Papers
Algorithms for the Hard Pre-Image Problem of String Kernels and the General Problem of String Prediction
Sébastien Giguère, Amélie Rolland, Francois Laviolette et al.
Low-Rank Matrix Recovery from Row-and-Column Affine Measurements
Or Zuk, Avishai Wagner
Entropic Graph-based Posterior Regularization
Maxwell Libbrecht, Michael Hoffman, Jeff Bilmes et al.
Feature-Budgeted Random Forest
Feng Nan, Joseph Wang, Venkatesh Saligrama
Adding vs. Averaging in Distributed Primal-Dual Optimization
Chenxin Ma, Virginia Smith, Martin Jaggi et al.
Variational Generative Stochastic Networks with Collaborative Shaping
Philip Bachman, Doina Precup
Submodularity in Data Subset Selection and Active Learning
Kai Wei, Rishabh Iyer, Jeff Bilmes
Bayesian Multiple Target Localization
Purnima Rajan, Weidong Han, Raphael Sznitman et al.
The Kendall and Mallows Kernels for Permutations
Yunlong Jiao, Jean-Philippe Vert
On Symmetric and Asymmetric LSHs for Inner Product Search
Behnam Neyshabur, Nathan Srebro
Causal Inference by Identification of Vector Autoregressive Processes with Hidden Components
Philipp Geiger, Kun Zhang, Bernhard Schoelkopf et al.
Preference Completion: Large-scale Collaborative Ranking from Pairwise Comparisons
Dohyung Park, Joe Neeman, Jin Zhang et al.
Discovering Temporal Causal Relations from Subsampled Data
Mingming Gong, Kun Zhang, Bernhard Schoelkopf et al.
Trust Region Policy Optimization
John Schulman, Sergey Levine, Pieter Abbeel et al.
Bipartite Edge Prediction via Transductive Learning over Product Graphs
Hanxiao Liu, Yiming Yang
Active Nearest Neighbors in Changing Environments
Christopher Berlind, Ruth Urner
Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks
Jose Miguel Hernandez-Lobato, Ryan Adams
Convex Calibrated Surrogates for Hierarchical Classification
Harish Ramaswamy, Ambuj Tewari, Shivani Agarwal
Robust Estimation of Transition Matrices in High Dimensional Heavy-tailed Vector Autoregressive Processes
Huitong Qiu, Sheng Xu, Fang Han et al.
Hidden Markov Anomaly Detection
Nico Goernitz, Mikio Braun, Marius Kloft
Scalable Deep Poisson Factor Analysis for Topic Modeling
Zhe Gan, Changyou Chen, Ricardo Henao et al.
Variational Inference for Gaussian Process Modulated Poisson Processes
Chris Lloyd, Tom Gunter, Michael Osborne et al.
Scalable Variational Inference in Log-supermodular Models
Josip Djolonga, Andreas Krause
Community Detection Using Time-Dependent Personalized PageRank
Haim Avron, Lior Horesh