Sealed calls in Java packages. - Ayal Zaks; Vitaly Feldman; Nava Aizikowitz (OOPSLA, 2000)

On Using Extended Statistical Queries to Avoid Membership Queries. - Nader H. Bshouty; Vitaly Feldman (J. Mach. Learn. Res., 2002)

Learnability and Automatizability. - Michael Alekhnovich; Mark Braverman; Vitaly Feldman; Adam R. Klivans; Toniann Pitassi (FOCS, 2004)

Optimal Hardness Results for Maximizing Agreements with Monomials. - Vitaly Feldman (Electron. Colloquium Comput. Complex., 2006)

On Attribute Efficient and Non-adaptive Learning of Parities and DNF Expressions. - Vitaly Feldman (Electron. Colloquium Comput. Complex., 2006)

New Results for Learning Noisy Parities and Halfspaces. - Vitaly Feldman; Parikshit Gopalan; Subhash Khot; Ashok Kumar Ponnuswami (Electron. Colloquium Comput. Complex., 2006)

Separating Models of Learning with Faulty Teachers. - Vitaly Feldman; Shrenik Shah; Neal Wadhwa (ALT, 2007)

The Learning Power of Evolution. - Vitaly Feldman; Leslie G. Valiant (COLT, 2008)

Evolvability from learning algorithms. - Vitaly Feldman (STOC, 2008)

On The Power of Membership Queries in Agnostic Learning. - Vitaly Feldman (Electron. Colloquium Comput. Complex., 2008)

The complexity of properly learning simple concept classes. - Michael Alekhnovich; Mark Braverman; Vitaly Feldman; Adam R. Klivans; Toniann Pitassi (J. Comput. Syst. Sci., 2008)

Hardness of Proper Learning. - Vitaly Feldman (Encyclopedia of Algorithms, 2008)

Statistical Query Learning. - Vitaly Feldman (Encyclopedia of Algorithms, 2008)

Robustness of Evolvability. - Vitaly Feldman (COLT, 2009)

Hardness of approximate two-level logic minimization and PAC learning with membership queries. - Vitaly Feldman (J. Comput. Syst. Sci., 2009)

Experience-Induced Neural Circuits That Achieve High Capacity. - Vitaly Feldman; Leslie G. Valiant (Neural Comput., 2009)

On Agnostic Learning of Parities, Monomials, and Halfspaces. - Vitaly Feldman; Parikshit Gopalan; Subhash Khot; Ashok Kumar Ponnuswami (SIAM J. Comput., 2009)

Separating models of learning with faulty teachers. - Vitaly Feldman; Shrenik Shah (Theor. Comput. Sci., 2009)

Distribution-Specific Agnostic Boosting. - Vitaly Feldman (ICS, 2010)

Lower Bounds and Hardness Amplification for Learning Shallow Monotone Formulas. - Vitaly Feldman; Homin K. Lee; Rocco A. Servedio (Electron. Colloquium Comput. Complex., 2010)

Distribution-Independent Evolvability of Linear Threshold Functions. - Vitaly Feldman (COLT, 2011)

The Complexity of Statistical Algorithms - Vitaly Feldman; Elena Grigorescu; Lev Reyzin; Santosh S. Vempala (CoRR, 2012)

Nearly optimal solutions for the Chow Parameters Problem and low-weight approximation of halfspaces. - Anindya De; Ilias Diakonikolas; Vitaly Feldman; Rocco A. Servedio (Electron. Colloquium Comput. Complex., 2012)

Statistical Algorithms and a Lower Bound for Planted Clique. - Vitaly Feldman; Elena Grigorescu; Lev Reyzin; Santosh S. Vempala; Ying Xiao 003 (Electron. Colloquium Comput. Complex., 2012)

A complete characterization of statistical query learning with applications to evolvability. - Vitaly Feldman (J. Comput. Syst. Sci., 2012)

Learning DNF Expressions from Fourier Spectrum. - Vitaly Feldman (COLT, 2012)

Computational Bounds on Statistical Query Learning. - Vitaly Feldman; Varun Kanade (COLT, 2012)

Agnostic Learning of Monomials by Halfspaces Is Hard. - Vitaly Feldman; Venkatesan Guruswami; Prasad Raghavendra; Yi Wu 002 (SIAM J. Comput., 2012)

Learning Using Local Membership Queries. - Pranjal Awasthi; Vitaly Feldman; Varun Kanade (COLT, 2013)

Representation, Approximation and Learning of Submodular Functions Using Low-rank Decision Trees. - Vitaly Feldman; Pravesh Kothari; Jan Vondrák (COLT, 2013)

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; et al. (IJCNN, 2013)

