no code implementations • 20 Dec 2022 • Mayee F. Chen, Benjamin Nachman, Frederic Sala
An important class of techniques for resonant anomaly detection in high energy physics builds models that can distinguish between reference and target datasets, where only the latter has appreciable signal.
3 code implementations • 5 Oct 2022 • Simran Arora, Avanika Narayan, Mayee F. Chen, Laurel Orr, Neel Guha, Kush Bhatia, Ines Chami, Frederic Sala, Christopher Ré
Prompting is a brittle process wherein small modifications to the prompt can cause large variations in the model predictions, and therefore significant effort is dedicated towards designing a painstakingly "perfect prompt" for a task.
Ranked #3 on Question Answering on Story Cloze
1 code implementation • Findings (ACL) 2022 • Megan Leszczynski, Daniel Y. Fu, Mayee F. Chen, Christopher Ré
Entity retrieval--retrieving information about entity mentions in a query--is a key step in open-domain tasks, such as question answering or fact checking.
1 code implementation • 15 Apr 2022 • Mayee F. Chen, Daniel Y. Fu, Avanika Narayan, Michael Zhang, Zhao Song, Kayvon Fatahalian, Christopher Ré
We first prove that adding a weighted class-conditional InfoNCE loss to SupCon controls the degree of spread.
1 code implementation • 24 Mar 2022 • Mayee F. Chen, Daniel Y. Fu, Dyah Adila, Michael Zhang, Frederic Sala, Kayvon Fatahalian, Christopher Ré
Despite the black-box nature of foundation models, we prove results characterizing how our approach improves performance and show that lift scales with the smoothness of label distributions in embedding space.
1 code implementation • 3 Mar 2021 • Mayee F. Chen, Benjamin Cohen-Wang, Stephen Mussmann, Frederic Sala, Christopher Ré
We apply our decomposition framework to three scenarios -- well-specified, misspecified, and corrected models -- to 1) choose between labeled and unlabeled data and 2) learn from their combination.
1 code implementation • 26 Jun 2020 • Mayee F. Chen, Daniel Y. Fu, Frederic Sala, Sen Wu, Ravi Teja Mullapudi, Fait Poms, Kayvon Fatahalian, Christopher Ré
Our goal is to enable machine learning systems to be trained interactively.
2 code implementations • 18 Mar 2020 • Mayee F. Chen, Miklos Z. Racz
Motivated by this reality, we introduce a simple model of network disruption where an adversary can take over a limited number of user profiles in a social network with the aim of maximizing disagreement and/or polarization in the network.
Social and Information Networks Data Structures and Algorithms Computer Science and Game Theory Physics and Society
1 code implementation • ICML 2020 • Daniel Y. Fu, Mayee F. Chen, Frederic Sala, Sarah M. Hooper, Kayvon Fatahalian, Christopher Ré
In this work, we show that, for a class of latent variable models highly applicable to weak supervision, we can find a closed-form solution to model parameters, obviating the need for iterative solutions like stochastic gradient descent (SGD).