Papers
Latent Feature Lasso
Ian En-Hsu Yen, Wei-Cheng Lee, Sung-En Chang et al.
Latent Intention Dialogue Models
Tsung-Hsien Wen, Yishu Miao, Phil Blunsom et al.
Latent LSTM Allocation: Joint Clustering and Non-Linear Dynamic Modeling of Sequence Data
Manzil Zaheer, Amr Ahmed, Alexander J. Smola
Lazifying Conditional Gradient Algorithms
Gábor Braun, Sebastian Pokutta, Daniel Zink
Learned Optimizers that Scale and Generalize
Olga Wichrowska, Niru Maheswaranathan, Matthew W. Hoffman et al.
Learning Algorithms for Active Learning
Philip Bachman, Alessandro Sordoni, Adam Trischler
Learning Continuous Semantic Representations of Symbolic Expressions
Miltiadis Allamanis, Pankajan Chanthirasegaran, Pushmeet Kohli et al.
Learning Deep Latent Gaussian Models with Markov Chain Monte Carlo
Matthew D. Hoffman
Learning Determinantal Point Processes with Moments and Cycles
John Urschel, Victor-Emmanuel Brunel, Ankur Moitra et al.
Learning Discrete Representations via Information Maximizing Self-Augmented Training
Weihua Hu, Takeru Miyato, Seiya Tokui et al.
Learning from Clinical Judgments: Semi-Markov-Modulated Marked Hawkes Processes for Risk Prognosis
Ahmed M. Alaa, Scott Hu, Mihaela Schaar
Learning Gradient Descent: Better Generalization and Longer Horizons
Kaifeng Lv, Shunhua Jiang, Jian Li
Learning Hawkes Processes from Short Doubly-Censored Event Sequences
Hongteng Xu, Dixin Luo, Hongyuan Zha
Learning Hierarchical Features from Deep Generative Models
Shengjia Zhao, Jiaming Song, Stefano Ermon
Learning Important Features Through Propagating Activation Differences
Avanti Shrikumar, Peyton Greenside, Anshul Kundaje
Learning Infinite Layer Networks Without the Kernel Trick
Roi Livni, Daniel Carmon, Amir Globerson
Learning in POMDPs with Monte Carlo Tree Search
Sammie Katt, Frans A. Oliehoek, Christopher Amato
Learning Latent Space Models with Angular Constraints
Pengtao Xie, Yuntian Deng, Yi Zhou et al.
Learning Sleep Stages from Radio Signals: A Conditional Adversarial Architecture
Mingmin Zhao, Shichao Yue, Dina Katabi et al.
Learning Stable Stochastic Nonlinear Dynamical Systems
Jonas Umlauft, Sandra Hirche
Learning Texture Manifolds with the Periodic Spatial GAN
Urs Bergmann, Nikolay Jetchev, Roland Vollgraf
Learning the Structure of Generative Models without Labeled Data
Stephen H. Bach, Bryan He, Alexander Ratner et al.
Learning to Aggregate Ordinal Labels by Maximizing Separating Width
Guangyong Chen, Shengyu Zhang, Di Lin et al.
Learning to Align the Source Code to the Compiled Object Code
Dor Levy, Lior Wolf