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Poster
Wed 17:00 Adaptive Procedural Task Generation for Hard-Exploration Problems
Kuan Fang · Yuke Zhu · Silvio Savarese · Li Fei-Fei
Poster
Tue 17:00 Drop-Bottleneck: Learning Discrete Compressed Representation for Noise-Robust Exploration
Jaekyeom Kim · Minjung Kim · Dongyeon Woo · Gunhee Kim
Poster
Mon 1:00 Temporally-Extended ε-Greedy Exploration
Will Dabney · Georg Ostrovski · Andre Barreto
Poster
Wed 9:00 Optimism in Reinforcement Learning with Generalized Linear Function Approximation
Yining Wang · Ruosong Wang · Simon Du · Akshay Krishnamurthy
Poster
Mon 9:00 Learning with AMIGo: Adversarially Motivated Intrinsic Goals
Andres Campero · Roberta Raileanu · Heinrich Kuttler · Joshua B Tenenbaum · Tim Rocktaeschel · Edward Grefenstette
Workshop
Fri 14:10 Improving Exploration in Policy Gradient Search: Application to Symbolic Optimization
Poster
Wed 9:00 Exploring the Uncertainty Properties of Neural Networks’ Implicit Priors in the Infinite-Width Limit
Ben Adlam · Jaehoon Lee · Lechao Xiao · Jeffrey Pennington · Jasper Snoek
Poster
Thu 9:00 A Mathematical Exploration of Why Language Models Help Solve Downstream Tasks
Nikunj Umesh Saunshi · Sadhika Malladi · Sanjeev Arora
Poster
Tue 1:00 Learning Subgoal Representations with Slow Dynamics
Siyuan Li · Lulu Zheng · Jianhao Wang · Chongjie Zhang
Poster
Tue 9:00 Rank the Episodes: A Simple Approach for Exploration in Procedurally-Generated Environments
Daochen Zha · Wenye Ma · Lei Yuan · Xia Hu · Ji Liu
Poster
Thu 9:00 Hierarchical Reinforcement Learning by Discovering Intrinsic Options
Jesse Zhang · Haonan Yu · Wei Xu
Workshop
Fri 6:00 Keynote 3: Ehsan Saboori. Title: Deep learning model compression using neural network design space exploration