Papers
Compositional Morphology for Word Representations and Language Modelling
Jan Botha, Phil Blunsom
Computing Parametric Ranking Models via Rank-Breaking
Hossein Azari Soufiani, David Parkes, Lirong Xia
Concentration in unbounded metric spaces and algorithmic stability
Aryeh Kontorovich
Concept Drift Detection Through Resampling
Maayan Harel, Shie Mannor, Ran El-Yaniv et al.
Condensed Filter Tree for Cost-Sensitive Multi-Label Classification
Chun-Liang Li, Hsuan-Tien Lin
Consistency of Causal Inference under the Additive Noise Model
Samory Kpotufe, Eleni Sgouritsa, Dominik Janzing et al.
Convergence rates for persistence diagram estimation in Topological Data Analysis
Frédéric Chazal, Marc Glisse, Catherine Labruère et al.
Convex Total Least Squares
Dmitry Malioutov, Nikolai Slavov
Coordinate-descent for learning orthogonal matrices through Givens rotations
Uri Shalit, Gal Chechik
Coupled Group Lasso for Web-Scale CTR Prediction in Display Advertising
Ling Yan, Wu-Jun Li, Gui-Rong Xue et al.
Covering Number for Efficient Heuristic-based POMDP Planning
Zongzhang Zhang, David Hsu, Wee Sun Lee
DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition
Jeff Donahue, Yangqing Jia, Oriol Vinyals et al.
Deep AutoRegressive Networks
Karol Gregor, Ivo Danihelka, Andriy Mnih et al.
Deep Boosting
Corinna Cortes, Mehryar Mohri, Umar Syed
Deep Generative Stochastic Networks Trainable by Backprop
Yoshua Bengio, Eric Laufer, Guillaume Alain et al.
Deep Supervised and Convolutional Generative Stochastic Network for Protein Secondary Structure Prediction
Jian Zhou, Olga Troyanskaya
Demystifying Information-Theoretic Clustering
Greg Ver Steeg, Aram Galstyan, Fei Sha et al.
Densifying One Permutation Hashing via Rotation for Fast Near Neighbor Search
Anshumali Shrivastava, Ping Li
Deterministic Anytime Inference for Stochastic Continuous-Time Markov Processes
E. Busra Celikkaya, Christian Shelton
Deterministic Policy Gradient Algorithms
David Silver, Guy Lever, Nicolas Heess et al.
Diagnosis determination: decision trees optimizing simultaneously worst and expected testing cost
Ferdinando Cicalese, Eduardo Laber, Aline Medeiros Saettler
Dimension-free Concentration Bounds on Hankel Matrices for Spectral Learning
François Denis, Mattias Gybels, Amaury Habrard
Discovering Latent Network Structure in Point Process Data
Scott Linderman, Ryan Adams
Discrete Chebyshev Classifiers
Elad Eban, Elad Mezuman, Amir Globerson
Discriminative Features via Generalized Eigenvectors
Nikos Karampatziakis, Paul Mineiro