Papers
A Risk Comparison of Ordinary Least Squares vs Ridge Regression
Paramveer S. Dhillon, Dean P. Foster, Sham M. Kakade et al.
Conjugate Relation between Loss Functions and Uncertainty Sets in Classification Problems
Takafumi Kanamori, Akiko Takeda, Taiji Suzuki
JKernelMachines: A Simple Framework for Kernel Machines
David Picard, Nicolas Thome, Matthieu Cord
Finding Optimal Bayesian Networks Using Precedence Constraints
Pekka Parviainen, Mikko Koivisto
Multicategory Large-Margin Unified Machines
Chong Zhang, Yufeng Liu
Stochastic Variational Inference
Matthew D. Hoffman, David M. Blei, Chong Wang et al.
Regularization-Free Principal Curve Estimation
Samuel Gerber, Ross Whitaker
Random Spanning Trees and the Prediction of Weighted Graphs
Nicolò Cesa-Bianchi, Claudio Gentile, Fabio Vitale et al.
GPstuff: Bayesian Modeling with Gaussian Processes
Jarno Vanhatalo, Jaakko Riihimäki, Jouni Hartikainen et al.
Stress Functions for Nonlinear Dimension Reduction, Proximity Analysis, and Graph Drawing
Lisha Chen, Andreas Buja
Sparse Activity and Sparse Connectivity in Supervised Learning
Markus Thom, Günther Palm
Beyond Fano's Inequality: Bounds on the Optimal F-Score, BER, and Cost-Sensitive Risk and Their Implications
Ming-Jie Zhao, Narayanan Edakunni, Adam Pocock et al.
Bayesian Canonical Correlation Analysis
Arto Klami, Seppo Virtanen, Samuel Kaski
Query Induction with Schema-Guided Pruning Strategies
Joachim Niehren, Jérôme Champavère, Aurélien Lemay et al.
Truncated Power Method for Sparse Eigenvalue Problems
Xiao-Tong Yuan, Tong Zhang
A Widely Applicable Bayesian Information Criterion
Sumio Watanabe
Quasi-Newton Method: A New Direction
Philipp Hennig, Martin Kiefel
Greedy Sparsity-Constrained Optimization
Sohail Bahmani, Bhiksha Raj, Petros T. Boufounos
MLPACK: A Scalable C++ Machine Learning Library
Ryan R. Curtin, James R. Cline, N. P. Slagle et al.
Semi-Supervised Learning Using Greedy Max-Cut
Jun Wang, Tony Jebara, Shih-Fu Chang
Sparsity Regret Bounds for Individual Sequences in Online Linear Regression
Sébastien Gerchinovitz
Differential Privacy for Functions and Functional Data
Rob Hall, Alessandro Rinaldo, Larry Wasserman