12 papers
Wally: Batched Private Nearest Neighbor Search at Scale
Hilal Asi, Fabian Boemer, Nicholas Genise +8
We present Wally, a batched private nearest-neighbor search protocol that uses differential privacy to break the linear computation barrier of fully-oblivious schemes. In Tiptoe, t…
Cram Less to Fit More: Training Data Pruning Improves Memorization of Facts
Jiayuan Ye, Vitaly Feldman, Kunal Talwar
Large language models (LLMs) can struggle to memorize factual knowledge in their parameters, often leading to hallucinations and poor performance on knowledge-intensive tasks. In t…
Enabling Differentially Private Federated Learning for Speech Recognition: Benchmarks, Adaptive Optimizers and Gradient Clipping
Martin Pelikan, Sheikh Shams Azam, Vitaly Feldman +4
While federated learning (FL) and differential privacy (DP) have been extensively studied, their application to automatic speech recognition (ASR) remains largely unexplored due to…
PREAMBLE: Private and Efficient Aggregation via Block Sparse Vectors
Hilal Asi, Vitaly Feldman, Hannah Keller +2
We revisit the problem of secure aggregation of high-dimensional vectors in a two-server system such as Prio. These systems are typically used to aggregate vectors such as gradient…
Improved Sample Complexity for Private Nonsmooth Nonconvex Optimization
Guy Kornowski, Daogao Liu, Kunal Talwar
We study differentially private (DP) optimization algorithms for stochastic and empirical objectives which are neither smooth nor convex, and propose methods that return a Goldstei…
Instance-Optimality for Private KL Distribution Estimation
Jiayuan Ye, Vitaly Feldman, Kunal Talwar
We study the fundamental problem of estimating an unknown discrete distribution over symbols, given i.i.d. samples from the distribution. We are interested in minimizin…