Papers
The Variational Nystrom method for large-scale spectral problems
Max Vladymyrov, Miguel Carreira-Perpinan
Towards Faster Rates and Oracle Property for Low-Rank Matrix Estimation
Huan Gui, Jiawei Han, Quanquan Gu
Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient
Tianbao Yang, Lijun Zhang, Rong Jin et al.
Train and Test Tightness of LP Relaxations in Structured Prediction
Ofer Meshi, Mehrdad Mahdavi, Adrian Weller et al.
Train faster, generalize better: Stability of stochastic gradient descent
Moritz Hardt, Ben Recht, Yoram Singer
Training Deep Neural Networks via Direct Loss Minimization
Yang Song, Alexander Schwing, Richard et al.
Training Neural Networks Without Gradients: A Scalable ADMM Approach
Gavin Taylor, Ryan Burmeister, Zheng Xu et al.
Truthful Univariate Estimators
Ioannis Caragiannis, Ariel Procaccia, Nisarg Shah
Understanding and Improving Convolutional Neural Networks via Concatenated Rectified Linear Units
Wenling Shang, Kihyuk Sohn, Diogo Almeida et al.
Unitary Evolution Recurrent Neural Networks
Martin Arjovsky, Amar Shah, Yoshua Bengio
Unsupervised Deep Embedding for Clustering Analysis
Junyuan Xie, Ross Girshick, Ali Farhadi
Uprooting and Rerooting Graphical Models
Adrian Weller
Variable Elimination in the Fourier Domain
Yexiang Xue, Stefano Ermon, Ronan Le Bras et al.
Variance-Reduced and Projection-Free Stochastic Optimization
Elad Hazan, Haipeng Luo
Variance Reduction for Faster Non-Convex Optimization
Zeyuan Allen-Zhu, Elad Hazan
Variational Inference for Monte Carlo Objectives
Andriy Mnih, Danilo Rezende
Why Most Decisions Are Easy in Tetris—And Perhaps in Other Sequential Decision Problems, As Well
Özgür Şimşek, Simón Algorta, Amit Kothiyal
Why Regularized Auto-Encoders learn Sparse Representation?
Devansh Arpit, Yingbo Zhou, Hung Ngo et al.
A Bayesian nonparametric procedure for comparing algorithms
Alessio Benavoli, Giorgio Corani, Francesca Mangili et al.
Abstraction Selection in Model-based Reinforcement Learning
Nan Jiang, Alex Kulesza, Satinder Singh
Accelerated Online Low Rank Tensor Learning for Multivariate Spatiotemporal Streams
Rose Yu, Dehua Cheng, Yan Liu
A Convex Exemplar-based Approach to MAD-Bayes Dirichlet Process Mixture Models
En-Hsu Yen, Xin Lin, Kai Zhong et al.
A Convex Optimization Framework for Bi-Clustering
Shiau Hong Lim, Yudong Chen, Huan Xu
Active Nearest Neighbors in Changing Environments
Christopher Berlind, Ruth Urner
Adaptive Belief Propagation
Georgios Papachristoudis, John Fisher