Papers
Robust Sparse Regression under Adversarial Corruption
Yudong Chen, Constantine Caramanis, Shie Mannor
Exact Rule Learning via Boolean Compressed Sensing
Dmitry Malioutov, Kush Varshney
Computation-Risk Tradeoffs for Covariance-Thresholded Regression
Dinah Shender, John Lafferty
Sparse PCA through Low-rank Approximations
Dimitris Papailiopoulos, Alexandros Dimakis, Stavros Korokythakis
A PAC-Bayesian Approach for Domain Adaptation with Specialization to Linear Classifiers
Pascal Germain, Amaury Habrard, François Laviolette et al.
Infinite Markov-Switching Maximum Entropy Discrimination Machines
Sotirios Chatzis
On autoencoder scoring
Hanna Kamyshanska, Roland Memisevic
LDA Topic Model with Soft Assignment of Descriptors to Words
Daphna Weinshall, Gal Levi, Dmitri Hanukaev
On learning parametric-output HMMs
Aryeh Kontorovich, Boaz Nadler, Roi Weiss
Sharp Generalization Error Bounds for Randomly-projected Classifiers
Robert Durrant, Ata Kaban
ABC Reinforcement Learning
Christos Dimitrakakis, Nikolaos Tziortziotis
Better Rates for Any Adversarial Deterministic MDP
Ofer Dekel, Elad Hazan
Modeling Information Propagation with Survival Theory
Manuel Gomez-Rodriguez, Jure Leskovec, Bernhard Schölkopf
Factorial Multi-Task Learning : A Bayesian Nonparametric Approach
Sunil Gupta, Dinh Phung, Svetha Venkatesh
Analogy-preserving Semantic Embedding for Visual Object Categorization
Sung Ju Hwang, Kristen Grauman, Fei Sha
Spectral Learning of Hidden Markov Models from Dynamic and Static Data
Tzu-Kuo Huang, Jeff Schneider
Online Kernel Learning with a Near Optimal Sparsity Bound
Lijun Zhang, Jinfeng Yi, Rong Jin et al.
Topic Model Diagnostics: Assessing Domain Relevance via Topical Alignment
Jason Chuang, Sonal Gupta, Christopher Manning et al.
On the Statistical Consistency of Algorithms for Binary Classification under Class Imbalance
Aditya Menon, Harikrishna Narasimhan, Shivani Agarwal et al.
Quickly Boosting Decision Trees – Pruning Underachieving Features Early
Ron Appel, Thomas Fuchs, Piotr Dollar et al.
A Unified Robust Regression Model for Lasso-like Algorithms
Wenzhuo Yang, Huan Xu
Infinite Positive Semidefinite Tensor Factorization for Source Separation of Mixture Signals
Kazuyoshi Yoshii, Ryota Tomioka, Daichi Mochihashi et al.
Revisiting the Nystrom method for improved large-scale machine learning
Alex Gittens, Michael Mahoney
Dynamic Covariance Models for Multivariate Financial Time Series
Yue Wu, Jose Miguel Hernandez-Lobato, Ghahramani Zoubin