153 citations · 461 across the 14 of their papers we have counts for
5 papers · 1 filter
Language models are weak learners
Hariharan Manikandan, Yiding Jiang, J Zico Kolter
A central notion in practical and theoretical machine learning is that of a , classifiers that achieve better-than-random performance (on any given distribut…
On the Importance of Exploration for Generalization in Reinforcement Learning
Yiding Jiang, J. Zico Kolter, Roberta Raileanu
Existing approaches for improving generalization in deep reinforcement learning (RL) have mostly focused on representation learning, neglecting RL-specific aspects such as explorat…
On the Joint Interaction of Models, Data, and Features
Yiding Jiang, Christina Baek, J. Zico Kolter
Learning features from data is one of the defining characteristics of deep learning, but our theoretical understanding of the role features play in deep learning is still rudimenta…
Neural Functional Transformers
Allan Zhou, Kaien Yang, Yiding Jiang +5
The recent success of neural networks as implicit representation of data has driven growing interest in neural functionals: models that can process other neural networks as input b…
Permutation Equivariant Neural Functionals
Allan Zhou, Kaien Yang, Kaylee Burns +5
This work studies the design of neural networks that can process the weights or gradients of other neural networks, which we refer to as neural functional networks (NFNs). Despite…