Papers
Spectral Ranking using Seriation
Fajwel Fogel, Alexandre d'Aspremont, Milan Vojnovic
L1-Regularized Least Squares for Support Recovery of High Dimensional Single Index Models with Gaussian Designs
Matey Neykov, Jun S. Liu, Tianxi Cai
LIBMF: A Library for Parallel Matrix Factorization in Shared-memory Systems
Wei-Sheng Chin, Bo-Wen Yuan, Meng-Yuan Yang et al.
Structure-Leveraged Methods in Breast Cancer Risk Prediction
Jun Fan, Yirong Wu, Ming Yuan et al.
Lenient Learning in Independent-Learner Stochastic Cooperative Games
Ermo Wei, Sean Luke
CVXPY: A Python-Embedded Modeling Language for Convex Optimization
Steven Diamond, Stephen Boyd
Model-free Variable Selection in Reproducing Kernel Hilbert Space
Lei Yang, Shaogao Lv, Junhui Wang
The Benefit of Multitask Representation Learning
Andreas Maurer, Massimiliano Pontil, Bernardino Romera-Paredes
Multiplicative Multitask Feature Learning
Xin Wang, Jinbo Bi, Shipeng Yu et al.
Patient Risk Stratification with Time-Varying Parameters: A Multitask Learning Approach
Jenna Wiens, John Guttag, Eric Horvitz
Latent Space Inference of Internet-Scale Networks
Qirong Ho, Junming Yin, Eric P. Xing
Iterative Regularization for Learning with Convex Loss Functions
Junhong Lin, Lorenzo Rosasco, Ding-Xuan Zhou
Scaling-up Empirical Risk Minimization: Optimization of Incomplete U-statistics
Stephan Clémençon, Igor Colin, Aurélien Bellet
Distributed Coordinate Descent Method for Learning with Big Data
Peter Richtárik, Martin Takáč
Learning Algorithms for Second-Price Auctions with Reserve
Mehryar Mohri, Andres Munoz Medina
An Emphatic Approach to the Problem of Off-policy Temporal-Difference Learning
Richard S. Sutton, A. Rupam Mahmood, Martha White
Challenges in multimodal gesture recognition
Sergio Escalera, Vassilis Athitsos, Isabelle Guyon
Exact Inference on Gaussian Graphical Models of Arbitrary Topology using Path-Sums
P.-L. Giscard, Z. Choo, S. J. Thwaite et al.
On the Characterization of a Class of Fisher-Consistent Loss Functions and its Application to Boosting
Matey Neykov, Jun S. Liu, Tianxi Cai
Compressed Gaussian Process for Manifold Regression
Rajarshi Guhaniyogi, David B. Dunson
An Information-Theoretic Analysis of Thompson Sampling
Daniel Russo, Benjamin Van Roy
Practical Kernel-Based Reinforcement Learning
André M.S. Barreto, Doina Precup, Joelle Pineau
Bayesian Policy Gradient and Actor-Critic Algorithms
Mohammad Ghavamzadeh, Yaakov Engel, Michal Valko
Stereo Matching by Training a Convolutional Neural Network to Compare Image Patches
Jure Žbontar, Yann LeCun
StructED: Risk Minimization in Structured Prediction
Yossi Adi, Joseph Keshet