Papers
A New Algorithm and Theory for Penalized Regression-based Clustering
Chong Wu, Sunghoon Kwon, Xiaotong Shen et al.
Low-Rank Doubly Stochastic Matrix Decomposition for Cluster Analysis
Zhirong Yang, Jukka Corander, Erkki Oja
Electronic Health Record Analysis via Deep Poisson Factor Models
Ricardo Henao, James T. Lu, Joseph E. Lucas et al.
The Factorized Self-Controlled Case Series Method: An Approach for Estimating the Effects of Many Drugs on Many Outcomes
Ramin Moghaddass, Cynthia Rudin, David Madigan
fastFM: A Library for Factorization Machines
Immanuel Bayer
Learning with Differential Privacy: Stability, Learnability and the Sufficiency and Necessity of ERM Principle
Yu-Xiang Wang, Jing Lei, Stephen E. Fienberg
Jointly Informative Feature Selection Made Tractable by Gaussian Modeling
Leonidas Lefakis, François Fleuret
Consistency of Cheeger and Ratio Graph Cuts
Nicolás García Trillos, Dejan Slepčev, James von Brecht et al.
Characteristic Kernels and Infinitely Divisible Distributions
Yu Nishiyama, Kenji Fukumizu
On the Consistency of the Likelihood Maximization Vertex Nomination Scheme: Bridging the Gap Between Maximum Likelihood Estimation and Graph Matching
Vince Lyzinski, Keith Levin, Donniell E. Fishkind et al.
The Asymptotic Performance of Linear Echo State Neural Networks
Romain Couillet, Gilles Wainrib, Harry Sevi et al.
Input Output Kernel Regression: Supervised and Semi-Supervised Structured Output Prediction with Operator-Valued Kernels
Céline Brouard, Marie Szafranski, Florence d'Alché-Buc
bandicoot: a Python Toolbox for Mobile Phone Metadata
Yves-Alexandre de Montjoye, Luc Rocher, Alex Sandy Pentland
Efficient Computation of Gaussian Process Regression for Large Spatial Data Sets by Patching Local Gaussian Processes
Chiwoo Park, Jianhua Z. Huang
Online PCA with Optimal Regret
Jiazhong Nie, Wojciech Kotlowski, Manfred K. Warmuth
Semiparametric Mean Field Variational Bayes: General Principles and Numerical Issues
David Rohde, Matt P. Wand
Feature-Level Domain Adaptation
Wouter M. Kouw, Laurens J.P. van der Maaten, Jesse H. Krijthe et al.
mlr: Machine Learning in R
Bernd Bischl, Michel Lang, Lars Kotthoff et al.
Bounding the Search Space for Global Optimization of Neural Networks Learning Error: An Interval Analysis Approach
Stavros P. Adam, George D. Magoulas, Dimitrios A. Karras et al.
Stable Graphical Models
Navodit Misra, Ercan E. Kuruoglu
Support Vector Hazards Machine: A Counting Process Framework for Learning Risk Scores for Censored Outcomes
Yuanjia Wang, Tianle Chen, Donglin Zeng
Joint Structural Estimation of Multiple Graphical Models
Jing Ma, George Michailidis
Double or Nothing: Multiplicative Incentive Mechanisms for Crowdsourcing
Nihar B. Shah, Dengyong Zhou
Optimal Estimation of Derivatives in Nonparametric Regression
Wenlin Dai, Tiejun Tong, Marc G. Genton