Vitaly Feldman

ORCID

Publication Activity (10 Years)

Years Active: 2000-2024
Publications (10 Years): 93

Top Venues

Publications

Aadirupa Saha, Vitaly Feldman, Yishay Mansour, Tomer Koren
Faster Convergence with MultiWay Preferences. AISTATS (2024)
Hilal Asi, Vitaly Feldman, Jelani Nelson, Huy L. Nguyen, Kunal Talwar, Samson Zhou
Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages. CoRR (2024)
Karan N. Chadha, Junye Chen, John C. Duchi, Vitaly Feldman, Hanieh Hashemi, Omid Javidbakht, Audra McMillan, Kunal Talwar
Differentially Private Heavy Hitter Detection using Federated Analytics. SaTML (2024)
Vitaly Feldman, Audra McMillan, Satchit Sivakumar, Kunal Talwar
Instance-Optimal Private Density Estimation in the Wasserstein Distance. CoRR (2024)
Martin Pelikan, Sheikh Shams Azam, Vitaly Feldman, Jan "Honza" Silovsky, Kunal Talwar, Tatiana Likhomanenko
Federated Learning with Differential Privacy for End-to-End Speech Recognition. CoRR (2023)
Vitaly Feldman, Audra McMillan, Kunal Talwar
Stronger Privacy Amplification by Shuffling for Renyi and Approximate Differential Privacy. SODA (2023)
Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar
Private Online Prediction from Experts: Separations and Faster Rates. COLT (2023)
Rachel Cummings, Vitaly Feldman, Audra McMillan, Kunal Talwar
Mean Estimation with User-level Privacy under Data Heterogeneity. CoRR (2023)
Kunal Talwar, Shan Wang, Audra McMillan, Vojta Jina, Vitaly Feldman, Bailey Basile, Áine Cahill, Yi Sheng Chan, Mike Chatzidakis, Junye Chen, Oliver 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 Rothblum, Michael Scaria, Linmao Song, Congzheng Song, Karl Tarbe, Sebastian Vogt, Luke Winstrom, Shundong Zhou
Samplable Anonymous Aggregation for Private Federated Data Analysis. CoRR (2023)
Hilal Asi, Vitaly Feldman, Jelani Nelson, Huy L. Nguyen, Kunal Talwar
Fast Optimal Locally Private Mean Estimation via Random Projections. NeurIPS (2023)
Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar
Near-Optimal Algorithms for Private Online Optimization in the Realizable Regime. ICML (2023)
Karan N. Chadha, Junye Chen, John C. Duchi, Vitaly Feldman, Hanieh Hashemi, Omid Javidbakht, Audra McMillan, Kunal Talwar
Differentially Private Heavy Hitter Detection using Federated Analytics. CoRR (2023)
Aadirupa Saha, Vitaly Feldman, Tomer Koren, Yishay Mansour
Faster Convergence with Multiway Preferences. CoRR (2023)
Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar
Near-Optimal Algorithms for Private Online Optimization in the Realizable Regime. CoRR (2023)
Hilal Asi, Vitaly Feldman, Jelani Nelson, Huy L. Nguyen, Kunal Talwar
Fast Optimal Locally Private Mean Estimation via Random Projections. CoRR (2023)
Vitaly Feldman, Audra McMillan, Kunal Talwar
Hiding Among the Clones: A Simple and Nearly Optimal Analysis of Privacy Amplification by Shuffling. FOCS (2022)
Hilal Asi, Vitaly Feldman, Kunal Talwar
Optimal Algorithms for Mean Estimation under Local Differential Privacy. CoRR (2022)
Vitaly Feldman, Jelani Nelson, Huy Le Nguyen, Kunal Talwar
Private Frequency Estimation via Projective Geometry. CoRR (2022)
Vitaly Feldman, Jelani Nelson, Huy L. Nguyen, Kunal Talwar
Private frequency estimation via projective geometry. ICML (2022)
Rachel Cummings, Vitaly Feldman, Audra McMillan, Kunal Talwar
Mean Estimation with User-level Privacy under Data Heterogeneity. NeurIPS (2022)
Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar
