Papers
Principal Component Projection Without Principal Component Analysis
Roy Frostig, Cameron Musco, Christopher Musco et al.
Generalization Properties and Implicit Regularization for Multiple Passes SGM
Junhong Lin, Raffaello Camoriano, Lorenzo Rosasco
Efficient Multi-Instance Learning for Activity Recognition from Time Series Data Using an Auto-Regressive Hidden Markov Model
Xinze Guan, Raviv Raich, Weng-Keen Wong
Stratified Sampling Meets Machine Learning
Edo Liberty, Kevin Lang, Konstantin Shmakov
Early and Reliable Event Detection Using Proximity Space Representation
Maxime Sangnier, Jerome Gauthier, Alain Rakotomamonjy
Towards Faster Rates and Oracle Property for Low-Rank Matrix Estimation
Huan Gui, Jiawei Han, Quanquan Gu
Robust Principal Component Analysis with Side Information
Kai-Yang Chiang, Cho-Jui Hsieh, Inderjit Dhillon
Generalized Direct Change Estimation in Ising Model Structure
Farideh Fazayeli, Arindam Banerjee
A Convex Atomic-Norm Approach to Multiple Sequence Alignment and Motif Discovery
Ian En-Hsu Yen, Xin Lin, Jiong Zhang et al.
On the Power and Limits of Distance-Based Learning
Periklis Papakonstantinou, Jia Xu, Guang Yang
Beyond Parity Constraints: Fourier Analysis of Hash Functions for Inference
Tudor Achim, Ashish Sabharwal, Stefano Ermon
Markov-modulated Marked Poisson Processes for Check-in Data
Jiangwei Pan, Vinayak Rao, Pankaj Agarwal et al.
Cross-Graph Learning of Multi-Relational Associations
Hanxiao Liu, Yiming Yang
Isotonic Hawkes Processes
Yichen Wang, Bo Xie, Nan Du et al.
Understanding and Improving Convolutional Neural Networks via Concatenated Rectified Linear Units
Wenling Shang, Kihyuk Sohn, Diogo Almeida et al.
Learning Sparse Combinatorial Representations via Two-stage Submodular Maximization
Eric Balkanski, Baharan Mirzasoleiman, Andreas Krause et al.
Hierarchical Decision Making In Electricity Grid Management
Gal Dalal, Elad Gilboa, Shie Mannor
Variational Inference for Monte Carlo Objectives
Andriy Mnih, Danilo Rezende
Sequence to Sequence Training of CTC-RNNs with Partial Windowing
Kyuyeon Hwang, Wonyong Sung
Training Deep Neural Networks via Direct Loss Minimization
Yang Song, Alexander Schwing, Richard et al.
Efficient Algorithms for Adversarial Contextual Learning
Vasilis Syrgkanis, Akshay Krishnamurthy, Robert Schapire
Discrete Deep Feature Extraction: A Theory and New Architectures
Thomas Wiatowski, Michael Tschannen, Aleksandar Stanic et al.
Data-Efficient Off-Policy Policy Evaluation for Reinforcement Learning
Philip Thomas, Emma Brunskill
Differentially Private Policy Evaluation
Borja Balle, Maziar Gomrokchi, Doina Precup
Pliable Rejection Sampling
Akram Erraqabi, Michal Valko, Alexandra Carpentier et al.