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ORCIDVitaly Feldman
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- affiliation: IBM Almaden Research Center
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2020 – today
- 2022
[i62]Vitaly Feldman, Jelani Nelson, Huy Le Nguyen, Kunal Talwar:
Private Frequency Estimation via Projective Geometry. CoRR abs/2203.00194 (2022)- [i61]Hilal Asi, Vitaly Feldman, Kunal Talwar:
Optimal Algorithms for Mean Estimation under Local Differential Privacy. CoRR abs/2205.02466 (2022) - 2021
- [j22]Vitaly Feldman, Cristóbal Guzmán
, Santosh Srinivas Vempala:
Statistical Query Algorithms for Mean Vector Estimation and Stochastic Convex Optimization. Math. Oper. Res. 46(3): 912-945 (2021) - [c69]Vitaly Feldman, Audra McMillan, Kunal Talwar:
Hiding Among the Clones: A Simple and Nearly Optimal Analysis of Privacy Amplification by Shuffling. FOCS 2021: 954-964 - [c68]Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar:
Private Stochastic Convex Optimization: Optimal Rates in L1 Geometry. ICML 2021: 393-403 - [c67]Vitaly Feldman, Kunal Talwar:
Lossless Compression of Efficient Private Local Randomizers. ICML 2021: 3208-3219 - [c66]Vitaly Feldman, Tijana Zrnic:
Individual Privacy Accounting via a Rényi Filter. NeurIPS 2021: 28080-28091 - [c65]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: 123-132 - [e3]Vitaly Feldman, Katrina Ligett, Sivan Sabato:
Algorithmic Learning Theory, 16-19 March 2021, Virtual Conference, Worldwide. Proceedings of Machine Learning Research 132, PMLR 2021 [contents] - [i60]Vitaly Feldman, Kunal Talwar:
Lossless Compression of Efficient Private Local Randomizers. CoRR abs/2102.12099 (2021) - [i59]Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar:
Private Stochastic Convex Optimization: Optimal Rates in 𝓁1 Geometry. CoRR abs/2103.01516 (2021) - 2020
- [j21]Vitaly Feldman, Pravesh Kothari, Jan Vondrák:
Tight bounds on ℓ1 approximation and learning of self-bounding functions. Theor. Comput. Sci. 808: 86-98 (2020) - [c64]Yuval Dagan, Vitaly Feldman:
PAC learning with stable and private predictions. COLT 2020: 1389-1410 - [c63]Raef Bassily, Vitaly Feldman, Cristóbal Guzmán, Kunal Talwar:
Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses. NeurIPS 2020 - [c62]Vitaly Feldman, Chiyuan Zhang:
What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation. NeurIPS 2020 - [c61]Vitaly Feldman, Tomer Koren, Kunal Talwar:
Private stochastic convex optimization: optimal rates in linear time. STOC 2020: 439-449 - [c60]Yuval Dagan, Vitaly Feldman:
Interaction is necessary for distributed learning with privacy or communication constraints. STOC 2020: 450-462 - [c59]Vitaly Feldman:
Does learning require memorization? a short tale about a long tail. STOC 2020: 954-959 - [i58]Úlfar Erlingsson, Vitaly Feldman, Ilya Mironov, Ananth Raghunathan, Shuang Song, Kunal Talwar, Abhradeep Thakurta:
Encode, Shuffle, Analyze Privacy Revisited: Formalizations and Empirical Evaluation. CoRR abs/2001.03618 (2020) - [i57]Vitaly Feldman, Tomer Koren, Kunal Talwar:
