Papers
Learning a Prior over Intent via Meta-Inverse Reinforcement Learning
Kelvin Xu, Ellis Ratner, Anca Dragan et al.
Learning Classifiers for Target Domain with Limited or No Labels
Pengkai Zhu, Hanxiao Wang, Venkatesh Saligrama
Learning Context-dependent Label Permutations for Multi-label Classification
Jinseok Nam, Young-Bum Kim, Eneldo Loza Mencia et al.
Learning deep kernels for exponential family densities
Li Wenliang, Danica J. Sutherland, Heiko Strathmann et al.
Learning Dependency Structures for Weak Supervision Models
Paroma Varma, Frederic Sala, Ann He et al.
Learning Discrete and Continuous Factors of Data via Alternating Disentanglement
Yeonwoo Jeong, Hyun Oh Song
Learning Discrete Structures for Graph Neural Networks
Luca Franceschi, Mathias Niepert, Massimiliano Pontil et al.
Learning Distance for Sequences by Learning a Ground Metric
Bing Su, Ying Wu
Learning Fast Algorithms for Linear Transforms Using Butterfly Factorizations
Tri Dao, Albert Gu, Matthew Eichhorn et al.
Learning from a Learner
Alexis Jacq, Matthieu Geist, Ana Paiva et al.
Learning from Delayed Outcomes via Proxies with Applications to Recommender Systems
Timothy Arthur Mann, Sven Gowal, Andras Gyorgy et al.
Learning Generative Models across Incomparable Spaces
Charlotte Bunne, David Alvarez-Melis, Andreas Krause et al.
Learning Hawkes Processes Under Synchronization Noise
William Trouleau, Jalal Etesami, Matthias Grossglauser et al.
Learning interpretable continuous-time models of latent stochastic dynamical systems
Lea Duncker, Gergo Bohner, Julien Boussard et al.
Learning Latent Dynamics for Planning from Pixels
Danijar Hafner, Timothy Lillicrap, Ian Fischer et al.
Learning Linear-Quadratic Regulators Efficiently with only $\sqrtT$ Regret
Alon Cohen, Tomer Koren, Yishay Mansour
Learning Models from Data with Measurement Error: Tackling Underreporting
Roy Adams, Yuelong Ji, Xiaobin Wang et al.
Learning Neurosymbolic Generative Models via Program Synthesis
Halley Young, Osbert Bastani, Mayur Naik
Learning Novel Policies For Tasks
Yunbo Zhang, Wenhao Yu, Greg Turk
Learning Optimal Fair Policies
Razieh Nabi, Daniel Malinsky, Ilya Shpitser
Learning Optimal Linear Regularizers
Matthew Streeter
Learning Structured Decision Problems with Unawareness
Craig Innes, Alex Lascarides
Learning to bid in revenue-maximizing auctions
Thomas Nedelec, Noureddine El Karoui, Vianney Perchet
Learning to Clear the Market
Weiran Shen, Sebastien Lahaie, Renato Paes Leme
Learning to Collaborate in Markov Decision Processes
Goran Radanovic, Rati Devidze, David Parkes et al.