Private Online Prediction from Experts: Separations and Faster Rates. CoRR (2022)
Nicholas Carlini, Vitaly Feldman, Milad Nasr
No Free Lunch in "Privacy for Free: How does Dataset Condensation Help Privacy". CoRR (2022)
Hilal Asi, Vitaly Feldman, Kunal Talwar
Optimal Algorithms for Mean Estimation under Local Differential Privacy. ICML (2022)
John C. Duchi, Vitaly Feldman, Lunjia Hu, Kunal Talwar
Subspace Recovery from Heterogeneous Data with Non-isotropic Noise. NeurIPS (2022)
Audra McMillan, Omid Javidbakht, Kunal Talwar, Elliot Briggs, Mike Chatzidakis, Junye Chen, John C. Duchi, Vitaly Feldman, Yusuf Goren, Michael Hesse, Vojta Jina, Anil Katti, Albert Liu, Cheney Lyford, Joey Meyer, Alex Palmer, David Park, Wonhee Park, Gianni Parsa, Paul Pelzl, Rehan Rishi, Congzheng Song, Shan Wang, Shundong Zhou
Private Federated Statistics in an Interactive Setting. CoRR (2022)
John Duchi, Vitaly Feldman, Lunjia Hu, Kunal Talwar
Subspace Recovery from Heterogeneous Data with Non-isotropic Noise. CoRR (2022)
Vitaly Feldman, Audra McMillan, Kunal Talwar
Stronger Privacy Amplification by Shuffling for Rényi and Approximate Differential Privacy. CoRR (2022)
Vitaly Feldman, Audra McMillan, Kunal Talwar
Hiding Among the Clones: A Simple and Nearly Optimal Analysis of Privacy Amplification by Shuffling. FOCS (2021)
Vitaly Feldman, Kunal Talwar
Lossless Compression of Efficient Private Local Randomizers. CoRR (2021)
Vitaly Feldman, Cristóbal Guzmán, Santosh Srinivas Vempala
Statistical Query Algorithms for Mean Vector Estimation and Stochastic Convex Optimization. Math. Oper. Res. 46 (3) (2021)
Yuval Dagan, Vitaly Feldman
Interaction is Necessary for Distributed Learning with Privacy or Communication Constraints. J. Priv. Confidentiality 11 (2) (2021)
Gavin Brown, Mark Bun, Vitaly Feldman, Adam D. Smith, Kunal Talwar
When is memorization of irrelevant training data necessary for high-accuracy learning? STOC (2021)
Vitaly Feldman, Tijana Zrnic
Individual Privacy Accounting via a Rényi Filter. NeurIPS (2021)
Vitaly Feldman, Kunal Talwar
Lossless Compression of Efficient Private Local Randomizers. ICML (2021)
Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar
Geometry. CoRR (2021)
Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar
Private Stochastic Convex Optimization: Optimal Rates in L1 Geometry. ICML (2021)
Vitaly Feldman
Does learning require memorization? a short tale about a long tail. STOC (2020)
Vitaly Feldman, Tomer Koren, Kunal Talwar
Private Stochastic Convex Optimization: Optimal Rates in Linear Time. CoRR (2020)
Vitaly Feldman, Audra McMillan, Kunal Talwar
Hiding Among the Clones: A Simple and Nearly Optimal Analysis of Privacy Amplification by Shuffling. CoRR (2020)
Gavin Brown, Mark Bun, Vitaly Feldman, Adam D. Smith, Kunal Talwar
When is Memorization of Irrelevant Training Data Necessary for High-Accuracy Learning? CoRR (2020)
Vitaly Feldman, Chiyuan Zhang
What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation. CoRR (2020)
Yuval Dagan, Vitaly Feldman
PAC learning with stable and private predictions. COLT (2020)
Vitaly Feldman, Tomer Koren, Kunal Talwar
Private stochastic convex optimization: optimal rates in linear time. STOC (2020)
Yuval Dagan, Vitaly Feldman
Interaction is necessary for distributed learning with privacy or communication constraints. STOC (2020)
Vitaly Feldman, Tijana Zrnic
Individual Privacy Accounting via a Renyi Filter. CoRR (2020)
Vitaly Feldman, Pravesh Kothari, Jan Vondrák