Private Stochastic Convex Optimization: Optimal Rates in Linear Time. CoRR abs/2005.04763 (2020) - [i56]Raef Bassily, Vitaly Feldman, Cristóbal Guzmán, Kunal Talwar:
Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses. CoRR abs/2006.06914 (2020) - [i55]Vitaly Feldman, Chiyuan Zhang:
What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation. CoRR abs/2008.03703 (2020) - [i54]Vitaly Feldman, Tijana Zrnic:
Individual Privacy Accounting via a Renyi Filter. CoRR abs/2008.11193 (2020) - [i53]Gavin Brown, Mark Bun, Vitaly Feldman, Adam D. Smith, Kunal Talwar:
When is Memorization of Irrelevant Training Data Necessary for High-Accuracy Learning? CoRR abs/2012.06421 (2020) - [i52]Vitaly Feldman, Audra McMillan, Kunal Talwar:
Hiding Among the Clones: A Simple and Nearly Optimal Analysis of Privacy Amplification by Shuffling. CoRR abs/2012.12803 (2020)
2010 – 2019
- 2019
- [c58]Vitaly Feldman, Jan Vondrák:
High probability generalization bounds for uniformly stable algorithms with nearly optimal rate. COLT 2019: 1270-1279 - [c57]Amit Daniely, Vitaly Feldman:
Open Problem: Is Margin Sufficient for Non-Interactive Private Distributed Learning? COLT 2019: 3180-3184 - [c56]Vitaly Feldman, Roy Frostig, Moritz Hardt:
Open Problem: How fast can a multiclass test set be overfit? COLT 2019: 3185-3189 - [c55]Vitaly Feldman, Roy Frostig, Moritz Hardt:
The advantages of multiple classes for reducing overfitting from test set reuse. ICML 2019: 1892-1900 - [c54]Raef Bassily, Vitaly Feldman, Kunal Talwar, Abhradeep Guha Thakurta:
Private Stochastic Convex Optimization with Optimal Rates. NeurIPS 2019: 11279-11288 - [c53]Amit Daniely, Vitaly Feldman:
Locally Private Learning without Interaction Requires Separation. NeurIPS 2019: 14975-14986 - [c52]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: 2468-2479 - [i51]Vitaly Feldman, Jan Vondrák:
High probability generalization bounds for uniformly stable algorithms with nearly optimal rate. CoRR abs/1902.10710 (2019) - [i50]Vitaly Feldman, Roy Frostig, Moritz Hardt:
The advantages of multiple classes for reducing overfitting from test set reuse. CoRR abs/1905.10360 (2019) - [i49]Vitaly Feldman:
Does Learning Require Memorization? A Short Tale about a Long Tail. CoRR abs/1906.05271 (2019) - [i48]Raef Bassily, Vitaly Feldman, Kunal Talwar, Abhradeep Thakurta:
Private Stochastic Convex Optimization with Optimal Rates. CoRR abs/1908.09970 (2019) - [i47]Yuval Dagan, Vitaly Feldman:
Interaction is necessary for distributed learning with privacy or communication constraints. CoRR abs/1911.04014 (2019) - [i46]Yuval Dagan, Vitaly Feldman:
PAC learning with stable and private predictions. CoRR abs/1911.10541 (2019) - 2018
- [j20]Vitaly Feldman, Will Perkins, Santosh S. Vempala:
On the Complexity of Random Satisfiability Problems with Planted Solutions. SIAM J. Comput. 47(4): 1294-1338 (2018) - [c51]Vitaly Feldman, Thomas Steinke:
Calibrating Noise to Variance in Adaptive Data Analysis. COLT 2018: 535-544 - [c50]Cynthia Dwork, Vitaly Feldman:
Privacy-preserving Prediction. COLT 2018: 1693-1702 - [c49]Vitaly Feldman, Ilya Mironov, Kunal Talwar, Abhradeep Thakurta:
Privacy Amplification by Iteration. FOCS 2018: 521-532 - [c48]Blake E. Woodworth, Vitaly Feldman, Saharon Rosset, Nati Srebro:
