| 2026 | STOC | Efficient Calibration for Decision Making. | Parikshit Gopalan, Konstantinos Stavropoulos, Kunal Talwar, Pranay Tankala |
| 2025 | ICLR | Adaptive Batch Size for Privately Finding Second-Order Stationary Points. | Daogao Liu, Kunal Talwar |
| 2025 | ICML | Faster Rates for Private Adversarial Bandits. | Hilal Asi, Vinod Raman, Kunal Talwar |
| 2025 | ICML | Local Pan-privacy for Federated Analytics. | Vitaly Feldman, Audra McMillan, Guy N. Rothblum, Kunal Talwar |
| 2025 | ICML | Improved Sample Complexity for Private Nonsmooth Nonconvex Optimization. | Guy Kornowski, Daogao Liu, Kunal Talwar |
| 2025 | STOC | Fingerprinting Codes Meet Geometry: Improved Lower Bounds for Private Query Release and Adaptive Data Analysis. | Xin Lyu, Kunal Talwar |
| 2024 | CCS | Samplable Anonymous Aggregation for Private Federated Data Analysis. | Kunal Talwar, Shan Wang, Audra McMillan, Vitaly Feldman, Pansy Bansal, Bailey Basile, ine Cahill, Yi Sheng Chan, Mike Chatzidakis, Junye Chen, Oliver R. A. Chick, Mona Chitnis, Suman Ganta, Yusuf Goren, Filip Granqvist, Kristine Guo, Frederic Jacobs, Omid Javidbakht, Albert Liu, Richard Low, Dan Mascenik, Steve Myers, David Park, Wonhee Park, Gianni Parsa, Tommy Pauly, Christian Priebe, Rehan Rishi, Guy N. Rothblum, Congzheng Song, Linmao Song, Karl Tarbe, Sebastian Vogt, Shundong Zhou, Vojta Jina, Michael Scaria, Luke Winstrom |
| 2024 | ICML | Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages. | Hilal Asi, Vitaly Feldman, Jelani Nelson, Huy L. Nguyen, Kunal Talwar, Samson Zhou |
| 2023 | COLT | Resolving the Mixing Time of the Langevin Algorithm to its Stationary Distribution for Log-Concave Sampling. | Jason M. Altschuler, Kunal Talwar |
| 2023 | COLT | Private Online Prediction from Experts: Separations and Faster Rates. | Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar |
| 2023 | ICML | Near-Optimal Algorithms for Private Online Optimization in the Realizable Regime. | Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar |
| 2023 | SODA | Stronger Privacy Amplification by Shuffling for Renyi and Approximate Differential Privacy. | Vitaly Feldman, Audra McMillan, Kunal Talwar |
| 2022 | ICML | Optimal Algorithms for Mean Estimation under Local Differential Privacy. | Hilal Asi, Vitaly Feldman, Kunal Talwar |
| 2022 | ICML | Private frequency estimation via projective geometry. | Vitaly Feldman, Jelani Nelson, Huy L. Nguyen, Kunal Talwar |
| 2022 | ICML | Practical Almost-Linear-Time Approximation Algorithms for Hybrid and Overlapping Graph Clustering. | Lorenzo Orecchia, Konstantinos Ameranis, Charalampos E. Tsourakakis, Kunal Talwar |
| 2021 | FOCS | Hiding Among the Clones: A Simple and Nearly Optimal Analysis of Privacy Amplification by Shuffling. | Vitaly Feldman, Audra McMillan, Kunal Talwar |
| 2021 | ICML | Private Adaptive Gradient Methods for Convex Optimization. | Hilal Asi, John C. Duchi, Alireza Fallah, Omid Javidbakht, Kunal Talwar |
| 2021 | ICML | Private Stochastic Convex Optimization: Optimal Rates in L1 Geometry. | Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar |
| 2021 | ICML | Lossless Compression of Efficient Private Local Randomizers. | Vitaly Feldman, Kunal Talwar |
| 2021 | ICML | Characterizing Structural Regularities of Labeled Data in Overparameterized Models. | Ziheng Jiang, Chiyuan Zhang, Kunal Talwar, Michael C. Mozer |
| 2021 | STOC | When is memorization of irrelevant training data necessary for high-accuracy learning? | Gavin Brown, Mark Bun, Vitaly Feldman, Adam D. Smith, Kunal Talwar |
| 2020 | STOC | Private stochastic convex optimization: optimal rates in linear time. | Vitaly Feldman, Tomer Koren, Kunal Talwar |
