Papers
Instance-Wise Minimax-Optimal Algorithms for Logistic Bandits
Marc Abeille, Louis Faury, Clement Calauzenes
Interpretable Random Forests via Rule Extraction
Clément Bénard, Gérard Biau, Sébastien da Veiga et al.
Iterative regularization for convex regularizers
Cesare Molinari, Mathurin Massias, Lorenzo Rosasco et al.
Kernel Distributionally Robust Optimization: Generalized Duality Theorem and Stochastic Approximation
Jia-Jie Zhu, Wittawat Jitkrittum, Moritz Diehl et al.
Kernel Interpolation for Scalable Online Gaussian Processes
Samuel Stanton, Wesley Maddox, Ian Delbridge et al.
Kernel regression in high dimensions: Refined analysis beyond double descent
Fanghui Liu, Zhenyu Liao, Johan Suykens
Large Scale K-Median Clustering for Stable Clustering Instances
Konstantin Voevodski
LassoNet: Neural Networks with Feature Sparsity
Ismael Lemhadri, Feng Ruan, Rob Tibshirani
Last iterate convergence in no-regret learning: constrained min-max optimization for convex-concave landscapes
Qi Lei, Sai Ganesh Nagarajan, Ioannis Panageas et al.
Latent Derivative Bayesian Last Layer Networks
Joe Watson, Jihao Andreas Lin, Pascal Klink et al.
Latent Gaussian process with composite likelihoods and numerical quadrature
Siddharth Ramchandran, Miika Koskinen, Harri Lähdesmäki
Latent variable modeling with random features
Gregory Gundersen, Michael Zhang, Barbara Engelhardt
Learning Bijective Feature Maps for Linear ICA
Alexander Camuto, Matthew Willetts, Chris Holmes et al.
Learning Complexity of Simulated Annealing
Avrim Blum, Chen Dan, Saeed Seddighin
Learning Contact Dynamics using Physically Structured Neural Networks
Andreas Hochlehnert, Alexander Terenin, Steindor Saemundsson et al.
Learning Fair Scoring Functions: Bipartite Ranking under ROC-based Fairness Constraints
Robin Vogel, Aurélien Bellet, Stephan Clémençon
Learning GPLVM with arbitrary kernels using the unscented transformation
Daniel de Souza, Diego Mesquita, João Paulo Gomes et al.
Learning Individually Fair Classifier with Path-Specific Causal-Effect Constraint
Yoichi Chikahara, Shinsaku Sakaue, Akinori Fujino et al.
Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation
Chen-Yu Wei, Mehdi Jafarnia Jahromi, Haipeng Luo et al.
Learning Matching Representations for Individualized Organ Transplantation Allocation
Can Xu, Ahmed Alaa, Ioana Bica et al.
Learning Partially Known Stochastic Dynamics with Empirical PAC Bayes
Manuel Haußmann, Sebastian Gerwinn, Andreas Look et al.
Learning Prediction Intervals for Regression: Generalization and Calibration
Haoxian Chen, Ziyi Huang, Henry Lam et al.
Learning Shared Subgraphs in Ising Model Pairs
Burak Varici, Saurabh Sihag, Ali Tajer
Learning Smooth and Fair Representations
Xavier Gitiaux, Huzefa Rangwala
Learning Temporal Point Processes with Intermittent Observations
Vinayak Gupta, Srikanta Bedathur, Sourangshu Bhattacharya et al.