The Everlasting Database: Statistical Validity at a Fair Price. NeurIPS 2018: 6532-6541 - [c47]Vitaly Feldman, Jan Vondrák:
Generalization Bounds for Uniformly Stable Algorithms. NeurIPS 2018: 9770-9780 - [i45]Blake E. Woodworth, Vitaly Feldman, Saharon Rosset, Nathan Srebro:
The Everlasting Database: Statistical Validity at a Fair Price. CoRR abs/1803.04307 (2018) - [i44]Cynthia Dwork, Vitaly Feldman:
Privacy-preserving Prediction. CoRR abs/1803.10266 (2018) - [i43]Vitaly Feldman, Ilya Mironov, Kunal Talwar, Abhradeep Thakurta:
Privacy Amplification by Iteration. CoRR abs/1808.06651 (2018) - [i42]Amit Daniely, Vitaly Feldman:
Learning without Interaction Requires Separation. CoRR abs/1809.09165 (2018) - [i41]Úlfar Erlingsson, Vitaly Feldman, Ilya Mironov, Ananth Raghunathan, Kunal Talwar, Abhradeep Thakurta:
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity. CoRR abs/1811.12469 (2018) - [i40]Vitaly Feldman, Jan Vondrák:
Generalization Bounds for Uniformly Stable Algorithms. CoRR abs/1812.09859 (2018) - 2017
- [j19]Cynthia Dwork, Vitaly Feldman, Moritz Hardt, Toniann Pitassi, Omer Reingold, Aaron Roth:
Guilt-free data reuse. Commun. ACM 60(4): 86-93 (2017) - [j18]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): 8:1-8:37 (2017) - [c46]Vitaly Feldman, Pravesh Kothari, Jan Vondrák:
Tight Bounds on ℓ1 Approximation and Learning of Self-Bounding Functions. ALT 2017: 540-559 - [c45]Vitaly Feldman:
Dealing with Range Anxiety in Mean Estimation via Statistical Queries. ALT 2017: 629-640 - [c44]Vitaly Feldman, Thomas Steinke:
Generalization for Adaptively-chosen Estimators via Stable Median. COLT 2017: 728-757 - [c43]Vitaly Feldman:
A General Characterization of the Statistical Query Complexity. COLT 2017: 785-830 - [c42]Vitaly Feldman, Badih Ghazi:
On the Power of Learning from k-Wise Queries. ITCS 2017: 41:1-41:32 - [c41]Vitaly Feldman, Cristóbal Guzmán, Santosh S. Vempala:
Statistical Query Algorithms for Mean Vector Estimation and Stochastic Convex Optimization. SODA 2017: 1265-1277 - [i39]Vitaly Feldman, Badih Ghazi:
On the Power of Learning from k-Wise Queries. CoRR abs/1703.00066 (2017) - [i38]Vitaly Feldman, Thomas Steinke:
Generalization for Adaptively-chosen Estimators via Stable Median. CoRR abs/1706.05069 (2017) - [i37]Vitaly Feldman, Thomas Steinke:
Calibrating Noise to Variance in Adaptive Data Analysis. CoRR abs/1712.07196 (2017) - 2016
- [j17]Vitaly Feldman, Jan Vondrák:
Optimal Bounds on Approximation of Submodular and XOS Functions by Juntas. SIAM J. Comput. 45(3): 1129-1170 (2016) - [j16]Miklós Ajtai, Vitaly Feldman, Avinatan Hassidim, Jelani Nelson:
Sorting and Selection with Imprecise Comparisons. ACM Trans. Algorithms 12(2): 19:1-19:19 (2016) - [c40]Vitaly Feldman, Alexander Rakhlin:
Conference on Learning Theory 2016: Preface. COLT 2016: 1-3 - [c39]Vitaly Feldman:
Generalization of ERM in Stochastic Convex Optimization: The Dimension Strikes Back. NIPS 2016: 3576-3584 - [e2]Vitaly Feldman, Alexander Rakhlin, Ohad Shamir:
