JMLR

The k-means-u* algorithm: non-local jumps and greedy retries improve k-means++ clustering

Bernd Fritzke

Comments submitted to JMLR (38 pages, 36 figures, 4 algorithms)

Time for a change: a tutorial for comparing multiple classifiers through Bayesian analysis

Alessio Benavoli, Giorgio Corani, Janez Demsar, Marco Zaffalon

Comments This paper has been published in the Journal of Machine Learning Research (JMLR) vol.18, 2017

Two New Approaches to Compressed Sensing Exhibiting Both Robust Sparse Recovery and the Grouping Effect

Mehmet Eren Ahsen, Niharika Challapalli, Mathukumalli Vidyasagar

Comments 22 pages, 3 figures, to appear in the Journal of Machine Learning Research

Calibrated Multivariate Regression with Application to Neural Semantic Basis Discovery

Han Liu, Lie Wang, Tuo Zhao

Comments Journal of Machine Learning Research, 2015

Uniform Hypergraph Partitioning: Provable Tensor Methods and Sampling Techniques

Debarghya Ghoshdastidar, Ambedkar Dukkipati

Comments To appear in Journal of Machine Learning Research (vol 18)

Improving variational methods via pairwise linear response identities

Jack Raymond, Federico Ricci-Tersenghi

Comments 36 pages, 17 figures

Journal ref Journal of Machine Learning Research 18(6), 1-36, 2017

Perishability of Data: Dynamic Pricing under Varying-Coefficient Models

Adel Javanmard

Comments 30 pages, 2 figures; accepted for publication in the Journal of Machine Learning Research (JMLR)

Certifiably Optimal Low Rank Factor Analysis

Dimitris Bertsimas, Martin S. Copenhaver, Rahul Mazumder

Journal ref JMLR 18(29) (2017)

Interacting Particle Markov Chain Monte Carlo

Tom Rainforth, Christian A. Naesseth, Fredrik Lindsten, Brooks Paige, Jan-Willem van de Meent, Arnaud Doucet, Frank Wood

Journal ref JMLR W&CP 48 : 2616-2625, 2016

Optimal Policies for Observing Time Series and Related Restless Bandit Problems

Christopher R. Dance, Tomi Silander

Comments In submission to JMLR. Authors' website: http://www.xrce.xerox.com

GPU Activity Prediction using Representation Learning

Aswin Raghavan, Mohamed Amer, Timothy Shields, David Zhang, Sek Chai

Comments Proceedings of the 33 rd International Conference on Machine Learning, New York, NY, USA, 2016. JMLR: W&CP volume 48. Copyright 2016 by the author(s)

Bayesian Network Models for Adaptive Testing

Martin Plajner, Jiří Vomlel

Comments 12th Annual Bayesian Modelling Applications Workshop, Amsterdam, Netherlands, (July 2015). 10 pages

Journal ref Proc. of the Eighth International Conference on Probabilistic Graphical Models (JMLR), 2016, pages 403-414

An Empirical-Bayes Score for Discrete Bayesian Networks

Marco Scutari

Comments 12 pages, PGM 2016

Journal ref Journal of Machine Learning Research (52, Proceedings Track, PGM 2016), 438-448

Learning Nash Equilibrium for General-Sum Markov Games from Batch Data

Julien Pérolat, Florian Strub, Bilal Piot, Olivier Pietquin

Comments 20th International Conference on Artificial Intelligence and Statistics (AISTATS) 2017, Fort Lauderdale, Florida, USA. JMLR: W&CP volume 54

PMLB: A Large Benchmark Suite for Machine Learning Evaluation and Comparison

Randal S. Olson, William La Cava, Patryk Orzechowski, Ryan J. Urbanowicz, Jason H. Moore

Comments 14 pages, 5 figures, submitted for review to JMLR

An Algebraic Formalization of Forward and Forward-backward Algorithms

Ai Azuma, Masashi Shimbo, Yuji Matsumoto

Comments 55 pages, in submission to JMLR

On the Inductive Bias of Dropout

David P. Helmbold, Philip M. Long

Journal ref Journal of Machine Learning Research, 16, 3403-3454 (2015). (See http://jmlr.org/papers/volume16/helmbold15a/helmbold15a.pdf.)

How to Center Binary Deep Boltzmann Machines

Jan Melchior, Asja Fischer, Laurenz Wiskott

Comments Author list in meta data corrected - 57 pages, 17 figures, 13 tables

Journal ref Journal of Machine Learning Research, 17(99), 2016, 1:61

Online Sequence Training of Recurrent Neural Networks with Connectionist Temporal Classification

Kyuyeon Hwang, Wonyong Sung

Comments Final version: Kyuyeon Hwang and Wonyong Sung, "Sequence to Sequence Training of CTC-RNNs with Partial Windowing," Proceedings of The 33rd International Conference on Machine Learning, pp. 2178-2187, 2016. URL: http://www.jmlr.org/proceedings/papers/v48/hwanga16.html

Scalable Influence Maximization for Multiple Products in Continuous-Time Diffusion Networks

Nan Du, Yingyu Liang, Maria-Florina Balcan, Manuel Gomez-Rodriguez, Hongyuan Zha, Le Song

Comments 45 pages, to appear in Journal of Machine Learning Research. arXiv admin note: substantial text overlap with arXiv:1312.2164, arXiv:1311.3669

Distributed Sequence Memory of Multidimensional Inputs in Recurrent Networks

Adam Charles, Dong Yin, Christopher Rozell

Comments 37 pages, 3 figures

Journal ref Journal of Machine Learning Research, 18:1-37 Jan. 2017

Weak Convergence Properties of Constrained Emphatic Temporal-difference Learning with Constant and Slowly Diminishing Stepsize

Huizhen Yu

Comments Minor edits; 53 pages. Longer and more proof details than the journal version

Journal ref Journal of Machine Learning Research, 17(220):1-58, 2016

AdaCluster : Adaptive Clustering for Heterogeneous Data

Mehmet Emin Basbug, Barbara Engelhardt

Comments Submitted to JMLR on January 2017

Modelling Interactions in High-dimensional Data with Backtracking

Rajen D. Shah

Comments Identical to published version

Journal ref Journal of Machine Learning Research, 2016, 17, 207, 1-31

Bayesian Decision Process for Cost-Efficient Dynamic Ranking via Crowdsourcing

Xi Chen, Kevin Jiao, Qihang Lin

Journal ref Journal of Machine Learning Research 17 (2016) 1-40

Parsimonious Online Learning with Kernels via Sparse Projections in Function Space

Alec Koppel, Garrett Warnell, Ethan Stump, Alejandro Ribeiro

Comments Submitted to JMLR on 11/24/2016

Towards More Efficient SPSD Matrix Approximation and CUR Matrix Decomposition

Shusen Wang, Zhihua Zhang, Tong Zhang

Comments Journal of Machine Learning Research 2016

Multivariate Spearman's rho for aggregating ranks using copulas

Justin Bedo, Cheng Soon Ong

Journal ref Journal of Machine Learning Research, 17(201):1-30, 2016

Influential Node Detection in Implicit Social Networks using Multi-task Gaussian Copula Models

Qunwei Li, Bhavya Kailkhura, Jayaraman J. Thiagarajan, Zhenliang Zhang, Pramod K. Varshney

Comments NIPS 2016 Workshop, JMLR: Workshop and Conference Proceedings

fastFM: A Library for Factorization Machines

Immanuel Bayer

Comments Source Code is available at https://github.com/ibayer/fastFM

Journal ref Journal of Machine Learning Research 17, pp. 1-5 (2016)