabh Agarwal, Rahul Garg, Nisheeth K. Vishnoi
In the 14th International Conference on High Performance Computing, 2005.
The unique games conjecture, integrality gap for cut problems and the embeddability of negative type metrics into l_1. [Extended abstract- pdf] [Full version- arxiv]
Subhash Khot, Nisheeth K. Vishnoi
In the 46th Annual IEEE Symposium on Foundations of Computer Science, 2005.
Awarded the Best Paper Award at IEEE FOCS 2005.
Awarded the IBM Research Pat Goldberg Memorial Award for 2005.
Hardness of approximating the closest vector problem with pre-processing. (Extended abstract) [pdf]
Misha Alekhnovich, Subhash Khot, Guy Kindler, Nisheeth K. Vishnoi
In the 46th Annual IEEE Symposium on Foundations of Computer Science, 2005.
Caching with expiration times for internet applications. [pdf]
Parikshit Gopalan, Howard Karloff, Aranyak Mehta, Milena Mihail, Nisheeth K. Vishnoi
In Internet Mathematics, 2005.
The impact of noise on the scaling of collectives: A theoretical approach. (Extended abstract) [pdf]
Saurabh Agarwal, Rahul Garg, Nisheeth K. Vishnoi
In the 12th International Conference on High Performance Computing, 2005.
On the fourier spectrum of symmetric boolean functions with applications to learning symmetric juntas. [pdf]
Richard J. Lipton, Evangelos Markakis, Aranyak Mehta, Nisheeth K. Vishnoi
In the 20th IEEE Conference on Computational Complexity, 2005.
On the complexity of Hilbert's 17th problem. [pdf]
Nikhil R. Devanur, Richard J. Lipton, Nisheeth K. Vishnoi
In Foundations of Software Technology and Theoretical Computer Science, 24th International
Conference, Chennai, India, 2004.
A Generalization of the Characteristic Polynomial of a Graph. [pdf]
Richard J. Lipton, Nisheeth K. Vishnoi
In 35th Southeastern International Conference on Combinatorics, Graph Theory
and Computing, Boca Raton 2004.
Deterministic identity testing for multivariate polynomials. [pdf]
Richard J. Lipton, Nisheeth K. Vishnoi
In 14th ACM-SIAM Symposium on Discrete Algorithms, 2003.
Non uniform random walks. [pdf]
Nisheeth K. Vishnoi
In Discrete Mathematics and Theoretical Computer Science, vol. AC (2003)
Discrete Random Walks 2003. Editors: Cyril Banderier and Christian Krattenthaler.
Who's �The Weakest Link�? [pdf]
Nikhil Devanur, Richard J. Lipton, Nisheeth K. Vishnoi
In 2nd Symposium on Stochastic Algorithms, Foundations and Applications, 2003.
On generating graphs with prescribed degree sequences for complex network modeling applications. [pdf]
Milena Mihail, Nisheeth K. Vishnoi
In Approximation and Randomized Algorithms for Communication Networks, 2002.
Caching with expiration times. [pdf]
Parikshit Gopalan, Howard Karloff, Aranyak Mehta, Milena Mihail, Nisheeth K. Vishnoi
In the 13th ACM-SIAM ACM Symposium on Discrete Algorithms, 2002.
An algebraic proof of Alon's Combinatorial Nullstellensatz. [pdf]
Nisheeth K. Vishnoi
In Congressus Numerantium, vol. 152, 89-91, 2001.
Manuscripts [Available on Request]
Matrix inversion is as easy as exponentiation. [arxiv]
Sushant Sachdeva, Nisheeth K. Vishnoi
Connections between Unique Games and Multicut. [ECCC]
David Steurer, Nisheeth K. Vishnoi
ECCC Technical Report TR09-125.
On a cut-matching game for expansion. [Tech Report]
Rohit M. Khandekar, Subhash A. Khot, Lorenzo Orecchia, Nisheeth K. Vishnoi
University of California, Berkeley Technical Report No. UCB/EECS-2007-177.
On the hardness of minimum linear arrangement.
Nikhil R. Devanur, Subhash A. Khot, Rishi Saket, Nisheeth K. Vishnoi
Manuscript, 2005.
Hardness of lattice problems in l_p norm.
Subhash A. Khot, Nisheeth K. Vishnoi
Manuscript, 2003.
GCD of p-1,q-1 for random p,q. [Tech Report]
Nisheeth K. Vishnoi
GIT-CC Technical Report 03-52.
The geometry of matrix rigidity. [Tech Report]
Joseph M. Landsberg, Jacob Taylor, Nisheeth K. Vishnoi
GIT-CC Technical Report 03-54.