| 2019 | COLT | Better Algorithms for Stochastic Bandits with Adversarial Corruptions. | Anupam Gupta, Tomer Koren, Kunal Talwar |
| 2019 | ICML | Semi-Cyclic Stochastic Gradient Descent. | Hubert Eichner, Tomer Koren, Brendan McMahan, Nathan Srebro, Kunal Talwar |
| 2019 | SODA | Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity. | lfar Erlingsson, Vitaly Feldman, Ilya Mironov, Ananth Raghunathan, Kunal Talwar, Abhradeep Thakurta |
| 2019 | STOC | Private selection from private candidates. | Jingcheng Liu, Kunal Talwar |
| 2018 | COLT | Online learning over a finite action set with limited switching. | Jason M. Altschuler, Kunal Talwar |
| 2018 | FOCS | Balancing Vectors in Any Norm. | Daniel Dadush, Aleksandar Nikolov, Kunal Talwar, Nicole Tomczak-Jaegermann |
| 2018 | FOCS | Privacy Amplification by Iteration. | Vitaly Feldman, Ilya Mironov, Kunal Talwar, Abhradeep Thakurta |
| 2018 | ICLR | Learning Differentially Private Recurrent Language Models. | H. Brendan McMahan, Daniel Ramage, Kunal Talwar, Li Zhang |
| 2018 | ICLR | Scalable Private Learning with PATE. | Nicolas Papernot, Shuang Song, Ilya Mironov, Ananth Raghunathan, Kunal Talwar, lfar Erlingsson |
| 2018 | ICML | Online Linear Quadratic Control. | Alon Cohen, Avinatan Hassidim, Tomer Koren, Nevena Lazic, Yishay Mansour, Kunal Talwar |
| 2017 | ICLR | Short and Deep: Sketching and Neural Networks. | Amit Daniely, Nevena Lazic, Yoram Singer, Kunal Talwar |
| 2017 | ICLR | Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data. | Nicolas Papernot, Martn Abadi, lfar Erlingsson, Ian J. Goodfellow, Kunal Talwar |
| 2017 | SODA | LAST but not Least: Online Spanners for Buy-at-Bulk. | Anupam Gupta, R. Ravi, Kunal Talwar, Seeun William Umboh |
| 2016 | CCS | Deep Learning with Differential Privacy. | Martn Abadi, Andy Chu, Ian J. Goodfellow, H. Brendan McMahan, Ilya Mironov, Kunal Talwar, Li Zhang |
| 2015 | SODA | Approximating Hereditary Discrepancy via Small Width Ellipsoids. | Aleksandar Nikolov, Kunal Talwar |
| 2014 | ICALP | Changing Bases: Multistage Optimization for Matroids and Matchings. | Anupam Gupta, Kunal Talwar, Udi Wieder |
| 2014 | ICALP | Balanced Allocations: A Simple Proof for the Heavily Loaded Case. | Kunal Talwar, Udi Wieder |
| 2014 | SODA | Non-Uniform Graph Partitioning. | Robert Krauthgamer, Joseph Naor, Roy Schwartz, Kunal Talwar |
| 2014 | STOC | Cops, robbers, and threatening skeletons: padded decomposition for minor-free graphs. | Ittai Abraham, Cyril Gavoille, Anupam Gupta, Ofer Neiman, Kunal Talwar |
| 2014 | STOC | Analyze gauss: optimal bounds for privacy-preserving principal component analysis. | Cynthia Dwork, Kunal Talwar, Abhradeep Thakurta, Li Zhang |
| 2013 | SODA | Minimum Makespan Scheduling with Low Rank Processing Times. | Aditya Bhaskara, Ravishankar Krishnaswamy, Kunal Talwar, Udi Wieder |
| 2013 | SODA | On differentially private low rank approximation. | Michael Kapralov, Kunal Talwar |
| 2013 | STOC | Sparsest cut on bounded treewidth graphs: algorithms and hardness results. | Anupam Gupta, Kunal Talwar, David Witmer |
| 2013 | STOC | The geometry of differential privacy: the sparse and approximate cases. | Aleksandar Nikolov, Kunal Talwar, Li Zhang |
| 2012 | STOC | Unconditional differentially private mechanisms for linear queries. | Aditya Bhaskara, Daniel Dadush, Ravishankar Krishnaswamy, Kunal Talwar |
| 2010 | FOCS | The Limits of Two-Party Differential Privacy. | Andrew McGregor, Ilya Mironov, Toniann Pitassi, Omer Reingold, Kunal Talwar, Salil P. Vadhan |
| 2010 | FOCS | Lower Bounds on Near Neighbor Search via Metric Expansion. | Rina Panigrahy, Kunal Talwar, Udi Wieder |
| 2010 | SODA | Differentially Private Combinatorial Optimization. | Anupam Gupta, Katrina Ligett, Frank McSherry, Aaron Roth, Kunal Talwar |
