Papers
Interpretable Neural Networks with Frank-Wolfe: Sparse Relevance Maps and Relevance Orderings
Jan Macdonald, Mathieu E. Besançon, Sebastian Pokutta
Interpretable Off-Policy Learning via Hyperbox Search
Daniel Tschernutter, Tobias Hatt, Stefan Feuerriegel
Interventional Contrastive Learning with Meta Semantic Regularizer
Wenwen Qiang, Jiangmeng Li, Changwen Zheng et al.
Intriguing Properties of Input-Dependent Randomized Smoothing
Peter Súkenı́k, Aleksei Kuvshinov, Stephan Günnemann
Invariant Ancestry Search
Phillip B Mogensen, Nikolaj Thams, Jonas Peters
Inverse Contextual Bandits: Learning How Behavior Evolves over Time
Alihan Hüyük, Daniel Jarrett, Mihaela van der Schaar
Investigating Generalization by Controlling Normalized Margin
Alexander R Farhang, Jeremy D Bernstein, Kushal Tirumala et al.
Investigating Why Contrastive Learning Benefits Robustness against Label Noise
Yihao Xue, Kyle Whitecross, Baharan Mirzasoleiman
Iterative Double Sketching for Faster Least-Squares Optimization
Rui Wang, Yanyan Ouyang, Wangli Xu
Iterative Hard Thresholding with Adaptive Regularization: Sparser Solutions Without Sacrificing Runtime
Kyriakos Axiotis, Maxim Sviridenko
It’s Raw! Audio Generation with State-Space Models
Karan Goel, Albert Gu, Chris Donahue et al.
Kernelized Multiplicative Weights for 0/1-Polyhedral Games: Bridging the Gap Between Learning in Extensive-Form and Normal-Form Games
Gabriele Farina, Chung-Wei Lee, Haipeng Luo et al.
Kernel Methods for Radial Transformed Compositional Data with Many Zeros
Junyoung Park, Changwon Yoon, Cheolwoo Park et al.
Kill a Bird with Two Stones: Closing the Convergence Gaps in Non-Strongly Convex Optimization by Directly Accelerated SVRG with Double Compensation and Snapshots
Yuanyuan Liu, Fanhua Shang, Weixin An et al.
Knowledge Base Question Answering by Case-based Reasoning over Subgraphs
Rajarshi Das, Ameya Godbole, Ankita Naik et al.
Knowledge-Grounded Self-Rationalization via Extractive and Natural Language Explanations
Bodhisattwa Prasad Majumder, Oana Camburu, Thomas Lukasiewicz et al.
Koopman Q-learning: Offline Reinforcement Learning via Symmetries of Dynamics
Matthias Weissenbacher, Samarth Sinha, Animesh Garg et al.
Label-Descriptive Patterns and Their Application to Characterizing Classification Errors
Michael A. Hedderich, Jonas Fischer, Dietrich Klakow et al.
Label-Free Explainability for Unsupervised Models
Jonathan Crabbé, Mihaela van der Schaar
Label Ranking through Nonparametric Regression
Dimitris Fotakis, Alkis Kalavasis, Eleni Psaroudaki
Langevin Monte Carlo for Contextual Bandits
Pan Xu, Hongkai Zheng, Eric V Mazumdar et al.
Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents
Wenlong Huang, Pieter Abbeel, Deepak Pathak et al.
Large Batch Experience Replay
Thibault Lahire, Matthieu Geist, Emmanuel Rachelson
Large-Scale Graph Neural Architecture Search
Chaoyu Guan, Xin Wang, Hong Chen et al.