Papers
Solving Ridge Regression using Sketched Preconditioned SVRG
Alon Gonen, Francesco Orabona, Shai Shalev-Shwartz
Gossip Dual Averaging for Decentralized Optimization of Pairwise Functions
Igor Colin, Aurelien Bellet, Joseph Salmon et al.
Ask Me Anything: Dynamic Memory Networks for Natural Language Processing
Ankit Kumar, Ozan Irsoy, Peter Ondruska et al.
On the Statistical Limits of Convex Relaxations
Zhaoran Wang, Quanquan Gu, Han Liu
Fast Constrained Submodular Maximization: Personalized Data Summarization
Baharan Mirzasoleiman, Ashwinkumar Badanidiyuru, Amin Karbasi
Texture Networks: Feed-forward Synthesis of Textures and Stylized Images
Dmitry Ulyanov, Vadim Lebedev, Andrea et al.
K-Means Clustering with Distributed Dimensions
Hu Ding, Yu Liu, Lingxiao Huang et al.
Benchmarking Deep Reinforcement Learning for Continuous Control
Yan Duan, Xi Chen, Rein Houthooft et al.
On the Analysis of Complex Backup Strategies in Monte Carlo Tree Search
Piyush Khandelwal, Elad Liebman, Scott Niekum et al.
Collapsed Variational Inference for Sum-Product Networks
Han Zhao, Tameem Adel, Geoff Gordon et al.
Distributed Clustering of Linear Bandits in Peer to Peer Networks
Nathan Korda, Balazs Szorenyi, Shuai Li
Strongly-Typed Recurrent Neural Networks
David Balduzzi, Muhammad Ghifary
False Discovery Rate Control and Statistical Quality Assessment of Annotators in Crowdsourced Ranking
QianQian Xu, Jiechao Xiong, Xiaochun Cao et al.
Factored Temporal Sigmoid Belief Networks for Sequence Learning
Jiaming Song, Zhe Gan, Lawrence Carin
Variance-Reduced and Projection-Free Stochastic Optimization
Elad Hazan, Haipeng Luo
Conservative Bandits
Yifan Wu, Roshan Shariff, Tor Lattimore et al.
Contextual Combinatorial Cascading Bandits
Shuai Li, Baoxiang Wang, Shengyu Zhang et al.
Copeland Dueling Bandit Problem: Regret Lower Bound, Optimal Algorithm, and Computationally Efficient Algorithm
Junpei Komiyama, Junya Honda, Hiroshi Nakagawa
Train faster, generalize better: Stability of stochastic gradient descent
Moritz Hardt, Ben Recht, Yoram Singer
DCM Bandits: Learning to Rank with Multiple Clicks
Sumeet Katariya, Branislav Kveton, Csaba Szepesvari et al.
A Subspace Learning Approach for High Dimensional Matrix Decomposition with Efficient Column/Row Sampling
Mostafa Rahmani, Geroge Atia
Learning to Filter with Predictive State Inference Machines
Wen Sun, Arun Venkatraman, Byron Boots et al.
Learning End-to-end Video Classification with Rank-Pooling
Basura Fernando, Stephen Gould
Learning to Generate with Memory
Chongxuan Li, Jun Zhu, Bo Zhang
Normalization Propagation: A Parametric Technique for Removing Internal Covariate Shift in Deep Networks
Devansh Arpit, Yingbo Zhou, Bhargava Kota et al.