Zobrazeno 1 - 10
of 162
pro vyhledávání: '"KAIROUZ, PETER"'
Autor:
Bian, Christopher, Cheu, Albert, Chiknavaryan, Stanislav, Gong, Zoe, Gruteser, Marco, Guinan, Oliver, Guzman, Yannis, Kairouz, Peter, Lagzdin, Artem, McKenna, Ryan, Ni, Grace, Roth, Edo, Spivak, Maya, Van Overveldt, Timon, Yi, Ren
This paper introduces Mayfly, a federated analytics approach enabling aggregate queries over ephemeral on-device data streams without central persistence of sensitive user data. Mayfly minimizes data via on-device windowing and contribution bounding
Externí odkaz:
http://arxiv.org/abs/2412.07962
Autor:
Cooper, A. Feder, Choquette-Choo, Christopher A., Bogen, Miranda, Jagielski, Matthew, Filippova, Katja, Liu, Ken Ziyu, Chouldechova, Alexandra, Hayes, Jamie, Huang, Yangsibo, Mireshghallah, Niloofar, Shumailov, Ilia, Triantafillou, Eleni, Kairouz, Peter, Mitchell, Nicole, Liang, Percy, Ho, Daniel E., Choi, Yejin, Koyejo, Sanmi, Delgado, Fernando, Grimmelmann, James, Shmatikov, Vitaly, De Sa, Christopher, Barocas, Solon, Cyphert, Amy, Lemley, Mark, boyd, danah, Vaughan, Jennifer Wortman, Brundage, Miles, Bau, David, Neel, Seth, Jacobs, Abigail Z., Terzis, Andreas, Wallach, Hanna, Papernot, Nicolas, Lee, Katherine
We articulate fundamental mismatches between technical methods for machine unlearning in Generative AI, and documented aspirations for broader impact that these methods could have for law and policy. These aspirations are both numerous and varied, mo
Externí odkaz:
http://arxiv.org/abs/2412.06966
Recent advances in differentially private federated learning (DPFL) algorithms have found that using correlated noise across the rounds of federated learning (DP-FTRL) yields provably and empirically better accuracy than using independent noise (DP-S
Externí odkaz:
http://arxiv.org/abs/2410.11368
Autor:
Daly, Katharine, Eichner, Hubert, Kairouz, Peter, McMahan, H. Brendan, Ramage, Daniel, Xu, Zheng
Federated Learning (FL) is a machine learning technique that enables multiple entities to collaboratively learn a shared model without exchanging their local data. Over the past decade, FL systems have achieved substantial progress, scaling to millio
Externí odkaz:
http://arxiv.org/abs/2410.08892
In this paper, we investigate potential randomization approaches that can complement current practices of input-based methods (such as licensing data and prompt filtering) and output-based methods (such as recitation checker, license checker, and mod
Externí odkaz:
http://arxiv.org/abs/2408.13278
Autor:
Bian, Christopher, Cheu, Albert, Guzman, Yannis, Gruteser, Marco, Kairouz, Peter, McKenna, Ryan, Roth, Edo
Environmental Insights Explorer (EIE) is a Google product that reports aggregate statistics about human mobility, including various methods of transit used by people across roughly 50,000 regions globally. These statistics are used to estimate carbon
Externí odkaz:
http://arxiv.org/abs/2407.03496
Autor:
Triantafillou, Eleni, Kairouz, Peter, Pedregosa, Fabian, Hayes, Jamie, Kurmanji, Meghdad, Zhao, Kairan, Dumoulin, Vincent, Junior, Julio Jacques, Mitliagkas, Ioannis, Wan, Jun, Hosoya, Lisheng Sun, Escalera, Sergio, Dziugaite, Gintare Karolina, Triantafillou, Peter, Guyon, Isabelle
We present the findings of the first NeurIPS competition on unlearning, which sought to stimulate the development of novel algorithms and initiate discussions on formal and robust evaluation methodologies. The competition was highly successful: nearl
Externí odkaz:
http://arxiv.org/abs/2406.09073
Autor:
Bagdasarian, Eugene, Yi, Ren, Ghalebikesabi, Sahra, Kairouz, Peter, Gruteser, Marco, Oh, Sewoong, Balle, Borja, Ramage, Daniel
The growing use of large language model (LLM)-based conversational agents to manage sensitive user data raises significant privacy concerns. While these agents excel at understanding and acting on context, this capability can be exploited by maliciou
Externí odkaz:
http://arxiv.org/abs/2405.05175
We study $L_2$ mean estimation under central differential privacy and communication constraints, and address two key challenges: firstly, existing mean estimation schemes that simultaneously handle both constraints are usually optimized for $L_\infty
Externí odkaz:
http://arxiv.org/abs/2405.02341
The vocabulary of language models in Gboard, Google's keyboard application, plays a crucial role for improving user experience. One way to improve the vocabulary is to discover frequently typed out-of-vocabulary (OOV) words on user devices. This task
Externí odkaz:
http://arxiv.org/abs/2404.11607