Statistical Active Learning Algorithms. - Maria-Florina Balcan; Vitaly Feldman (NIPS, 2013)

Provenance-based dictionary refinement in information extraction. - Sudeepa Roy 001; Laura Chiticariu; Vitaly Feldman; Frederick Reiss 001; Huaiyu Zhu 001 (SIGMOD Conference, 2013)

Learning Coverage Functions - Vitaly Feldman; Pravesh Kothari (CoRR, 2013)

Structure and learning of valuation functions. - Vitaly Feldman; Jan Vondrák (SIGecom Exch., 2013)

Open Problem: The Statistical Query Complexity of Learning Sparse Halfspaces. - Vitaly Feldman (COLT, 2014)

Learning Coverage Functions and Private Release of Marginals. - Vitaly Feldman; Pravesh Kothari (COLT, 2014)

Nearly Tight Bounds on ℓ1 Approximation of Self-Bounding Functions. - Vitaly Feldman; Pravesh Kothari; Jan Vondrák (CoRR, 2014)

Subsampled Power Iteration: a New Algorithm for Block Models and Planted CSP's. - Vitaly Feldman; Will Perkins 001; Santosh S. Vempala (CoRR, 2014)

Tight Bounds on Low-Degree Spectral Concentration of Submodular and XOS Functions. - Vitaly Feldman; Jan Vondrák (FOCS, 2015)

Generalization in Adaptive Data Analysis and Holdout Reuse. - Cynthia Dwork; Vitaly Feldman; Moritz Hardt; Toniann Pitassi; Omer Reingold; Aaron Roth 001 (NIPS, 2015)

Subsampled Power Iteration: a Unified Algorithm for Block Models and Planted CSP's. - Vitaly Feldman; Will Perkins 001; Santosh S. Vempala (NIPS, 2015)

Approximate resilience, monotonicity, and the complexity of agnostic learning. - Dana Dachman-Soled; Vitaly Feldman; Li-Yang Tan; Andrew Wan; Karl Wimmer (SODA, 2015)

Preserving Statistical Validity in Adaptive Data Analysis. - Cynthia Dwork; Vitaly Feldman; Moritz Hardt; Toniann Pitassi; Omer Reingold; Aaron Leon Roth (STOC, 2015)

Statistical Active Learning Algorithms for Noise Tolerance and Differential Privacy. - Maria-Florina Balcan; Vitaly Feldman (Algorithmica, 2015)

Statistical Query Algorithms for Stochastic Convex Optimization. - Vitaly Feldman; Cristóbal Guzmán; Santosh S. Vempala (CoRR, 2015)

Agnostic learning of disjunctions on symmetric distributions. - Vitaly Feldman; Pravesh Kothari (J. Mach. Learn. Res., 2015)

Sample Complexity Bounds on Differentially Private Learning via Communication Complexity. - Vitaly Feldman; David Xiao (SIAM J. Comput., 2015)

Conference on Learning Theory 2016: Preface. - Vitaly Feldman; Alexander Rakhlin (COLT, 2016)

Generalization of ERM in Stochastic Convex Optimization: The Dimension Strikes Back. - Vitaly Feldman (NIPS, 2016)

Optimal Bounds on Approximation of Submodular and XOS Functions by Juntas. - Vitaly Feldman; Jan Vondrák (SIAM J. Comput., 2016)

Sorting and Selection with Imprecise Comparisons. - Miklós Ajtai; Vitaly Feldman; Avinatan Hassidim; Jelani Nelson (ACM Trans. Algorithms, 2016)

Hardness of Proper Learning. - Vitaly Feldman (Encyclopedia of Algorithms, 2016)

Statistical Query Learning. - Vitaly Feldman (Encyclopedia of Algorithms, 2016)

Dealing with Range Anxiety in Mean Estimation via Statistical Queries. - Vitaly Feldman (ALT, 2017)

Tight Bounds on ℓ1 Approximation and Learning of Self-Bounding Functions. - Vitaly Feldman; Pravesh Kothari; Jan Vondrák (ALT, 2017)

A General Characterization of the Statistical Query Complexity. - Vitaly Feldman (COLT, 2017)

Generalization for Adaptively-chosen Estimators via Stable Median. - Vitaly Feldman; Thomas Steinke 002 (COLT, 2017)

On the Power of Learning from k-Wise Queries. - Vitaly Feldman; Badih Ghazi (ITCS, 2017)

Guilt-free data reuse. - Cynthia Dwork; Vitaly Feldman; Moritz Hardt; Toniann Pitassi; Omer Reingold; Aaron Roth 001 (Commun. ACM, 2017)

