96 citations · 444 across the 23 of their papers we have counts for
27 papers
TwHIN-BERT: A Socially-Enriched Pre-trained Language Model for Multilingual Tweet Representations at Twitter
Xinyang Zhang, Yury Malkov, Omar Florez +4
Pre-trained language models (PLMs) are fundamental for natural language processing applications. Most existing PLMs are not tailored to the noisy user-generated text on social medi…
The Symmetric Generalized Eigenvalue Problem as a Nash Equilibrium
Ian Gemp, Charlie Chen, Brian McWilliams
The symmetric generalized eigenvalue problem (SGEP) is a fundamental concept in numerical linear algebra. It captures the solution of many classical machine learning problems such…
Pushing the limits of self-supervised ResNets: Can we outperform supervised learning without labels on ImageNet?
Nenad Tomasev, Ioana Bica, Brian McWilliams +4
Despite recent progress made by self-supervised methods in representation learning with residual networks, they still underperform supervised learning on the ImageNet classificatio…
EigenGame Unloaded: When playing games is better than optimizing
Ian Gemp, Brian McWilliams, Claire Vernade +1
We build on the recently proposed EigenGame that views eigendecomposition as a competitive game. EigenGame's updates are biased if computed using minibatches of data, which hinders…
Representation Learning via Invariant Causal Mechanisms
Jovana Mitrovic, Brian McWilliams, Jacob Walker +2
Self-supervised learning has emerged as a strategy to reduce the reliance on costly supervised signal by pretraining representations only using unlabeled data. These methods combin…
EigenGame: PCA as a Nash Equilibrium
Ian Gemp, Brian McWilliams, Claire Vernade +1
We present a novel view on principal component analysis (PCA) as a competitive game in which each approximate eigenvector is controlled by a player whose goal is to maximize their…