| 2010 | SODA | The (1 + beta)-Choice Process and Weighted Balls-into-Bins. | Yuval Peres, Kunal Talwar, Udi Wieder |
| 2010 | STOC | On the geometry of differential privacy. | Moritz Hardt, Kunal Talwar |
| 2009 | SODA | Secretary problems: weights and discounts. | Moshe Babaioff, Michael Dinitz, Anupam Gupta, Nicole Immorlica, Kunal Talwar |
| 2009 | SOSP | Quincy: fair scheduling for distributed computing clusters. | Michael Isard, Vijayan Prabhakaran, Jon Currey, Udi Wieder, Kunal Talwar, Andrew V. Goldberg |
| 2008 | FOCS | A Geometric Approach to Lower Bounds for Approximate Near-Neighbor Search and Partial Match. | Rina Panigrahy, Kunal Talwar, Udi Wieder |
| 2008 | IPCO | A Constant Approximation Algorithm for the a prioriTraveling Salesman Problem. | David B. Shmoys, Kunal Talwar |
| 2008 | LATIN | How to Complete a Doubling Metric. | Anupam Gupta, Kunal Talwar |
| 2008 | PODC | Efficient distributed approximation algorithms via probabilistic tree embeddings. | Maleq Khan, Fabian Kuhn, Dahlia Malkhi, Gopal Pandurangan, Kunal Talwar |
| 2008 | SODA | Ultra-low-dimensional embeddings for doubling metrics. | T.-H. Hubert Chan, Anupam Gupta, Kunal Talwar |
| 2007 | FOCS | Balloon Popping With Applications to Ascending Auctions. | Nicole Immorlica, Anna R. Karlin, Mohammad Mahdian, Kunal Talwar |
| 2007 | FOCS | Mechanism Design via Differential Privacy. | Frank McSherry, Kunal Talwar |
| 2007 | PODC | Reconstructing approximate tree metrics. | Ittai Abraham, Mahesh Balakrishnan, Fabian Kuhn, Dahlia Malkhi, Venugopalan Ramasubramanian, Kunal Talwar |
| 2007 | PODS | Privacy, accuracy, and consistency too: a holistic solution to contingency table release. | Boaz Barak, Kamalika Chaudhuri, Cynthia Dwork, Satyen Kale, Frank McSherry, Kunal Talwar |
| 2007 | STOC | Hardness of routing with congestion in directed graphs. | Julia Chuzhoy, Venkatesan Guruswami, Sanjeev Khanna, Kunal Talwar |
| 2007 | STOC | The price of privacy and the limits of LP decoding. | Cynthia Dwork, Frank McSherry, Kunal Talwar |
| 2007 | STOC | Balanced allocations: the weighted case. | Kunal Talwar, Udi Wieder |
| 2006 | ICALP | A Push-Relabel Algorithm for Approximating Degree Bounded MSTs. | Kamalika Chaudhuri, Satish Rao, Samantha J. Riesenfeld, Kunal Talwar |
| 2006 | SODA | Approximating unique games. | Anupam Gupta, Kunal Talwar |
| 2005 | ICALP | The Generalized Deadlock Resolution Problem. | Kamal Jain, Mohammad Taghi Hajiaghayi, Kunal Talwar |
| 2005 | UAI | On Privacy-Preserving Histograms. | Shuchi Chawla, Cynthia Dwork, Frank McSherry, Kunal Talwar |
| 2004 | SODA | Approximate classification via earthmover metrics. | Aaron Archer, Jittat Fakcharoenphol, Chris Harrelson, Robert Krauthgamer, Kunal Talwar, va Tardos |
| 2004 | STOC | The complexity of pure Nash equilibria. | Alex Fabrikant, Christos H. Papadimitriou, Kunal Talwar |
| 2004 | STOC | Bypassing the embedding: algorithms for low dimensional metrics. | Kunal Talwar |
| 2003 | FOCS | Paths, Trees, and Minimum Latency Tours. | Kamalika Chaudhuri, Brighten Godfrey, Satish Rao, Kunal Talwar |
| 2003 | SODA | An approximate truthful mechanism for combinatorial auctions with single parameter agents. | Aaron Archer, Christos H. Papadimitriou, Kunal Talwar, va Tardos |
| 2003 | SODA | An improved approximation algorithm for the 0-extension problem. | Jittat Fakcharoenphol, Chris Harrelson, Satish Rao, Kunal Talwar |
| 2003 | STOC | A tight bound on approximating arbitrary metrics by tree metrics. | Jittat Fakcharoenphol, Satish Rao, Kunal Talwar |
| 2003 | STACS | The Price of Truth: Frugality in Truthful Mechanisms. | Kunal Talwar |
| 2002 | IPCO | The Single-Sink Buy-at-Bulk LP Has Constant Integrality Gap. | Kunal Talwar |