Papers
Split LBI: An Iterative Regularization Path with Structural Sparsity
Chendi Huang, Xinwei Sun, Jiechao Xiong et al.
Computational and Statistical Tradeoffs in Learning to Rank
Ashish Khetan, Sewoong Oh
Probabilistic Linear Multistep Methods
Onur Teymur, Kostas Zygalakis, Ben Calderhead
Generative Shape Models: Joint Text Recognition and Segmentation with Very Little Training Data
Xinghua Lou, Ken Kansky, Wolfgang Lehrach et al.
PAC Reinforcement Learning with Rich Observations
Akshay Krishnamurthy, Alekh Agarwal, John Langford
RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanism
Edward Choi, Mohammad Taha Bahadori, Jimeng Sun et al.
Learning Tree Structured Potential Games
Vikas Garg, Tommi Jaakkola
Learning shape correspondence with anisotropic convolutional neural networks
Davide Boscaini, Jonathan Masci, Emanuele Rodolà et al.
Stochastic Multiple Choice Learning for Training Diverse Deep Ensembles
Stefan Lee, Senthil Purushwalkam Shiva Prakash, Michael Cogswell et al.
Iterative Refinement of the Approximate Posterior for Directed Belief Networks
Devon Hjelm, Ruslan Salakhutdinov, Kyunghyun Cho et al.
Sequential Neural Models with Stochastic Layers
Marco Fraccaro, Søren Kaae Sønderby, Ulrich Paquet et al.
Optimal Black-Box Reductions Between Optimization Objectives
Zeyuan Allen-Zhu, Elad Hazan
Globally Optimal Training of Generalized Polynomial Neural Networks with Nonlinear Spectral Methods
Antoine Gautier, Quynh N Nguyen, Matthias Hein
Learning Supervised PageRank with Gradient-Based and Gradient-Free Optimization Methods
Lev Bogolubsky, Pavel Dvurechenskii, Alexander Gasnikov et al.
beta-risk: a New Surrogate Risk for Learning from Weakly Labeled Data
Valentina Zantedeschi, Rémi Emonet, Marc Sebban
Unsupervised Learning of 3D Structure from Images
Danilo Jimenez Rezende, S. M. Ali Eslami, Shakir Mohamed et al.
Bootstrap Model Aggregation for Distributed Statistical Learning
JUN HAN, Qiang Liu
A Probabilistic Model of Social Decision Making based on Reward Maximization
Koosha Khalvati, Seongmin A. Park, Jean-Claude Dreher et al.
Stochastic Variance Reduction Methods for Saddle-Point Problems
Balamurugan Palaniappan, Francis Bach
Edge-exchangeable graphs and sparsity
Diana Cai, Trevor Campbell, Tamara Broderick
The Parallel Knowledge Gradient Method for Batch Bayesian Optimization
Jian Wu, Peter Frazier
Algorithms and matching lower bounds for approximately-convex optimization
Andrej Risteski, Yuanzhi Li
Quantized Random Projections and Non-Linear Estimation of Cosine Similarity
Ping Li, Michael Mitzenmacher, Martin Slawski
Density Estimation via Discrepancy Based Adaptive Sequential Partition
Dangna Li, Kun Yang, Wing Hung Wong
Hardness of Online Sleeping Combinatorial Optimization Problems
Satyen Kale, Chansoo Lee, David Pal