Papers
Learning interaction rules from multi-animal trajectories via augmented behavioral models
Keisuke Fujii, Naoya Takeishi, Kazushi Tsutsui et al.
Learning Interpretable Decision Rule Sets: A Submodular Optimization Approach
Fan Yang, Kai He, Linxiao Yang et al.
Learning in two-player zero-sum partially observable Markov games with perfect recall
Tadashi Kozuno, Pierre Ménard, Remi Munos et al.
Learning Knowledge Graph-based World Models of Textual Environments
Prithviraj Ammanabrolu, Mark Riedl
Learning Large Neighborhood Search Policy for Integer Programming
Yaoxin Wu, Wen Song, Zhiguang Cao et al.
Learning latent causal graphs via mixture oracles
Bohdan Kivva, Goutham Rajendran, Pradeep K. Ravikumar et al.
Learning Markov State Abstractions for Deep Reinforcement Learning
Cameron Allen, Neev Parikh, Omer Gottesman et al.
Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Making by Reinforcement Learning
Kai Wang, Sanket Shah, Haipeng Chen et al.
Learning Models for Actionable Recourse
Alexis Ross, Himabindu Lakkaraju, Osbert Bastani
Learning Nonparametric Volterra Kernels with Gaussian Processes
Magnus Ross, Michael T Smith, Mauricio Álvarez
Learning One Representation to Optimize All Rewards
Ahmed Touati, Yann Ollivier
Learning on Random Balls is Sufficient for Estimating (Some) Graph Parameters
Takanori Maehara, Hoang NT
Learning Optimal Predictive Checklists
Haoran Zhang, Quaid D. Morris, Berk Ustun et al.
Learning Policies with Zero or Bounded Constraint Violation for Constrained MDPs
Tao Liu, Ruida Zhou, Dileep Kalathil et al.
Learning Riemannian metric for disease progression modeling
Samuel Gruffaz, Pierre-Emmanuel Poulet, Etienne Maheux et al.
Learning Robust Hierarchical Patterns of Human Brain across Many fMRI Studies
Dushyant Sahoo, Christos Davatzikos
Learning rule influences recurrent network representations but not attractor structure in decision-making tasks
Brandon McMahan, Michael Kleinman, Jonathan Kao
Learning Semantic Representations to Verify Hardware Designs
Shobha Vasudevan, Wenjie (Joe) Jiang, David Bieber et al.
Learning Signal-Agnostic Manifolds of Neural Fields
Yilun Du, Katie Collins, Josh Tenenbaum et al.
Learning Space Partitions for Path Planning
Kevin Yang, Tianjun Zhang, Chris Cummins et al.
Learning Stable Deep Dynamics Models for Partially Observed or Delayed Dynamical Systems
Andreas Schlaginhaufen, Philippe Wenk, Andreas Krause et al.
Learning State Representations from Random Deep Action-conditional Predictions
Zeyu Zheng, Vivek Veeriah, Risto Vuorio et al.
Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound
Valentina Zantedeschi, Paul Viallard, Emilie Morvant et al.
Learning Student-Friendly Teacher Networks for Knowledge Distillation
Dae Young Park, Moon-Hyun Cha, changwook jeong et al.
Learning the optimal Tikhonov regularizer for inverse problems
Giovanni S Alberti, Ernesto De Vito, Matti Lassas et al.