approximation and learning of self-bounding functions. Theor. Comput. Sci. 808 (2020)
Raef Bassily, Vitaly Feldman, Cristóbal Guzmán, Kunal Talwar
Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses. NeurIPS (2020)
Úlfar Erlingsson, Vitaly Feldman, Ilya Mironov, Ananth Raghunathan, Shuang Song, Kunal Talwar, Abhradeep Thakurta
Encode, Shuffle, Analyze Privacy Revisited: Formalizations and Empirical Evaluation. CoRR (2020)
Vitaly Feldman, Chiyuan Zhang
What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation. NeurIPS (2020)
Raef Bassily, Vitaly Feldman, Cristóbal Guzmán, Kunal Talwar
Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses. CoRR (2020)
Raef Bassily, Vitaly Feldman, Kunal Talwar, Abhradeep Thakurta
Private Stochastic Convex Optimization with Optimal Rates. CoRR (2019)
Vitaly Feldman, Roy Frostig, Moritz Hardt
The advantages of multiple classes for reducing overfitting from test set reuse. CoRR (2019)
Vitaly Feldman, Roy Frostig, Moritz Hardt
The advantages of multiple classes for reducing overfitting from test set reuse. ICML (2019)
Raef Bassily, Vitaly Feldman, Kunal Talwar, Abhradeep Guha Thakurta
Private Stochastic Convex Optimization with Optimal Rates. NeurIPS (2019)
Vitaly Feldman
Does Learning Require Memorization? A Short Tale about a Long Tail. CoRR (2019)
Vitaly Feldman, Jan Vondrák
High probability generalization bounds for uniformly stable algorithms with nearly optimal rate. COLT (2019)
Yuval Dagan, Vitaly Feldman
Interaction is necessary for distributed learning with privacy or communication constraints. CoRR (2019)
Amit Daniely, Vitaly Feldman
Locally Private Learning without Interaction Requires Separation. NeurIPS (2019)
Úlfar Erlingsson, Vitaly Feldman, Ilya Mironov, Ananth Raghunathan, Kunal Talwar, Abhradeep Thakurta
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity. SODA (2019)
Vitaly Feldman, Jan Vondrák
High probability generalization bounds for uniformly stable algorithms with nearly optimal rate. CoRR (2019)
Vitaly Feldman, Roy Frostig, Moritz Hardt
Open Problem: How fast can a multiclass test set be overfit? COLT (2019)
Amit Daniely, Vitaly Feldman
Open Problem: Is Margin Sufficient for Non-Interactive Private Distributed Learning? COLT (2019)
Yuval Dagan, Vitaly Feldman
PAC learning with stable and private predictions. CoRR (2019)
Cynthia Dwork, Vitaly Feldman
Privacy-preserving Prediction. CoRR (2018)
Vitaly Feldman, Ilya Mironov, Kunal Talwar, Abhradeep Thakurta
Privacy Amplification by Iteration. FOCS (2018)
Blake E. Woodworth, Vitaly Feldman, Saharon Rosset, Nati Srebro
The Everlasting Database: Statistical Validity at a Fair Price. NeurIPS (2018)
Cynthia Dwork, Vitaly Feldman
Privacy-preserving Prediction. COLT (2018)
Vitaly Feldman, Will Perkins, Santosh S. Vempala
On the Complexity of Random Satisfiability Problems with Planted Solutions. SIAM J. Comput. 47 (4) (2018)
Vitaly Feldman, Thomas Steinke
Calibrating Noise to Variance in Adaptive Data Analysis. COLT (2018)
Úlfar Erlingsson, Vitaly Feldman, Ilya Mironov, Ananth Raghunathan, Kunal Talwar, Abhradeep Thakurta
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity. CoRR (2018)
Vitaly Feldman, Jan Vondrák
Generalization Bounds for Uniformly Stable Algorithms. NeurIPS (2018)
Vitaly Feldman, Ilya Mironov, Kunal Talwar, Abhradeep Thakurta
Privacy Amplification by Iteration. CoRR (2018)
Vitaly Feldman, Jan Vondrák
Generalization Bounds for Uniformly Stable Algorithms. CoRR (2018)