Proceedings of the 29th Conference on Learning Theory, COLT 2016, New York, USA, June 23-26, 2016. JMLR Workshop and Conference Proceedings 49, JMLR.org 2016 [contents] - [r4]Vitaly Feldman:
Hardness of Proper Learning. Encyclopedia of Algorithms 2016: 897-900 - [r3]Vitaly Feldman:
Statistical Query Learning. Encyclopedia of Algorithms 2016: 2090-2095 - [i36]Vitaly Feldman:
A General Characterization of the Statistical Query Complexity. CoRR abs/1608.02198 (2016) - [i35]Vitaly Feldman:
Generalization of ERM in Stochastic Convex Optimization: The Dimension Strikes Back. CoRR abs/1608.04414 (2016) - [i34]Vitaly Feldman:
Dealing with Range Anxiety in Mean Estimation via Statistical Queries. CoRR abs/1611.06475 (2016) - 2015
- [j15]Maria-Florina Balcan, Vitaly Feldman:
Statistical Active Learning Algorithms for Noise Tolerance and Differential Privacy. Algorithmica 72(1): 282-315 (2015) - [j14]Vitaly Feldman, Pravesh Kothari:
Agnostic learning of disjunctions on symmetric distributions. J. Mach. Learn. Res. 16: 3455-3467 (2015) - [j13]Vitaly Feldman, David Xiao:
Sample Complexity Bounds on Differentially Private Learning via Communication Complexity. SIAM J. Comput. 44(6): 1740-1764 (2015) - [c38]Vitaly Feldman, Jan Vondrák:
Tight Bounds on Low-Degree Spectral Concentration of Submodular and XOS Functions. FOCS 2015: 923-942 - [c37]Cynthia Dwork, Vitaly Feldman, Moritz Hardt, Toniann Pitassi, Omer Reingold, Aaron Roth:
Generalization in Adaptive Data Analysis and Holdout Reuse. NIPS 2015: 2350-2358 - [c36]Vitaly Feldman, Will Perkins, Santosh S. Vempala:
Subsampled Power Iteration: a Unified Algorithm for Block Models and Planted CSP's. NIPS 2015: 2836-2844 - [c35]Dana Dachman-Soled, Vitaly Feldman, Li-Yang Tan, Andrew Wan, Karl Wimmer:
Approximate resilience, monotonicity, and the complexity of agnostic learning. SODA 2015: 498-511 - [c34]Vitaly Feldman, Will Perkins, Santosh S. Vempala:
On the Complexity of Random Satisfiability Problems with Planted Solutions. STOC 2015: 77-86 - [c33]Cynthia Dwork, Vitaly Feldman, Moritz Hardt, Toniann Pitassi, Omer Reingold, Aaron Leon Roth:
Preserving Statistical Validity in Adaptive Data Analysis. STOC 2015: 117-126 - [i33]Miklós Ajtai, Vitaly Feldman, Avinatan Hassidim, Jelani Nelson:
Sorting and Selection with Imprecise Comparisons. CoRR abs/1501.02911 (2015) - [i32]Vitaly Feldman, Jan Vondrák:
Tight Bounds on Low-degree Spectral Concentration of Submodular and XOS functions. CoRR abs/1504.03391 (2015) - [i31]Cynthia Dwork, Vitaly Feldman, Moritz Hardt, Toniann Pitassi, Omer Reingold, Aaron Roth:
Generalization in Adaptive Data Analysis and Holdout Reuse. CoRR abs/1506.02629 (2015) - [i30]Vitaly Feldman, Cristóbal Guzmán, Santosh S. Vempala:
Statistical Query Algorithms for Stochastic Convex Optimization. CoRR abs/1512.09170 (2015) - 2014
- [j12]Anindya De, Ilias Diakonikolas, Vitaly Feldman, Rocco A. Servedio:
Nearly Optimal Solutions for the Chow Parameters Problem and Low-Weight Approximation of Halfspaces. J. ACM 61(2): 11:1-11:36 (2014) - [c32]Vitaly Feldman, Pravesh Kothari:
Learning Coverage Functions and Private Release of Marginals. COLT 2014: 679-702 - [c31]Vitaly Feldman, David Xiao:
