269 citations · 443 across the 19 of their papers we have counts for
4 papers · 1 filter
Gym-RTS: Toward Affordable Full Game Real-time Strategy Games Research with Deep Reinforcement Learning
Shengyi Huang, Santiago Ontañón, Chris Bamford +1
In recent years, researchers have achieved great success in applying Deep Reinforcement Learning (DRL) algorithms to Real-time Strategy (RTS) games, creating strong autonomous agen…
Regression Oracles and Exploration Strategies for Short-Horizon Multi-Armed Bandits
Robert C. Gray, Jichen Zhu, Santiago Ontañón
This paper explores multi-armed bandit (MAB) strategies in very short horizon scenarios, i.e., when the bandit strategy is only allowed very few interactions with the environment.…
Big Bird: Transformers for Longer Sequences
Manzil Zaheer, Guru Guruganesh, Avinava Dubey +8
Transformers-based models, such as BERT, have been one of the most successful deep learning models for NLP. Unfortunately, one of their core limitations is the quadratic dependency…
ETC: Encoding Long and Structured Inputs in Transformers
Joshua Ainslie, Santiago Ontanon, Chris Alberti +7
Transformer models have advanced the state of the art in many Natural Language Processing (NLP) tasks. In this paper, we present a new Transformer architecture, Extended Transforme…