Papers
Leveraging Low-Rank Relations Between Surrogate Tasks in Structured Prediction
Giulia Luise, Dimitrios Stamos, Massimiliano Pontil et al.
High-Fidelity Image Generation With Fewer Labels
Mario Lučić, Michael Tschannen, Marvin Ritter et al.
Generalized Approximate Survey Propagation for High-Dimensional Estimation
Carlo Lucibello, Luca Saglietti, Yue Lu
CoT: Cooperative Training for Generative Modeling of Discrete Data
Sidi Lu, Lantao Yu, Siyuan Feng et al.
Optimal Algorithms for Lipschitz Bandits with Heavy-tailed Rewards
Shiyin Lu, Guanghui Wang, Yao Hu et al.
Neurally-Guided Structure Inference
Sidi Lu, Jiayuan Mao, Joshua Tenenbaum et al.
PA-GD: On the Convergence of Perturbed Alternating Gradient Descent to Second-Order Stationary Points for Structured Nonconvex Optimization
Songtao Lu, Mingyi Hong, Zhengdao Wang
Bayesian Counterfactual Risk Minimization
Ben London, Ted Sandler
Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations
Francesco Locatello, Stefan Bauer, Mario Lucic et al.
Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal Transport and Diffusions
Antoine Liutkus, Umut Simsekli, Szymon Majewski et al.
Understanding MCMC Dynamics as Flows on the Wasserstein Space
Chang Liu, Jingwei Zhuo, Jun Zhu
Understanding and Accelerating Particle-Based Variational Inference
Chang Liu, Jingwei Zhuo, Pengyu Cheng et al.
On Certifying Non-Uniform Bounds against Adversarial Attacks
Chen Liu, Ryota Tomioka, Volkan Cevher
Taming MAML: Efficient unbiased meta-reinforcement learning
Hao Liu, Richard Socher, Caiming Xiong
The Implicit Fairness Criterion of Unconstrained Learning
Lydia T. Liu, Max Simchowitz, Moritz Hardt
Data Poisoning Attacks on Stochastic Bandits
Fang Liu, Ness Shroff
Sparse Extreme Multi-label Learning with Oracle Property
Weiwei Liu, Xiaobo Shen
Rao-Blackwellized Stochastic Gradients for Discrete Distributions
Runjing Liu, Jeffrey Regier, Nilesh Tripuraneni et al.
Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers
Hong Liu, Mingsheng Long, Jianmin Wang et al.
Acceleration of SVRG and Katyusha X by Inexact Preconditioning
Yanli Liu, Fei Feng, Wotao Yin
Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations
Wu Lin, Mohammad Emtiyaz Khan, Mark Schmidt
On Efficient Optimal Transport: An Analysis of Greedy and Accelerated Mirror Descent Algorithms
Tianyi Lin, Nhat Ho, Michael Jordan
Kernel-Based Reinforcement Learning in Robust Markov Decision Processes
Shiau Hong Lim, Arnaud Autef
Inference and Sampling of K_33-free Ising Models
Valerii Likhosherstov, Yury Maximov, Misha Chertkov
Regularization in directable environments with application to Tetris
Jan Malte Lichtenberg, Özgür Şimşek