6 citations · 13 across the 6 of their papers we have counts for
5 papers · 1 filter
Decision Transformer under Random Frame Dropping
Kaizhe Hu, Ray Chen Zheng, Yang Gao +1
Controlling agents remotely with deep reinforcement learning~(DRL) in the real world is yet to come. One crucial stepping stone is to devise RL algorithms that are robust in the fa…
Differentiable Architecture Pruning for Transfer Learning
Nicolo Colombo, Yang Gao
We propose a new gradient-based approach for extracting sub-architectures from a given large model. Contrarily to existing pruning methods, which are unable to disentangle the netw…
Adapting by Pruning: A Case Study on BERT
Yang Gao, Nicolo Colombo, Wei Wang
Adapting pre-trained neural models to downstream tasks has become the standard practice for obtaining high-quality models. In this work, we propose a novel model adaptation paradig…
Mutual Information State Intrinsic Control
Rui Zhao, Yang Gao, Pieter Abbeel +2
Reinforcement learning has been shown to be highly successful at many challenging tasks. However, success heavily relies on well-shaped rewards. Intrinsically motivated RL attempts…
Disentangling Neural Architectures and Weights: A Case Study in Supervised Classification
Nicolo Colombo, Yang Gao
The history of deep learning has shown that human-designed problem-specific networks can greatly improve the classification performance of general neural models. In most practical…