Amit Daniely, Vitaly Feldman
Learning without Interaction Requires Separation. CoRR (2018)
Blake E. Woodworth, Vitaly Feldman, Saharon Rosset, Nathan Srebro
The Everlasting Database: Statistical Validity at a Fair Price. CoRR (2018)
Vitaly Feldman, Thomas Steinke
Generalization for Adaptively-chosen Estimators via Stable Median. CoRR (2017)
Cynthia Dwork, Vitaly Feldman, Moritz Hardt, Toniann Pitassi, Omer Reingold, Aaron Roth
Guilt-free data reuse. Commun. ACM 60 (4) (2017)
Vitaly Feldman, Pravesh Kothari, Jan Vondrák
Approximation and Learning of Self-Bounding Functions. ALT (2017)
Vitaly Feldman, Badih Ghazi
On the Power of Learning from k-Wise Queries. ITCS (2017)
Vitaly Feldman, Cristobal Guzman, Santosh S. Vempala
Statistical Query Algorithms for Mean Vector Estimation and Stochastic Convex Optimization. SODA (2017)
Vitaly Feldman, Elena Grigorescu, Lev Reyzin, Santosh S. Vempala, Ying Xiao
Statistical Algorithms and a Lower Bound for Detecting Planted Cliques. J. ACM 64 (2) (2017)
Vitaly Feldman, Badih Ghazi
On the Power of Learning from k-Wise Queries. CoRR (2017)
Vitaly Feldman, Thomas Steinke
Generalization for Adaptively-chosen Estimators via Stable Median. COLT (2017)
Vitaly Feldman
A General Characterization of the Statistical Query Complexity. COLT (2017)
Vitaly Feldman, Thomas Steinke
Calibrating Noise to Variance in Adaptive Data Analysis. CoRR (2017)
Vitaly Feldman
Dealing with Range Anxiety in Mean Estimation via Statistical Queries. ALT (2017)
Vitaly Feldman, Alexander Rakhlin
Conference on Learning Theory 2016: Preface. COLT (2016)
Vitaly Feldman, Jan Vondrák
Optimal Bounds on Approximation of Submodular and XOS Functions by Juntas. SIAM J. Comput. 45 (3) (2016)
Vitaly Feldman
Generalization of ERM in Stochastic Convex Optimization: The Dimension Strikes Back. CoRR (2016)
Vitaly Feldman
Generalization of ERM in Stochastic Convex Optimization: The Dimension Strikes Back. NIPS (2016)
Vitaly Feldman
A General Characterization of the Statistical Query Complexity. CoRR (2016)
Miklós Ajtai, Vitaly Feldman, Avinatan Hassidim, Jelani Nelson
Sorting and Selection with Imprecise Comparisons. ACM Trans. Algorithms 12 (2) (2016)
Vitaly Feldman
Dealing with Range Anxiety in Mean Estimation via Statistical Queries. CoRR (2016)
Vitaly Feldman, Will Perkins, Santosh S. Vempala
On the Complexity of Random Satisfiability Problems with Planted Solutions. STOC (2015)
Maria-Florina Balcan, Vitaly Feldman
Statistical Active Learning Algorithms for Noise Tolerance and Differential Privacy. Algorithmica 72 (1) (2015)
Vitaly Feldman, Will Perkins, Santosh S. Vempala
Subsampled Power Iteration: a Unified Algorithm for Block Models and Planted CSP's. NIPS (2015)
Cynthia Dwork, Vitaly Feldman, Moritz Hardt, Toniann Pitassi, Omer Reingold, Aaron Roth
Generalization in Adaptive Data Analysis and Holdout Reuse. CoRR (2015)
Vitaly Feldman, Jan Vondrák
Tight Bounds on Low-Degree Spectral Concentration of Submodular and XOS Functions. FOCS (2015)
Cynthia Dwork, Vitaly Feldman, Moritz Hardt, Toniann Pitassi, Omer Reingold, Aaron Leon Roth
Preserving Statistical Validity in Adaptive Data Analysis. STOC (2015)
Dana Dachman-Soled, Vitaly Feldman, Li-Yang Tan, Andrew Wan, Karl Wimmer
Approximate resilience, monotonicity, and the complexity of agnostic learning. SODA (2015)

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Publication Activity (10 Years)

Top Topics

Top Venues

Vitaly Feldman