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Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors
BERT, and GPT models show GRACE's state-of-the-art performance in making
On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks
Based on our definitions, we identify and analyze six real-world benchmarks spanning from homophilic to heterophilic link prediction settings, with graphs containing up to 30M edges.
Doob's Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling
To solve this optimization, we propose a simulation-free training objective with a model parameterization that imposes the desired boundary conditions by design.
Online Performative Gradient Descent for Learning Nash Equilibria in Decision-Dependent Games Zihan Zhu Duke University Ethan X. Fang Duke University Zhuoran Yang Yale University
We focus on finding the Nash equilibrium of decision-dependent games in the bandit feedback setting.
Fast Exact Leverage Score Sampling from Khatri-Rao Products with Applications to Tensor Decomposition
As a result, it tractably draws samples even when the matrices forming the Khatri-Rao product have tens of millions of rows each.
78ed45281dd746a265fff16ff75a02e5-Paper-Conference.pdf
Unfortunately, these theoretical results cannot well explain the empirical successes of deep learning well, as they require the model size tobenolargerthan O(n)(thegeneralization boundsbecomevacuousotherwise).