Papers
4,025 papers found
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
Local Causal Discovery with Linear non-Gaussian Cyclic Models
Haoyue Dai, Ignavier Ng, Yujia Zheng et al.
Looping in the Human: Collaborative and Explainable Bayesian Optimization
Masaki Adachi, Brady Planden, David Howey et al.
Lower-level Duality Based Reformulation and Majorization Minimization Algorithm for Hyperparameter Optimization
He Chen, Haochen Xu, Rujun Jiang et al.
Low-rank MDPs with Continuous Action Spaces
Miruna Oprescu, Andrew Bennett, Nathan Kallus
LP-based Construction of DC Decompositions for Efficient Inference of Markov Random Fields
Chaitanya Murti, Dhruva Kashyap, Chiranjib Bhattacharyya
Making Better Use of Unlabelled Data in Bayesian Active Learning
Freddie Bickford Smith, Adam Foster, Tom Rainforth
Manifold-Aligned Counterfactual Explanations for Neural Networks
Asterios Tsiourvas, Wei Sun, Georgia Perakis
Maximum entropy GFlowNets with soft Q-learning
Sobhan Mohammadpour, Emmanuel Bengio, Emma Frejinger et al.