Papers
Online and Stochastic Gradient Methods for Non-decomposable Loss Functions
Purushottam Kar, Harikrishna Narasimhan, Prateek Jain
Multi-scale Graphical Models for Spatio-Temporal Processes
firdaus janoos, Huseyin Denli, Niranjan Subrahmanya
Learning Distributed Representations for Structured Output Prediction
Vivek Srikumar, Christopher D. Manning
A Boosting Framework on Grounds of Online Learning
Tofigh Naghibi Mohamadpoor, Beat Pfister
A* Sampling
Chris J Maddison, Daniel Tarlow, Tom Minka
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives
Aaron Defazio, Francis Bach, Simon Lacoste-Julien
Communication Efficient Distributed Machine Learning with the Parameter Server
Mu Li, David G Andersen, Alexander J Smola et al.
Depth Map Prediction from a Single Image using a Multi-Scale Deep Network
David Eigen, Christian Puhrsch, Rob Fergus
Stochastic Multi-Armed-Bandit Problem with Non-stationary Rewards
Omar Besbes, Yonatan Gur, Assaf Zeevi
Distributed Bayesian Posterior Sampling via Moment Sharing
Minjie Xu, Balaji Lakshminarayanan, Yee Whye Teh et al.
Learning to Optimize via Information-Directed Sampling
Daniel Russo, Benjamin Van Roy
Parallel Feature Selection Inspired by Group Testing
Yingbo Zhou, Utkarsh Porwal, Ce Zhang et al.
Submodular meets Structured: Finding Diverse Subsets in Exponentially-Large Structured Item Sets
Adarsh Prasad, Stefanie Jegelka, Dhruv Batra
Optimal Neural Codes for Control and Estimation
Alex K. Susemihl, Ron Meir, Manfred Opper
Extended and Unscented Gaussian Processes
Daniel M Steinberg, Edwin V. Bonilla
Randomized Experimental Design for Causal Graph Discovery
Huining Hu, Zhentao Li, Adrian R Vetta
Exploiting easy data in online optimization
Amir Sani, Gergely Neu, Alessandro Lazaric
Sensory Integration and Density Estimation
Joseph G Makin, Philip N. Sabes
Computing Nash Equilibria in Generalized Interdependent Security Games
Hau Chan, Luis E. Ortiz
Restricted Boltzmann machines modeling human choice
Takayuki Osogami, Makoto Otsuka
Expectation-Maximization for Learning Determinantal Point Processes
Jennifer A Gillenwater, Alex Kulesza, Emily B. Fox et al.
Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimation
Jonathan J Tompson, Arjun Jain, Yann LeCun et al.
Bayesian Inference for Structured Spike and Slab Priors
Michael R Andersen, Ole Winther, Lars K. Hansen
Deep Learning for Real-Time Atari Game Play Using Offline Monte-Carlo Tree Search Planning
Xiaoxiao Guo, Satinder Singh, Honglak Lee et al.