p
Trivium
JMLR
- 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, Yong Zhuang, Yu-Chin Juan, Chih-Jen Lin
- Structure-Leveraged Methods in Breast Cancer Risk Prediction; Jun Fan, Yirong Wu, Ming Yuan, David Page, Jie Liu, Irene M. Ong, Peggy Peissig, Elizabeth Burnside
- 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, Jiangwen Sun, Minghu Song
- 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, D. Jaksch
- 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