276 citations · 2k across the 138 of their papers we have counts for
7 papers · 1 filter
Improving Few-Shot Generalization by Exploring and Exploiting Auxiliary Data
Alon Albalak, Colin Raffel, William Yang Wang
Few-shot learning is valuable in many real-world applications, but learning a generalizable model without overfitting to the few labeled datapoints is challenging. In this work, we…
Offline Reinforcement Learning with Closed-Form Policy Improvement Operators
Jiachen Li, Edwin Zhang, Ming Yin +3
Behavior constrained policy optimization has been demonstrated to be a successful paradigm for tackling Offline Reinforcement Learning. By exploiting historical transitions, a poli…
Flexible Attention-Based Multi-Policy Fusion for Efficient Deep Reinforcement Learning
Zih-Yun Chiu, Yi-Lin Tuan, William Yang Wang +1
Reinforcement learning (RL) agents have long sought to approach the efficiency of human learning. Humans are great observers who can learn by aggregating external knowledge from va…
Dynamic Latent Separation for Deep Learning
Yi-Lin Tuan, Zih-Yun Chiu, William Yang Wang
A core problem in machine learning is to learn expressive latent variables for model prediction on complex data that involves multiple sub-components in a flexible and interpretabl…
Causal Balancing for Domain Generalization
Xinyi Wang, Michael Saxon, Jiachen Li +3
While machine learning models rapidly advance the state-of-the-art on various real-world tasks, out-of-domain (OOD) generalization remains a challenging problem given the vulnerabi…
Disentangled Representation Learning with Wasserstein Total Correlation
Yijun Xiao, William Yang Wang
Unsupervised learning of disentangled representations involves uncovering of different factors of variations that contribute to the data generation process. Total correlation penal…
Towards Understanding Gender Bias in Relation Extraction
Andrew Gaut, Tony Sun, Shirlyn Tang +8
Recent developments in Neural Relation Extraction (NRE) have made significant strides towards Automated Knowledge Base Construction (AKBC). While much attention has been dedicated…