111 citations · 154 across the 6 of their papers we have counts for
6 papers
Hindsight Task Relabelling: Experience Replay for Sparse Reward Meta-RL
Charles Packer, Pieter Abbeel, Joseph E. Gonzalez
Meta-reinforcement learning (meta-RL) has proven to be a successful framework for leveraging experience from prior tasks to rapidly learn new related tasks, however, current meta-R…
Contingencies from Observations: Tractable Contingency Planning with Learned Behavior Models
Nicholas Rhinehart, Jeff He, Charles Packer +4
Humans have a remarkable ability to make decisions by accurately reasoning about future events, including the future behaviors and states of mind of other agents. Consider driving…
Assessing Generalization in Deep Reinforcement Learning
Charles Packer, Katelyn Gao, Jernej Kos +3
Deep reinforcement learning (RL) has achieved breakthrough results on many tasks, but agents often fail to generalize beyond the environment they were trained in. As a result, deep…
Visually-Aware Personalized Recommendation using Interpretable Image Representations
Charles Packer, Julian McAuley, Arnau Ramisa
Visually-aware recommender systems use visual signals present in the underlying data to model the visual characteristics of items and users' preferences towards them. In the domain…
GraphZip: Dictionary-based Compression for Mining Graph Streams
Charles A. Packer, Lawrence B. Holder
A massive amount of data generated today on platforms such as social networks, telecommunication networks, and the internet in general can be represented as graph streams. Activity…
Learning Compatibility Across Categories for Heterogeneous Item Recommendation
Ruining He, Charles Packer, Julian McAuley
Identifying relationships between items is a key task of an online recommender system, in order to help users discover items that are functionally complementary or visually compati…