Papers
DiSCO: Distributed Optimization for Self-Concordant Empirical Loss
Yuchen Zhang, Xiao Lin
Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization
Yuchen Zhang, Xiao Lin
A General Analysis of the Convergence of ADMM
Robert Nishihara, Laurent Lessard, Ben Recht et al.
Mind the duality gap: safer rules for the Lasso
Olivier Fercoq, Alexandre Gramfort, Joseph Salmon
PeakSeg: constrained optimal segmentation and supervised penalty learning for peak detection in count data
Toby Hocking, Guillem Rigaill, Guillaume Bourque
Generalization error bounds for learning to rank: Does the length of document lists matter?
Ambuj Tewari, Sougata Chaudhuri
Theory of Dual-sparse Regularized Randomized Reduction
Tianbao Yang, Lijun Zhang, Rong Jin et al.
High Dimensional Bayesian Optimisation and Bandits via Additive Models
Kirthevasan Kandasamy, Jeff Schneider, Barnabas Poczos
Telling cause from effect in deterministic linear dynamical systems
Naji Shajarisales, Dominik Janzing, Bernhard Schoelkopf et al.
A Modified Orthant-Wise Limited Memory Quasi-Newton Method with Convergence Analysis
Pinghua Gong, Jieping Ye
Dynamic Sensing: Better Classification under Acquisition Constraints
Oran Richman, Shie Mannor
Classification with Low Rank and Missing Data
Elad Hazan, Roi Livni, Yishay Mansour
Atomic Spatial Processes
Sean Jewell, Neil Spencer, Alexandre Bouchard-Côté
Accelerated Online Low Rank Tensor Learning for Multivariate Spatiotemporal Streams
Rose Yu, Dehua Cheng, Yan Liu
Functional Subspace Clustering with Application to Time Series
Mohammad Taha Bahadori, David Kale, Yingying Fan et al.
A Relative Exponential Weighing Algorithm for Adversarial Utility-based Dueling Bandits
Pratik Gajane, Tanguy Urvoy, Fabrice Clérot
Coresets for Nonparametric Estimation - the Case of DP-Means
Olivier Bachem, Mario Lucic, Andreas Krause
Optimizing Non-decomposable Performance Measures: A Tale of Two Classes
Harikrishna Narasimhan, Purushottam Kar, Prateek Jain
Surrogate Functions for Maximizing Precision at the Top
Purushottam Kar, Harikrishna Narasimhan, Prateek Jain
Abstraction Selection in Model-based Reinforcement Learning
Nan Jiang, Alex Kulesza, Satinder Singh
Finding Linear Structure in Large Datasets with Scalable Canonical Correlation Analysis
Zhuang Ma, Yichao Lu, Dean Foster
Learning Local Invariant Mahalanobis Distances
Ethan Fetaya, Shimon Ullman
Attribute Efficient Linear Regression with Distribution-Dependent Sampling
Doron Kukliansky, Ohad Shamir
An Explicit Sampling Dependent Spectral Error Bound for Column Subset Selection
Tianbao Yang, Lijun Zhang, Rong Jin et al.