Papers
Multiplicative Normalizing Flows for Variational Bayesian Neural Networks
Christos Louizos, Max Welling
Deep Transfer Learning with Joint Adaptation Networks
Mingsheng Long, Han Zhu, Jianmin Wang et al.
Learning Infinite Layer Networks Without the Kernel Trick
Roi Livni, Daniel Carmon, Amir Globerson
Gram-CTC: Automatic Unit Selection and Target Decomposition for Sequence Labelling
Hairong Liu, Zhenyao Zhu, Xiangang Li et al.
Dual Iterative Hard Thresholding: From Non-convex Sparse Minimization to Non-smooth Concave Maximization
Bo Liu, Xiao-Tong Yuan, Lezi Wang et al.
Analogical Inference for Multi-relational Embeddings
Hanxiao Liu, Yuexin Wu, Yiming Yang
Algorithmic Stability and Hypothesis Complexity
Tongliang Liu, Gábor Lugosi, Gergely Neu et al.
Iterative Machine Teaching
Weiyang Liu, Bo Dai, Ahmad Humayun et al.
Zero-Inflated Exponential Family Embeddings
Li-Ping Liu, David M. Blei
Leveraging Union of Subspace Structure to Improve Constrained Clustering
John Lipor, Laura Balzano
Exact MAP Inference by Avoiding Fractional Vertices
Erik M. Lindgren, Alexandros G. Dimakis, Adam Klivans
Convergence Analysis of Proximal Gradient with Momentum for Nonconvex Optimization
Qunwei Li, Yi Zhou, Yingbin Liang et al.
Stochastic Modified Equations and Adaptive Stochastic Gradient Algorithms
Qianxiao Li, Cheng Tai, Weinan E
Forest-type Regression with General Losses and Robust Forest
Alexander Hanbo Li, Andrew Martin
Fast k-Nearest Neighbour Search via Prioritized DCI
Ke Li, Jitendra Malik
Provably Optimal Algorithms for Generalized Linear Contextual Bandits
Lihong Li, Yu Lu, Dengyong Zhou
Provable Alternating Gradient Descent for Non-negative Matrix Factorization with Strong Correlations
Yuanzhi Li, Yingyu Liang
Dropout Inference in Bayesian Neural Networks with Alpha-divergences
Yingzhen Li, Yarin Gal
Learning to Align the Source Code to the Compiled Object Code
Dor Levy, Lior Wolf
Doubly Greedy Primal-Dual Coordinate Descent for Sparse Empirical Risk Minimization
Qi Lei, Ian En-Hsu Yen, Chao-yuan Wu et al.
Deriving Neural Architectures from Sequence and Graph Kernels
Tao Lei, Wengong Jin, Regina Barzilay et al.
Confident Multiple Choice Learning
Kimin Lee, Changho Hwang, KyoungSoo Park et al.
Bayesian inference on random simple graphs with power law degree distributions
Juho Lee, Creighton Heaukulani, Zoubin Ghahramani et al.
Coordinated Multi-Agent Imitation Learning
Hoang M. Le, Yisong Yue, Peter Carr et al.
Deep Spectral Clustering Learning
Marc T. Law, Raquel Urtasun, Richard S. Zemel