Papers
Finding Linear Structure in Large Datasets with Scalable Canonical Correlation Analysis
Zhuang Ma, Yichao Lu, Dean Foster
Fixed-point algorithms for learning determinantal point processes
Zelda Mariet, Suvrit Sra
Following the Perturbed Leader for Online Structured Learning
Alon Cohen, Tamir Hazan
From Word Embeddings To Document Distances
Matt Kusner, Yu Sun, Nicholas Kolkin et al.
Functional Subspace Clustering with Application to Time Series
Mohammad Taha Bahadori, David Kale, Yingying Fan et al.
Gated Feedback Recurrent Neural Networks
Junyoung Chung, Caglar Gulcehre, Kyunghyun Cho et al.
Generalization error bounds for learning to rank: Does the length of document lists matter?
Ambuj Tewari, Sougata Chaudhuri
Generative Moment Matching Networks
Yujia Li, Kevin Swersky, Rich Zemel
Geometric Conditions for Subspace-Sparse Recovery
Chong You, Rene Vidal
Global Convergence of Stochastic Gradient Descent for Some Non-convex Matrix Problems
Christopher De Sa, Christopher Re, Kunle Olukotun
Gradient-based Hyperparameter Optimization through Reversible Learning
Dougal Maclaurin, David Duvenaud, Ryan Adams
Guaranteed Tensor Decomposition: A Moment Approach
Gongguo Tang, Parikshit Shah
Harmonic Exponential Families on Manifolds
Taco Cohen, Max Welling
Hashing for Distributed Data
Cong Leng, Jiaxiang Wu, Jian Cheng et al.
HawkesTopic: A Joint Model for Network Inference and Topic Modeling from Text-Based Cascades
Xinran He, Theodoros Rekatsinas, James Foulds et al.
Hidden Markov Anomaly Detection
Nico Goernitz, Mikio Braun, Marius Kloft
High Confidence Policy Improvement
Philip Thomas, Georgios Theocharous, Mohammad Ghavamzadeh
High Dimensional Bayesian Optimisation and Bandits via Additive Models
Kirthevasan Kandasamy, Jeff Schneider, Barnabas Poczos
How Can Deep Rectifier Networks Achieve Linear Separability and Preserve Distances?
Senjian An, Farid Boussaid, Mohammed Bennamoun
How Hard is Inference for Structured Prediction?
Amir Globerson, Tim Roughgarden, David Sontag et al.
Improved Regret Bounds for Undiscounted Continuous Reinforcement Learning
K. Lakshmanan, Ronald Ortner, Daniil Ryabko
Inference in a Partially Observed Queuing Model with Applications in Ecology
Kevin Winner, Garrett Bernstein, Dan Sheldon
Inferring Graphs from Cascades: A Sparse Recovery Framework
Jean Pouget-Abadie, Thibaut Horel
Information Geometry and Minimum Description Length Networks
Ke Sun, Jun Wang, Alexandros Kalousis et al.