Statistical Algorithms and a Lower Bound for Detecting Planted Cliques. - Vitaly Feldman; Elena Grigorescu; Lev Reyzin; Santosh S. Vempala; Ying Xiao 003 (J. ACM, 2017)

Privacy-preserving Prediction. - Cynthia Dwork; Vitaly Feldman (COLT, 2018)

Calibrating Noise to Variance in Adaptive Data Analysis. - Vitaly Feldman; Thomas Steinke 002 (COLT, 2018)

Privacy Amplification by Iteration. - Vitaly Feldman; Ilya Mironov; Kunal Talwar; Abhradeep Thakurta (FOCS, 2018)

Generalization Bounds for Uniformly Stable Algorithms. - Vitaly Feldman; Jan Vondrák (NeurIPS, 2018)

The Everlasting Database: Statistical Validity at a Fair Price. - Blake E. Woodworth; Vitaly Feldman; Saharon Rosset; Nati Srebro (NeurIPS, 2018)

Learning without Interaction Requires Separation. - Amit Daniely; Vitaly Feldman (CoRR, 2018)

On the Complexity of Random Satisfiability Problems with Planted Solutions. - Vitaly Feldman; Will Perkins 001; Santosh S. Vempala (SIAM J. Comput., 2018)

Open Problem: Is Margin Sufficient for Non-Interactive Private Distributed Learning? - Amit Daniely; Vitaly Feldman (COLT, 2019)

Open Problem: How fast can a multiclass test set be overfit? - Vitaly Feldman; Roy Frostig; Moritz Hardt (COLT, 2019)

High probability generalization bounds for uniformly stable algorithms with nearly optimal rate. - Vitaly Feldman; Jan Vondrák (COLT, 2019)

The advantages of multiple classes for reducing overfitting from test set reuse. - Vitaly Feldman; Roy Frostig; Moritz Hardt (ICML, 2019)

Private Stochastic Convex Optimization with Optimal Rates. - Raef Bassily; Vitaly Feldman; Kunal Talwar; Abhradeep Guha Thakurta (NeurIPS, 2019)

Locally Private Learning without Interaction Requires Separation. - Amit Daniely; Vitaly Feldman (NeurIPS, 2019)

Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity. - Úlfar Erlingsson; Vitaly Feldman; Ilya Mironov; Ananth Raghunathan; Kunal Talwar; Abhradeep Thakurta (SODA, 2019)

PAC learning with stable and private predictions. - Yuval Dagan; Vitaly Feldman (COLT, 2020)

Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses. - Raef Bassily; Vitaly Feldman; Cristóbal Guzmán; Kunal Talwar (NeurIPS, 2020)

What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation. - Vitaly Feldman; Chiyuan Zhang (NeurIPS, 2020)

Does learning require memorization? a short tale about a long tail. - Vitaly Feldman (STOC, 2020)

Private stochastic convex optimization: optimal rates in linear time. - Vitaly Feldman; Tomer Koren; Kunal Talwar (STOC, 2020)

Encode, Shuffle, Analyze Privacy Revisited: Formalizations and Empirical Evaluation. - Úlfar Erlingsson; Vitaly Feldman; Ilya Mironov; Ananth Raghunathan; Shuang Song 001; Kunal Talwar; Abhradeep Thakurta (CoRR, 2020)

Tight bounds on ℓ1 approximation and learning of self-bounding functions. - Vitaly Feldman; Pravesh Kothari; Jan Vondrák (Theor. Comput. Sci., 2020)

Hiding Among the Clones: A Simple and Nearly Optimal Analysis of Privacy Amplification by Shuffling. - Vitaly Feldman; Audra McMillan; Kunal Talwar (FOCS, 2021)

Private Stochastic Convex Optimization: Optimal Rates in L1 Geometry. - Hilal Asi; Vitaly Feldman; Tomer Koren; Kunal Talwar (ICML, 2021)

Lossless Compression of Efficient Private Local Randomizers. - Vitaly Feldman; Kunal Talwar (ICML, 2021)

Individual Privacy Accounting via a Rényi Filter. - Vitaly Feldman; Tijana Zrnic (NeurIPS, 2021)

When is memorization of irrelevant training data necessary for high-accuracy learning? - Gavin Brown 003; Mark Bun; Vitaly Feldman; Adam D. Smith 001; Kunal Talwar (STOC, 2021)

Private Stochastic Convex Optimization: Optimal Rates in 𝓁1 Geometry. - Hilal Asi; Vitaly Feldman; Tomer Koren; Kunal Talwar (CoRR, 2021)

Interaction is Necessary for Distributed Learning with Privacy or Communication Constraints. - Yuval Dagan; Vitaly Feldman (J. Priv. Confidentiality, 2021)

