Papers
Learning-Based Algorithms for Graph Searching Problems
Adela F. DePavia, Erasmo Tani, Ali Vakilian
Learning Cartesian Product Graphs with Laplacian Constraints
Changhao Shi, Gal Mishne
Learning Extensive-Form Perfect Equilibria in Two-Player Zero-Sum Sequential Games
Martino Bernasconi, Alberto Marchesi, Francesco Trovò
Learning Fair Division from Bandit Feedback
Hakuei Yamada, Junpei Komiyama, Kenshi Abe et al.
Learning Granger Causality from Instance-wise Self-attentive Hawkes Processes
Dongxia Wu, Tsuyoshi Ide, Georgios Kollias et al.
Learning Latent Partial Matchings with Gumbel-IPF Networks
Hedda Cohen Indelman, Tamir Hazan
Learning multivariate temporal point processes via the time-change theorem
Guilherme Augusto Zagatti, See Kiong Ng, Stéphane Bressan
Learning Populations of Preferences via Pairwise Comparison Queries
Gokcan Tatli, Yi Chen, Ramya Korlakai Vinayak
Learning Safety Constraints from Demonstrations with Unknown Rewards
David Lindner, Xin Chen, Sebastian Tschiatschek et al.
Learning Sampling Policy to Achieve Fewer Queries for Zeroth-Order Optimization
Zhou Zhai, Wanli Shi, Heng Huang et al.
Learning Sparse Codes with Entropy-Based ELBOs
Dmytro Velychko, Simon Damm, Asja Fischer et al.
Learning the Pareto Set Under Incomplete Preferences: Pure Exploration in Vector Bandits
Efe Mert Karagözlü, Yaşar Cahit Yıldırım, Cağın Ararat et al.
Learning to Defer to a Population: A Meta-Learning Approach
Dharmesh Tailor, Aditya Patra, Rajeev Verma et al.
Learning to Rank for Optimal Treatment Allocation Under Resource Constraints
Fahad Kamran, Maggie Makar, Jenna Wiens
Learning to Solve the Constrained Most Probable Explanation Task in Probabilistic Graphical Models
Shivvrat Arya, Tahrima Rahman, Vibhav Gogate
Learning Under Random Distributional Shifts
Kirk C. Bansak, Elisabeth Paulson, Dominik Rothenhaeusler
Learning Unknown Intervention Targets in Structural Causal Models from Heterogeneous Data
Yuqin Yang, Saber Salehkaleybar, Negar Kiyavash
Length independent PAC-Bayes bounds for Simple RNNs
Volodimir Mitarchuk, Clara Lacroce, Rémi Eyraud et al.
Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks
Hristo Papazov, Scott Pesme, Nicolas Flammarion
Leveraging Ensemble Diversity for Robust Self-Training in the Presence of Sample Selection Bias
Ambroise Odonnat, Vasilii Feofanov, Ievgen Redko
Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures
Paul Viallard, Rémi Emonet, Amaury Habrard et al.
Lexicographic Optimization: Algorithms and Stability
Jacob A. Abernethy, Robert Schapire, Umar Syed
Linear Convergence of Black-Box Variational Inference: Should We Stick the Landing?
Kyurae Kim, Yian Ma, Jacob Gardner