Papers
Bayesian Sampling Using Stochastic Gradient Thermostats
Nan Ding, Youhan Fang, Ryan Babbush et al.
Robust Kernel Density Estimation by Scaling and Projection in Hilbert Space
Robert A Vandermeulen, Clayton Scott
Multiscale Fields of Patterns
Pedro Felzenszwalb, John G Oberlin
Learning Mixed Multinomial Logit Model from Ordinal Data
Sewoong Oh, Devavrat Shah
Stochastic Gradient Descent, Weighted Sampling, and the Randomized Kaczmarz algorithm
Deanna Needell, Rachel Ward, Nati Srebro
Conditional Random Field Autoencoders for Unsupervised Structured Prediction
Waleed Ammar, Chris Dyer, Noah A. Smith
Smoothed Gradients for Stochastic Variational Inference
Stephan Mandt, David Blei
Probabilistic Differential Dynamic Programming
Yunpeng Pan, Evangelos Theodorou
A State-Space Model for Decoding Auditory Attentional Modulation from MEG in a Competing-Speaker Environment
Sahar Akram, Jonathan Z Simon, Shihab A Shamma et al.
Do Deep Nets Really Need to be Deep?
Jimmy Ba, Rich Caruana
Model-based Reinforcement Learning and the Eluder Dimension
Ian Osband, Benjamin Van Roy
Iterative Neural Autoregressive Distribution Estimator NADE-k
Tapani Raiko, Yao Li, Kyunghyun Cho et al.
Scale Adaptive Blind Deblurring
Haichao Zhang, Jianchao Yang
Subspace Embeddings for the Polynomial Kernel
Haim Avron, Huy Nguyen, David Woodruff
Modeling Deep Temporal Dependencies with Recurrent Grammar Cells""
Vincent Michalski, Roland Memisevic, Kishore Konda
Fast Training of Pose Detectors in the Fourier Domain
João F. Henriques, Pedro Martins, Rui F Caseiro et al.
Convolutional Neural Network Architectures for Matching Natural Language Sentences
Baotian Hu, Zhengdong Lu, Hang Li et al.
Advances in Learning Bayesian Networks of Bounded Treewidth
Siqi Nie, Denis D. Maua, Cassio P de Campos et al.
Nonparametric Bayesian inference on multivariate exponential families
William R Vega-Brown, Marek Doniec, Nicholas G Roy
Ranking via Robust Binary Classification
Hyokun Yun, Parameswaran Raman, S. Vishwanathan
Fast and Robust Least Squares Estimation in Corrupted Linear Models
Brian McWilliams, Gabriel Krummenacher, Mario Lucic et al.
Global Belief Recursive Neural Networks
Romain Paulus, Richard Socher, Christopher D. Manning
Accelerated Mini-batch Randomized Block Coordinate Descent Method
Tuo Zhao, Mo Yu, Yiming Wang et al.
Mind the Nuisance: Gaussian Process Classification using Privileged Noise
Daniel Hernández-lobato, Viktoriia Sharmanska, Kristian Kersting et al.
Optimization Methods for Sparse Pseudo-Likelihood Graphical Model Selection
Sang Oh, Onkar Dalal, Kshitij Khare et al.