Vitaly Feldman
53 papers · 2002–2026 · 6 venues · across top CS/AI venues
This profile combines several different researchers. Authors are keyed by name, and this name's papers fall into 27 separate collaboration groups - the largest holds only 30% of them. Pick the group below that matches the researcher you mean. How a shared name is split.
Achievements are not shown for a combined profile - each one describes a single researcher's record, which this is not.
Which Vitaly Feldman?
6 groups of papers that share co-authors internally but none with each other - each most likely a different researcher. Pick one to see its papers.
with Kunal Talwar, Hilal Asi, Tomer Koren
16 papers
· 2019–2025
· ICML, NeurIPS, AISTATS
Hide ▲
Local Pan-privacy for Federated Analytics
ICML 2025
Faster Convergence with MultiWay Preferences
AISTATS 2024
Instance-Optimal Private Density Estimation in the Wasserstein Distance
NeurIPS 2024
Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages
ICML 2024
Private and Personalized Frequency Estimation in a Federated Setting
NeurIPS 2024
Fast Optimal Locally Private Mean Estimation via Random Projections
NeurIPS 2023
Near-Optimal Algorithms for Private Online Optimization in the Realizable Regime
ICML 2023
Private Online Prediction from Experts: Separations and Faster Rates
COLT 2023
Mean Estimation with User-level Privacy under Data Heterogeneity
NeurIPS 2022
Optimal Algorithms for Mean Estimation under Local Differential Privacy
ICML 2022
Private frequency estimation via projective geometry
ICML 2022
Subspace Recovery from Heterogeneous Data with Non-isotropic Noise
NeurIPS 2022
Lossless Compression of Efficient Private Local Randomizers
ICML 2021
Private Stochastic Convex Optimization: Optimal Rates in L1 Geometry
ICML 2021
Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses
NeurIPS 2020
Private Stochastic Convex Optimization with Optimal Rates
NeurIPS 2019
21 papers whose co-authors appear nowhere else under this name
Invited Open Problem: Is the Power of Deep Learning over Linear Models Inherently Distribution Dependent?
COLT 2026
Trade-offs in Data Memorization via Strong Data Processing Inequalities
COLT 2025
Algorithmic Learning Theory 2021: Preface
ALT 2021
Individual Privacy Accounting via a Rényi Filter
NeurIPS 2021
PAC learning with stable and private predictions
COLT 2020
What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation
NeurIPS 2020
The Everlasting Database: Statistical Validity at a Fair Price
NeurIPS 2018
A General Characterization of the Statistical Query Complexity
COLT 2017
Dealing with Range Anxiety in Mean Estimation via Statistical Queries
ALT 2017
Conference on Learning Theory 2016: Preface
COLT 2016
Generalization of ERM in Stochastic Convex Optimization: The Dimension Strikes Back
NeurIPS 2016
Subsampled Power Iteration: a Unified Algorithm for Block Models and Planted CSP's
NeurIPS 2015
Open Problem: The Statistical Query Complexity of Learning Sparse Halfspaces
COLT 2014
Sample Complexity Bounds on Differentially Private Learning via Communication Complexity
COLT 2014
Statistical Active Learning Algorithms
NeurIPS 2013
Learning DNF Expressions from Fourier Spectrum
COLT 2012
Distribution-Independent Evolvability of Linear Threshold Functions
COLT 2011
Lower Bounds and Hardness Amplification for Learning Shallow Monotone Formulas
COLT 2011
On The Power of Membership Queries in Agnostic Learning
JMLR 2009
Attribute-Efficient and Non-adaptive Learning of Parities and DNF Expressions
JMLR 2007
On Using Extended Statistical Queries to Avoid Membership Queries
JMLR 2002