Education
Scaling Laws in Linear Regression: Compute, Parameters, and Data
From the perspective of statistical learning theory, (1) is rather intriguing. Moreover, they do not provide instance-wise matching lower bounds to verify the tightness of the upper bounds.
On the Limitations of Fractal Dimension as a Measure of Generalization Charlie B. Tan University of Oxford Inรฉs Garcรญa-Redondo Imperial College London Qiquan Wang
Bounding and predicting the generalization gap of overparameterized neural networks remains a central open problem in theoretical machine learning. There is a recent and growing body of literature that proposes the framework of fractals to model optimization trajectories of neural networks, motivating generalization bounds and measures based on the fractal dimension of the trajectory. Notably, the persistent homology dimension has been proposed to correlate with the generalization gap.
ODRL: A Benchmark for Off-Dynamics Reinforcement Learning
Human beings are able to transfer the policies swiftly to a structurally similar task.
Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models Pan Lu
This title draws inspiration from the chameleon's ability to adapt and blend into its surroundings, which parallels
