Zobrazeno 1 - 10
of 16 928
pro vyhledávání: '"Talwar, A. A."'
Autor:
Talwar, Kunal
A Private Repetition algorithm takes as input a differentially private algorithm with constant success probability and boosts it to one that succeeds with high probability. These algorithms are closely related to private metaselection algorithms that
Externí odkaz:
http://arxiv.org/abs/2410.19012
Autor:
Liu, Daogao, Talwar, Kunal
There is a gap between finding a first-order stationary point (FOSP) and a second-order stationary point (SOSP) under differential privacy constraints, and it remains unclear whether privately finding an SOSP is more challenging than finding an FOSP.
Externí odkaz:
http://arxiv.org/abs/2410.07502
We study differentially private (DP) optimization algorithms for stochastic and empirical objectives which are neither smooth nor convex, and propose methods that return a Goldstein-stationary point with sample complexity bounds that improve on exist
Externí odkaz:
http://arxiv.org/abs/2410.05880
As content generated by Large Language Model (LLM) has grown exponentially, the ability to accurately identify and fingerprint such text has become increasingly crucial. In this work, we introduce a novel black-box approach for fingerprinting LLMs, a
Externí odkaz:
http://arxiv.org/abs/2408.02871
Estimating the density of a distribution from samples is a fundamental problem in statistics. In many practical settings, the Wasserstein distance is an appropriate error metric for density estimation. For example, when estimating population densitie
Externí odkaz:
http://arxiv.org/abs/2406.19566
Autor:
Asi, Hilal, Boemer, Fabian, Genise, Nicholas, Mughees, Muhammad Haris, Ogilvie, Tabitha, Rishi, Rehan, Rothblum, Guy N., Talwar, Kunal, Tarbe, Karl, Zhu, Ruiyu, Zuliani, Marco
This paper presents Wally, a private search system that supports efficient semantic and keyword search queries against large databases. When sufficiently many clients are making queries, Wally's performance is significantly better than previous syste
Externí odkaz:
http://arxiv.org/abs/2406.06761
We study the problem of private online learning, specifically, online prediction from experts (OPE) and online convex optimization (OCO). We propose a new transformation that transforms lazy online learning algorithms into private algorithms. We appl
Externí odkaz:
http://arxiv.org/abs/2406.03620
We study the problem of private vector mean estimation in the shuffle model of privacy where $n$ users each have a unit vector $v^{(i)} \in\mathbb{R}^d$. We propose a new multi-message protocol that achieves the optimal error using $\tilde{\mathcal{O
Externí odkaz:
http://arxiv.org/abs/2404.10201
Ultra-reliable low-latency communication (URLLC) is the cornerstone for a broad range of emerging services in next-generation wireless networks. URLLC fundamentally relies on the network's ability to proactively determine whether sufficient resources
Externí odkaz:
http://arxiv.org/abs/2401.03059
Publikováno v:
International Journal of Emerging Markets, 2023, Vol. 19, Issue 11, pp. 4327-4342.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/IJOEM-03-2022-0529