Sample Complexity Bounds on Differentially Private Learning via Communication Complexity. COLT 2014: 1000-1019 - [c30]Vitaly Feldman:
Open Problem: The Statistical Query Complexity of Learning Sparse Halfspaces. COLT 2014: 1283-1289 - [c29]Vitaly Feldman, Jan Vondrák:
Optimal bounds on approximation of submodular and XOS functions by juntas. ITA 2014: 1-10 - [e1]Maria-Florina Balcan, Vitaly Feldman, Csaba Szepesvári:
Proceedings of The 27th Conference on Learning Theory, COLT 2014, Barcelona, Spain, June 13-15, 2014. JMLR Workshop and Conference Proceedings 35, JMLR.org 2014 [contents] - [i29]Vitaly Feldman, David Xiao:
Sample Complexity Bounds on Differentially Private Learning via Communication Complexity. CoRR abs/1402.6278 (2014) - [i28]Vitaly Feldman, Pravesh Kothari, Jan Vondrák:
Nearly Tight Bounds on ℓ1 Approximation of Self-Bounding Functions. CoRR abs/1404.4702 (2014) - [i27]Dana Dachman-Soled, Vitaly Feldman, Li-Yang Tan, Andrew Wan, Karl Wimmer:
Approximate resilience, monotonicity, and the complexity of agnostic learning. CoRR abs/1405.5268 (2014) - [i26]Vitaly Feldman, Pravesh Kothari:
Agnostic Learning of Disjunctions on Symmetric Distributions. CoRR abs/1405.6791 (2014) - [i25]Vitaly Feldman, Will Perkins, Santosh S. Vempala:
Subsampled Power Iteration: a New Algorithm for Block Models and Planted CSP's. CoRR abs/1407.2774 (2014) - [i24]Cynthia Dwork, Vitaly Feldman, Moritz Hardt, Toniann Pitassi, Omer Reingold, Aaron Roth:
Preserving Statistical Validity in Adaptive Data Analysis. CoRR abs/1411.2664 (2014) - [i23]Vitaly Feldman, Will Perkins, Santosh S. Vempala:
On the Complexity of Random Satisfiability Problems with Planted Solutions. Electron. Colloquium Comput. Complex. 21: 148 (2014) - 2013
- [j11]Vitaly Feldman, Jan Vondrák:
Structure and learning of valuation functions. SIGecom Exch. 12(2): 50-53 (2013) - [c28]Pranjal Awasthi, Vitaly Feldman, Varun Kanade:
Learning Using Local Membership Queries. COLT 2013: 398-431 - [c27]Vitaly Feldman, Pravesh Kothari, Jan Vondrák:
Representation, Approximation and Learning of Submodular Functions Using Low-rank Decision Trees. COLT 2013: 711-740 - [c26]Vitaly Feldman, Jan Vondrák:
Optimal Bounds on Approximation of Submodular and XOS Functions by Juntas. FOCS 2013: 227-236 - [c25]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:
Cognitive computing building block: A versatile and efficient digital neuron model for neurosynaptic cores. IJCNN 2013: 1-10 - [c24]Maria-Florina Balcan, Vitaly Feldman:
Statistical Active Learning Algorithms. NIPS 2013: 1295-1303 - [c23]Sudeepa Roy, Laura Chiticariu, Vitaly Feldman, Frederick Reiss, Huaiyu Zhu:
Provenance-based dictionary refinement in information extraction. SIGMOD Conference 2013: 457-468 - [c22]Vitaly Feldman, Elena Grigorescu, Lev Reyzin, Santosh S. Vempala, Ying Xiao:
Statistical algorithms and a lower bound for detecting planted cliques. STOC 2013: 655-664 - [i22]Vitaly Feldman, Pravesh Kothari, Jan Vondrák:
Representation, Approximation and Learning of Submodular Functions Using Low-rank Decision Trees. CoRR abs/1304.0730 (2013) - [i21]Vitaly Feldman, Pravesh Kothari:
