Papers
Leverage the Average: an Analysis of KL Regularization in Reinforcement Learning
Nino Vieillard, Tadashi Kozuno, Bruno Scherrer et al.
Liberty or Depth: Deep Bayesian Neural Nets Do Not Need Complex Weight Posterior Approximations
Sebastian Farquhar, Lewis Smith, Yarin Gal
Lifelong Policy Gradient Learning of Factored Policies for Faster Training Without Forgetting
Jorge Mendez, Boyu Wang, Eric Eaton
Lightweight Generative Adversarial Networks for Text-Guided Image Manipulation
Bowen Li, Xiaojuan Qi, Philip Torr et al.
Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder
Zhisheng Xiao, Qing Yan, Yali Amit
Limits on Testing Structural Changes in Ising Models
Aditya Gangrade, Bobak Nazer, Venkatesh Saligrama
Limits to Depth Efficiencies of Self-Attention
Yoav Levine, Noam Wies, Or Sharir et al.
Linear Disentangled Representations and Unsupervised Action Estimation
Matthew Painter, Adam Prugel-Bennett, Jonathon Hare
Linearly Converging Error Compensated SGD
Eduard Gorbunov, Dmitry Kovalev, Dmitry Makarenko et al.
Linear-Sample Learning of Low-Rank Distributions
Ayush Jain, Alon Orlitsky
Linear Time Sinkhorn Divergences using Positive Features
Meyer Scetbon, Marco Cuturi
Lipschitz Bounds and Provably Robust Training by Laplacian Smoothing
Vishaal Krishnan, Abed AlRahman Al Makdah, Fabio Pasqualetti
Lipschitz-Certifiable Training with a Tight Outer Bound
Sungyoon Lee, Jaewook Lee, Saerom Park
List-Decodable Mean Estimation via Iterative Multi-Filtering
Ilias Diakonikolas, Daniel Kane, Daniel Kongsgaard
Listening to Sounds of Silence for Speech Denoising
Ruilin Xu, Rundi Wu, Yuko Ishiwaka et al.
Locally-Adaptive Nonparametric Online Learning
Ilja Kuzborskij, Nicolò Cesa-Bianchi
Locally Differentially Private (Contextual) Bandits Learning
Kai Zheng, Tianle Cai, Weiran Huang et al.
Locally private non-asymptotic testing of discrete distributions is faster using interactive mechanisms
Thomas Berrett, Cristina Butucea
LoCo: Local Contrastive Representation Learning
Yuwen Xiong, Mengye Ren, Raquel Urtasun
Logarithmic Pruning is All You Need
Laurent Orseau, Marcus Hutter, Omar Rivasplata
Logarithmic Regret Bound in Partially Observable Linear Dynamical Systems
Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi et al.
Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment
Ben Usman, Avneesh Sud, Nick Dufour et al.
Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors
Karl Pertsch, Oleh Rybkin, Frederik Ebert et al.