| 2026 | COLT | Invited Open Problem: Is the Power of Deep Learning over Linear Models Inherently Distribution Dependent? | Vitaly Feldman, Pritish Kamath, Nathan Srebro |
| 2025 | COLT | Trade-offs in Data Memorization via Strong Data Processing Inequalities. | Vitaly Feldman, Guy Kornowski, Xin Lyu |
| 2025 | ICML | Local Pan-privacy for Federated Analytics. | Vitaly Feldman, Audra McMillan, Guy N. Rothblum, Kunal Talwar |
| 2024 | AISTATS | Faster Convergence with MultiWay Preferences. | Aadirupa Saha, Vitaly Feldman, Yishay Mansour, Tomer Koren |
| 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 | 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 |
| 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 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 | 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 | COLT | PAC learning with stable and private predictions. | Yuval Dagan, Vitaly Feldman |
| 2020 | STOC | Interaction is necessary for distributed learning with privacy or communication constraints. | Yuval Dagan, Vitaly Feldman |
| 2020 | STOC | Does learning require memorization? a short tale about a long tail. | Vitaly Feldman |
| 2020 | STOC | Private stochastic convex optimization: optimal rates in linear time. | Vitaly Feldman, Tomer Koren, Kunal Talwar |
| 2019 | COLT | Open Problem: Is Margin Sufficient for Non-Interactive Private Distributed Learning? | Amit Daniely, Vitaly Feldman |
| 2019 | COLT | Open Problem: How fast can a multiclass test set be overfit? | Vitaly Feldman, Roy Frostig, Moritz Hardt |
| 2019 | COLT | High probability generalization bounds for uniformly stable algorithms with nearly optimal rate. | Vitaly Feldman, Jan Vondrk |
| 2019 | ICML | The advantages of multiple classes for reducing overfitting from test set reuse. | Vitaly Feldman, Roy Frostig, Moritz Hardt |
| 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 |
| 2018 | COLT | Privacy-preserving Prediction. | Cynthia Dwork, Vitaly Feldman |
| 2018 | COLT | Calibrating Noise to Variance in Adaptive Data Analysis. | Vitaly Feldman, Thomas Steinke |
| 2018 | FOCS | Privacy Amplification by Iteration. | Vitaly Feldman, Ilya Mironov, Kunal Talwar, Abhradeep Thakurta |
| 2017 | ALT | Dealing with Range Anxiety in Mean Estimation via Statistical Queries. | Vitaly Feldman |
| 2017 | ALT | Tight Bounds on ℓ | Vitaly Feldman, Pravesh Kothari, Jan Vondrk |
| 2017 | COLT | A General Characterization of the Statistical Query Complexity. | Vitaly Feldman |
| 2017 | COLT | Generalization for Adaptively-chosen Estimators via Stable Median. | Vitaly Feldman, Thomas Steinke |
| 2017 | SODA | Statistical Query Algorithms for Mean Vector Estimation and Stochastic Convex Optimization. | Vitaly Feldman, Cristbal Guzmn, Santosh S. Vempala |
| 2016 | COLT | Conference on Learning Theory 2016: Preface. | Vitaly Feldman, Alexander Rakhlin |
| 2015 | FOCS | Tight Bounds on Low-Degree Spectral Concentration of Submodular and XOS Functions. | Vitaly Feldman, Jan Vondrk |
| 2015 | SODA | Approximate resilience, monotonicity, and the complexity of agnostic learning. | Dana Dachman-Soled, Vitaly Feldman, Li-Yang Tan, Andrew Wan, Karl Wimmer |
| 2015 | STOC | Preserving Statistical Validity in Adaptive Data Analysis. | Cynthia Dwork, Vitaly Feldman, Moritz Hardt, Toniann Pitassi, Omer Reingold, Aaron Leon Roth |
| 2015 | STOC | On the Complexity of Random Satisfiability Problems with Planted Solutions. | Vitaly Feldman, Will Perkins, Santosh S. Vempala |