Learning Coverage Functions. CoRR abs/1304.2079 (2013) - [i20]Maria-Florina Balcan, Vitaly Feldman:
Statistical Active Learning Algorithms. CoRR abs/1307.3102 (2013) - [i19]Vitaly Feldman, Jan Vondrák:
Optimal Bounds on Approximation of Submodular and XOS Functions by Juntas. CoRR abs/1307.3301 (2013) - [i18]Vitaly Feldman, Will Perkins, Santosh S. Vempala:
On the Complexity of Random Satisfiability Problems with Planted Solutions. CoRR abs/1311.4821 (2013) - 2012
- [j10]Vitaly Feldman:
A complete characterization of statistical query learning with applications to evolvability. J. Comput. Syst. Sci. 78(5): 1444-1459 (2012) - [j9]Vitaly Feldman, Venkatesan Guruswami, Prasad Raghavendra, Yi Wu:
Agnostic Learning of Monomials by Halfspaces Is Hard. SIAM J. Comput. 41(6): 1558-1590 (2012) - [c21]Anindya De, Ilias Diakonikolas, Vitaly Feldman, Rocco A. Servedio:
Nearly optimal solutions for the chow parameters problem and low-weight approximation of halfspaces. STOC 2012: 729-746 - [c20]Vitaly Feldman, Varun Kanade:
Computational Bounds on Statistical Query Learning. COLT 2012: 16.1-16.22 - [c19]Vitaly Feldman:
Learning DNF Expressions from Fourier Spectrum. COLT 2012: 17.1-17.19 - [i17]Vitaly Feldman, Elena Grigorescu, Lev Reyzin, Santosh S. Vempala:
The Complexity of Statistical Algorithms. CoRR abs/1201.1214 (2012) - [i16]Vitaly Feldman:
Learning DNF Expressions from Fourier Spectrum. CoRR abs/1203.0594 (2012) - [i15]Anindya De, Ilias Diakonikolas, Vitaly Feldman, Rocco A. Servedio:
Nearly optimal solutions for the Chow Parameters Problem and low-weight approximation of halfspaces. CoRR abs/1206.0985 (2012) - [i14]Vitaly Feldman, Elena Grigorescu, Lev Reyzin, Santosh S. Vempala, Ying Xiao:
Statistical Algorithms and a Lower Bound for Planted Clique. Electron. Colloquium Comput. Complex. 19: 64 (2012) - [i13]Anindya De, Ilias Diakonikolas, Vitaly Feldman, Rocco A. Servedio:
Nearly optimal solutions for the Chow Parameters Problem and low-weight approximation of halfspaces. Electron. Colloquium Comput. Complex. 19: 72 (2012) - 2011
- [c18]Vitaly Feldman:
Distribution-Independent Evolvability of Linear Threshold Functions. COLT 2011: 253-272 - [c17]Vitaly Feldman, Homin K. Lee, Rocco A. Servedio:
Lower Bounds and Hardness Amplification for Learning Shallow Monotone Formulas. COLT 2011: 273-292 - [i12]Vitaly Feldman:
Distribution-Independent Evolvability of Linear Threshold Functions. CoRR abs/1103.4904 (2011) - 2010
- [c16]Vitaly Feldman:
Distribution-Specific Agnostic Boosting. ICS 2010: 241-250 - [i11]Vitaly Feldman:
A Complete Characterization of Statistical Query Learning with Applications to Evolvability. CoRR abs/1002.3183 (2010) - [i10]Vitaly Feldman, Venkatesan Guruswami, Prasad Raghavendra, Yi Wu:
Agnostic Learning of Monomials by Halfspaces is Hard. CoRR abs/1012.0729 (2010) - [i9]Vitaly Feldman:
A Complete Characterization of Statistical Query Learning with Applications to Evolvability. Electron. Colloquium Comput. Complex. 17: 18 (2010) - [i8]Vitaly Feldman, Homin K. Lee, Rocco A. Servedio:
Lower Bounds and Hardness Amplification for Learning Shallow Monotone Formulas. Electron. Colloquium Comput. Complex. 17: 22 (2010) - [i7]