Papers
Verification Based Solution for Structured MAB Problems
Zohar S Karnin
VIME: Variational Information Maximizing Exploration
Rein Houthooft, Xi Chen, Xi Chen et al.
Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks
Tianfan Xue, Jiajun Wu, Katherine Bouman et al.
Visual Question Answering with Question Representation Update (QRU)
Ruiyu Li, Jiaya Jia
Wasserstein Training of Restricted Boltzmann Machines
Grégoire Montavon, Klaus-Robert Müller, Marco Cuturi
Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks
Tim Salimans, Diederik P. Kingma
What Makes Objects Similar: A Unified Multi-Metric Learning Approach
Han-Jia Ye, De-Chuan Zhan, Xue-Min Si et al.
Yggdrasil: An Optimized System for Training Deep Decision Trees at Scale
Firas Abuzaid, Joseph K. Bradley, Feynman T Liang et al.
3D Object Proposals for Accurate Object Class Detection
Xiaozhi Chen, Kaustav Kundu, Yukun Zhu et al.
A Bayesian Framework for Modeling Confidence in Perceptual Decision Making
Koosha Khalvati, Rajesh P. Rao
Accelerated Mirror Descent in Continuous and Discrete Time
Walid Krichene, Alexandre Bayen, Peter L Bartlett
Accelerated Proximal Gradient Methods for Nonconvex Programming
Huan Li, Zhouchen Lin
A class of network models recoverable by spectral clustering
Yali Wan, Marina Meila
A Complete Recipe for Stochastic Gradient MCMC
Yi-An Ma, Tianqi Chen, Emily B. Fox
Action-Conditional Video Prediction using Deep Networks in Atari Games
Junhyuk Oh, Xiaoxiao Guo, Honglak Lee et al.
Active Learning from Weak and Strong Labelers
Chicheng Zhang, Kamalika Chaudhuri
Adaptive Low-Complexity Sequential Inference for Dirichlet Process Mixture Models
Theodoros Tsiligkaridis, Theodoros Tsiligkaridis, Keith Forsythe
Adaptive Online Learning
Dylan J Foster, Alexander Rakhlin, Karthik Sridharan
Adaptive Primal-Dual Splitting Methods for Statistical Learning and Image Processing
Tom Goldstein, Min Li, Xiaoming Yuan
Adaptive Stochastic Optimization: From Sets to Paths
Zhan Wei Lim, David Hsu, Wee Sun Lee
A Dual Augmented Block Minimization Framework for Learning with Limited Memory
Ian En-Hsu Yen, Shan-Wei Lin, Shou-De Lin
Adversarial Prediction Games for Multivariate Losses
Hong Wang, Wei Xing, Kaiser Asif et al.
A fast, universal algorithm to learn parametric nonlinear embeddings
Miguel A. Carreira-Perpinan, Max Vladymyrov