|
Workshop
|
|
A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning
Zixiang Chen · Chris Junchi Li · Angela Yuan · Quanquan Gu · Michael Jordan
|
|
|
Poster
|
Tue 14:00
|
Causal Inference with Non-IID Data using Linear Graphical Models
Chi Zhang · Karthika Mohan · Judea Pearl
|
|
|
Workshop
|
|
Are Deep Sequence Classifiers Good at Non-Trivial Generalization?
Francesco Cazzaro · Ariadna Quattoni · Xavier Carreras
|
|
|
Poster
|
Wed 9:00
|
Global Linear and Local Superlinear Convergence of IRLS for Non-Smooth Robust Regression
Liangzu Peng · Christian Kümmerle · Rene Vidal
|
|
|
Workshop
|
|
Near-Optimal Deployment Efficiency in Reward-Free Reinforcement Learning with Linear Function Approximation
Dan Qiao · Yu-Xiang Wang
|
|
|
Poster
|
Tue 9:00
|
Biologically plausible solutions for spiking networks with efficient coding
Veronika Koren · Stefano Panzeri
|
|
|
Poster
|
Tue 9:00
|
NSNet: A General Neural Probabilistic Framework for Satisfiability Problems
Zhaoyu Li · Xujie Si
|
|
|
Poster
|
Wed 9:00
|
Change-point Detection for Sparse and Dense Functional Data in General Dimensions
Carlos Misael Madrid Padilla · Daren Wang · Zifeng Zhao · Yi Yu
|
|
|
Poster
|
Tue 9:00
|
Improving Zero-Shot Generalization in Offline Reinforcement Learning using Generalized Similarity Functions
Bogdan Mazoure · Ilya Kostrikov · Ofir Nachum · Jonathan Tompson
|
|
|
Poster
|
Tue 9:00
|
Spectral Bias in Practice: The Role of Function Frequency in Generalization
Sara Fridovich-Keil · Raphael Gontijo Lopes · Rebecca Roelofs
|
|
|
Workshop
|
|
A general framework for reward function distances
Erik Jenner · Joar Skalse · Adam Gleave
|
|
|
Poster
|
Wed 9:00
|
Rethinking Value Function Learning for Generalization in Reinforcement Learning
Seungyong Moon · JunYeong Lee · Hyun Oh Song
|
|