| 2014 | COLT | Open Problem: The Statistical Query Complexity of Learning Sparse Halfspaces. | Vitaly Feldman |
| 2014 | COLT | Learning Coverage Functions and Private Release of Marginals. | Vitaly Feldman, Pravesh Kothari |
| 2014 | COLT | Sample Complexity Bounds on Differentially Private Learning via Communication Complexity. | Vitaly Feldman, David Xiao |
| 2014 | ITA | Optimal bounds on approximation of submodular and XOS functions by juntas. | Vitaly Feldman, Jan Vondrk |
| 2013 | COLT | Learning Using Local Membership Queries. | Pranjal Awasthi, Vitaly Feldman, Varun Kanade |
| 2013 | COLT | Representation, Approximation and Learning of Submodular Functions Using Low-rank Decision Trees. | Vitaly Feldman, Pravesh Kothari, Jan Vondrk |
| 2013 | FOCS | Optimal Bounds on Approximation of Submodular and XOS Functions by Juntas. | Vitaly Feldman, Jan Vondrk |
| 2013 | IJCNN | Cognitive computing building block: A versatile and efficient digital neuron model for neurosynaptic cores. | Andrew S. Cassidy, Paul Merolla, John V. Arthur, Steven K. Esser, Bryan L. Jackson, Rodrigo Alvarez-Icaza, Pallab Datta, Jun Sawada, Theodore M. Wong, Vitaly Feldman, Arnon Amir, Daniel Ben Dayan Rubin, Filipp Akopyan, Emmett McQuinn, William P. Risk, Dharmendra S. Modha |
| 2013 | SIGMOD | Provenance-based dictionary refinement in information extraction. | Sudeepa Roy, Laura Chiticariu, Vitaly Feldman, Frederick Reiss, Huaiyu Zhu |
| 2013 | STOC | Statistical algorithms and a lower bound for detecting planted cliques. | Vitaly Feldman, Elena Grigorescu, Lev Reyzin, Santosh S. Vempala, Ying Xiao |
| 2012 | STOC | Nearly optimal solutions for the chow parameters problem and low-weight approximation of halfspaces. | Anindya De, Ilias Diakonikolas, Vitaly Feldman, Rocco A. Servedio |
| 2009 | COLT | Robustness of Evolvability. | Vitaly Feldman |
| 2009 | FOCS | A Complete Characterization of Statistical Query Learning with Applications to Evolvability. | Vitaly Feldman |
| 2009 | FOCS | Agnostic Learning of Monomials by Halfspaces Is Hard. | Vitaly Feldman, Venkatesan Guruswami, Prasad Raghavendra, Yi Wu |
| 2009 | ICALP | Sorting and Selection with Imprecise Comparisons. | Mikls Ajtai, Vitaly Feldman, Avinatan Hassidim, Jelani Nelson |
| 2008 | COLT | On the Power of Membership Queries in Agnostic Learning. | Vitaly Feldman |
| 2008 | COLT | The Learning Power of Evolution. | Vitaly Feldman, Leslie G. Valiant |
| 2008 | STOC | Evolvability from learning algorithms. | Vitaly Feldman |
| 2007 | ALT | Separating Models of Learning with Faulty Teachers. | Vitaly Feldman, Shrenik Shah, Neal Wadhwa |
| 2006 | FOCS | New Results for Learning Noisy Parities and Halfspaces. | Vitaly Feldman, Parikshit Gopalan, Subhash Khot, Ashok Kumar Ponnuswami |
| 2006 | STOC | Hardness of approximate two-level logic minimization and PAC learning with membership queries. | Vitaly Feldman |
| 2005 | COLT | On Attribute Efficient and Non-adaptive Learning of Parities and DNF Expressions. | Vitaly Feldman |
| 2004 | FOCS | Learnability and Automatizability. | Michael Alekhnovich, Mark Braverman, Vitaly Feldman, Adam R. Klivans, Toniann Pitassi |
| 2001 | COLT | On Using Extended Statistical Queries to Avoid Membership Queries. | Nader H. Bshouty, Vitaly Feldman |
| 2000 | OOPSLA | Sealed calls in Java packages. | Ayal Zaks, Vitaly Feldman, Nava Aizikowitz |