Statistical Query Algorithms for Mean Vector Estimation and Stochastic Convex Optimization. - Vitaly Feldman; Cristóbal Guzmán; Santosh Srinivas Vempala (Math. Oper. Res., 2021)

Optimal Algorithms for Mean Estimation under Local Differential Privacy. - Hilal Asi; Vitaly Feldman; Kunal Talwar (ICML, 2022)

Private frequency estimation via projective geometry. - Vitaly Feldman; Jelani Nelson; Huy L. Nguyen; Kunal Talwar (ICML, 2022)

Mean Estimation with User-level Privacy under Data Heterogeneity. - Rachel Cummings; Vitaly Feldman; Audra McMillan; Kunal Talwar (NeurIPS, 2022)

Subspace Recovery from Heterogeneous Data with Non-isotropic Noise. - John C. Duchi; Vitaly Feldman; Lunjia Hu; Kunal Talwar (NeurIPS, 2022)

No Free Lunch in "Privacy for Free: How does Dataset Condensation Help Privacy". - Nicholas Carlini; Vitaly Feldman; Milad Nasr (CoRR, 2022)

Private Federated Statistics in an Interactive Setting. - 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; et al. (CoRR, 2022)

Private Online Prediction from Experts: Separations and Faster Rates. - Hilal Asi; Vitaly Feldman; Tomer Koren; Kunal Talwar (COLT, 2023)

Near-Optimal Algorithms for Private Online Optimization in the Realizable Regime. - Hilal Asi; Vitaly Feldman; Tomer Koren; Kunal Talwar (ICML, 2023)

Fast Optimal Locally Private Mean Estimation via Random Projections. - Hilal Asi; Vitaly Feldman; Jelani Nelson; Huy L. Nguyen; Kunal Talwar (NeurIPS, 2023)

Stronger Privacy Amplification by Shuffling for Renyi and Approximate Differential Privacy. - Vitaly Feldman; Audra McMillan; Kunal Talwar (SODA, 2023)

Samplable Anonymous Aggregation for Private Federated Data Analysis. - Kunal Talwar; Shan Wang; Audra McMillan; Vojta Jina; Vitaly Feldman; Bailey Basile; Áine Cahill; Yi Sheng Chan; Mike Chatzidakis; Junye Chen; Oliver R. A. Chick; Mona Chitnis; et al. (CoRR, 2023)

Federated Learning with Differential Privacy for End-to-End Speech Recognition. - Martin Pelikan; Sheikh Shams Azam; Vitaly Feldman; Jan Honza Silovsky; Kunal Talwar; Tatiana Likhomanenko (CoRR, 2023)

Faster Convergence with MultiWay Preferences. - Aadirupa Saha; Vitaly Feldman; Yishay Mansour; Tomer Koren (AISTATS, 2024)

Samplable Anonymous Aggregation for Private Federated Data Analysis. - Kunal Talwar; Shan Wang; Audra McMillan; Vitaly Feldman; Pansy Bansal; Bailey Basile; Áine Cahill; Yi Sheng Chan; Mike Chatzidakis; Junye Chen; Oliver R. A. Chick; Mona Chitnis; et al. (CCS, 2024)

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 (ICML, 2024)

Instance-Optimal Private Density Estimation in the Wasserstein Distance. - Vitaly Feldman; Audra McMillan; Satchit Sivakumar; Kunal Talwar (NeurIPS, 2024)

Private and Personalized Frequency Estimation in a Federated Setting. - Amrith Setlur; Vitaly Feldman; Kunal Talwar (NeurIPS, 2024)

Differentially Private Heavy Hitter Detection using Federated Analytics. - Karan N. Chadha; Junye Chen; John C. Duchi; Vitaly Feldman; Hanieh Hashemi; Omid Javidbakht; Audra McMillan; Kunal Talwar (SaTML, 2024)

Trade-offs in Data Memorization via Strong Data Processing Inequalities. - Vitaly Feldman; Guy Kornowski; Xin Lyu 003 (COLT, 2025)

PREAMBLE: Private and Efficient Aggregation of Block Sparse Vectors and Applications. - Hilal Asi; Vitaly Feldman; Hannah Keller; Guy N. Rothblum; Kunal Talwar (IACR Cryptol. ePrint Arch., 2025)

Privacy amplification by random allocation. - Vitaly Feldman; Moshe Shenfeld (CoRR, 2025)

Local Pan-Privacy for Federated Analytics. - Vitaly Feldman; Audra McMillan; Guy N. Rothblum; Kunal Talwar (CoRR, 2025)

Instance-Optimality for Private KL Distribution Estimation. - Jiayuan Ye 001; Vitaly Feldman; Kunal Talwar (CoRR, 2025)