Papers
Importance Sampling for Minibatches
Dominik Csiba, Peter Richtárik
Improved Asynchronous Parallel Optimization Analysis for Stochastic Incremental Methods
Remi Leblond, Fabian Pedregosa, Simon Lacoste-Julien
Improved spectral community detection in large heterogeneous networks
Hafiz TIOMOKO ALI, Romain COUILLET
Inference via Low-Dimensional Couplings
Alessio Spantini, Daniele Bigoni, Youssef Marzouk
In Search of Coherence and Consensus: Measuring the Interpretability of Statistical Topics
Fred Morstatter, Huan Liu
Interactive Algorithms: Pool, Stream and Precognitive Stream
Sivan Sabato, Tom Hess
Invariant Models for Causal Transfer Learning
Mateo Rojas-Carulla, Bernhard Schölkopf, Richard Turner et al.
Inverse Reinforcement Learning via Nonparametric Spatio-Temporal Subgoal Modeling
Adrian Šošić, Elmar Rueckert, Jan Peters et al.
KELP: a Kernel-based Learning Platform
Simone Filice, Giuseppe Castellucci, Giovanni Da San Martino et al.
Kernel Density Estimation for Dynamical Systems
Hanyuan Hang, Ingo Steinwart, Yunlong Feng et al.
Kernel Distribution Embeddings: Universal Kernels, Characteristic Kernels and Kernel Metrics on Distributions
Carl-Johann Simon-Gabriel, Bernhard Schölkopf
Kernel Method for Persistence Diagrams via Kernel Embedding and Weight Factor
Genki Kusano, Kenji Fukumizu, Yasuaki Hiraoka
Learning Certifiably Optimal Rule Lists for Categorical Data
Elaine Angelino, Nicholas Larus-Stone, Daniel Alabi et al.
Learning from Comparisons and Choices
Sahand Negahban, Sewoong Oh, Kiran K. Thekumparampil et al.
Learning Quadratic Variance Function (QVF) DAG Models via OverDispersion Scoring (ODS)
Gunwoong Park, Garvesh Raskutti
Local Rademacher Complexity-based Learning Guarantees for Multi-Task Learning
Niloofar Yousefi, Yunwen Lei, Marius Kloft et al.
Making Better Use of the Crowd: How Crowdsourcing Can Advance Machine Learning Research
Jennifer Wortman Vaughan
Markov Blanket and Markov Boundary of Multiple Variables
Xu-Qing Liu, Xin-Sheng Liu
Maximum Likelihood Estimation for Mixtures of Spherical Gaussians is NP-hard
Christopher Tosh, Sanjoy Dasgupta
Maximum Principle Based Algorithms for Deep Learning
Qianxiao Li, Long Chen, Cheng Tai et al.
Maximum Selection and Sorting with Adversarial Comparators
Jayadev Acharya, Moein Falahatgar, Ashkan Jafarpour et al.
Model-Free Trajectory-based Policy Optimization with Monotonic Improvement
Riad Akrour, Abbas Abdolmaleki, Hany Abdulsamad et al.
Mode-Seeking Clustering and Density Ridge Estimation via Direct Estimation of Density-Derivative-Ratios
Hiroaki Sasaki, Takafumi Kanamori, Aapo Hyvärinen et al.