Papers
Stay on path: PCA along graph paths
Megasthenis Asteris, Anastasios Kyrillidis, Alex Dimakis et al.
Stochastic Dual Coordinate Ascent with Adaptive Probabilities
Dominik Csiba, Zheng Qu, Peter Richtarik
Stochastic Optimization with Importance Sampling for Regularized Loss Minimization
Peilin Zhao, Tong Zhang
Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization
Yuchen Zhang, Xiao Lin
Streaming Sparse Principal Component Analysis
Wenzhuo Yang, Huan Xu
Strongly Adaptive Online Learning
Amit Daniely, Alon Gonen, Shai Shalev-Shwartz
Structural Maxent Models
Corinna Cortes, Vitaly Kuznetsov, Mehryar Mohri et al.
Submodularity in Data Subset Selection and Active Learning
Kai Wei, Rishabh Iyer, Jeff Bilmes
Subsampling Methods for Persistent Homology
Frederic Chazal, Brittany Fasy, Fabrizio Lecci et al.
Support Matrix Machines
Luo Luo, Yubo Xie, Zhihua Zhang et al.
Surrogate Functions for Maximizing Precision at the Top
Purushottam Kar, Harikrishna Narasimhan, Prateek Jain
Swept Approximate Message Passing for Sparse Estimation
Andre Manoel, Florent Krzakala, Eric Tramel et al.
Telling cause from effect in deterministic linear dynamical systems
Naji Shajarisales, Dominik Janzing, Bernhard Schoelkopf et al.
The Benefits of Learning with Strongly Convex Approximate Inference
Ben London, Bert Huang, Lise Getoor
The Composition Theorem for Differential Privacy
Peter Kairouz, Sewoong Oh, Pramod Viswanath
The Hedge Algorithm on a Continuum
Walid Krichene, Maximilian Balandat, Claire Tomlin et al.
The Kendall and Mallows Kernels for Permutations
Yunlong Jiao, Jean-Philippe Vert
The Ladder: A Reliable Leaderboard for Machine Learning Competitions
Avrim Blum, Moritz Hardt
Theory of Dual-sparse Regularized Randomized Reduction
Tianbao Yang, Lijun Zhang, Rong Jin et al.
The Power of Randomization: Distributed Submodular Maximization on Massive Datasets
Rafael Barbosa, Alina Ene, Huy Nguyen et al.
Threshold Influence Model for Allocating Advertising Budgets
Atsushi Miyauchi, Yuni Iwamasa, Takuro Fukunaga et al.
Towards a Learning Theory of Cause-Effect Inference
David Lopez-Paz, Krikamol Muandet, Bernhard Schölkopf et al.
Towards a Lower Sample Complexity for Robust One-bit Compressed Sensing
Rongda Zhu, Quanquan Gu
Tracking Approximate Solutions of Parameterized Optimization Problems over Multi-Dimensional (Hyper-)Parameter Domains
Katharina Blechschmidt, Joachim Giesen, Soeren Laue