JMLR

Linear Dimensionality Reduction: Survey, Insights, and Generalizations

John P. Cunningham, Zoubin Ghahramani

Comments 42 pages, 5 figures, 1 table

Journal ref Journal of Machine Learning Research. 16(Dec): 2859-2900, 2015

Mutual Conditional Independence and its Applications to Inference in Markov Networks

Niharika Gauraha

Comments Submitted to JMLR on 02 Apr 2015

Spectral Ranking using Seriation

Fajwel Fogel, Alexandre d'Aspremont, Milan Vojnovic

Comments Substantially revised. Accepted by JMLR

Deep Clustered Convolutional Kernels

Minyoung Kim, Luca Rigazio

Comments draft

Journal ref JMLR: Workshop and Conference Proceedings 44 (2015) 160-172

Learning the Structure and Parameters of Large-Population Graphical Games from Behavioral Data

Jean Honorio, Luis Ortiz

Comments Journal of Machine Learning Research. (accepted, pending publication.) Last conference version: submitted March 30, 2012 to UAI 2012. First conference version: entitled, Learning Influence Games, initially submitted on June 1, 2010 to NIPS 2010

Journal ref Journal of Machine Learning Research (JMLR), 16(Jul):1249--1274, 2015

Fast Cross-Validation via Sequential Testing

Tammo Krueger, Danny Panknin, Mikio Braun

Journal ref Journal of Machine Learning Research, 16:1103-1155, 2015

Image Denoising with Kernels based on Natural Image Relations

Valero Laparra, Juan Gutiérrez, Gustavo Camps-Valls, Jesús Malo

Journal ref Journal of Machine Learning Research 11: 873-903 (2010)

Manopt, a Matlab toolbox for optimization on manifolds

Nicolas Boumal, Bamdev Mishra, P. -A. Absil, Rodolphe Sepulchre

Journal ref The Journal of Machine Learning Research, 15(1), 1455-1459 (2014)

Perturbed Message Passing for Constraint Satisfaction Problems

Siamak Ravanbakhsh, Russell Greiner

Journal ref JMLR 16(Jul):1249-1274, 2015

Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models

Michael U. Gutmann, Jukka Corander

Comments In press with the Journal of Machine Learning Research (JMLR). Accepted August 17, 2015

Nonparametric Bayesian Factor Analysis for Dynamic Count Matrices

Ayan Acharya, Joydeep Ghosh, Mingyuan Zhou

Comments Appeared in Artificial Intelligence and Statistics (AISTATS), May 2015. The ArXiv version fixes a typo in (8), the equation right above Section 3.2 in Page 4 of http://www.jmlr.org/proceedings/papers/v38/acharya15.pdf

Large-Scale Optimization Algorithms for Sparse Conditional Gaussian Graphical Models

Calvin McCarter, Seyoung Kim

Comments 11 pages, 7 figures. Appearing in Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS) 2016, Cadiz, Spain. JMLR: W&CP volume 41

A Deep Generative Deconvolutional Image Model

Yunchen Pu, Xin Yuan, Andrew Stevens, Chunyuan Li, Lawrence Carin

Comments 10 pages, 7 figures. Appearing in Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS) 2016, Cadiz, Spain. JMLR: W&CP volume 41

Concave Penalized Estimation of Sparse Gaussian Bayesian Networks

Bryon Aragam, Qing Zhou

Comments 57 pages

Journal ref Journal of Machine Learning Research 16(Nov):2273-2328, 2015

Modular Autoencoders for Ensemble Feature Extraction

Henry W J Reeve, Gavin Brown

Comments 18 pages, 8 figures, to appear in a special issue of The Journal Of Machine Learning Research (vol.44, Dec 2015)

Extremal Mechanisms for Local Differential Privacy

Peter Kairouz, Sewoong Oh, Pramod Viswanath

Comments 52 pages, 10 figures in JMLR 2015

A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights

Weijie Su, Stephen Boyd, Emmanuel J. Candes

Comments To appear in Journal of Machine Learning Research. Added more simulation studies. Preliminary version appeared in NIPS 2014

On the Statistical Efficiency of $\ell_{1,p}$ Multi-Task Learning of Gaussian Graphical Models

Jean Honorio, Tommi Jaakkola, Dimitris Samaras

Comments Submitted on October 21, 2015 to the Journal of Machine Learning Research

Characterizing predictable classes of processes

Daniil Ryabko

Comments This is a duplicate submission of 0905.4341, made by UAI foundation who had the brilliant idea of flooding arxiv with UAI papers 5 years after the conference, without checking whether these papers were already submitted to arxiv or at least asking the authors. Great job, UAI! The journal (extended) version appears in JMLR, 11: 581-602, 2010; also as arXiv:0912.4883

Online Tensor Methods for Learning Latent Variable Models

Furong Huang, U. N. Niranjan, Mohammad Umar Hakeem, Animashree Anandkumar

Comments JMLR 2014

Real-time data analysis at the LHC: present and future

Vladimir V. Gligorov

Comments Contribution to the proceedings of the HEPML workshop NIPS 2014. 20 pages, 5 figures

Journal ref Published in JMLR Volume 42, p. 1-18, 2015

Quantifying Uncertainty in Random Forests via Confidence Intervals and Hypothesis Tests

Lucas Mentch, Giles Hooker

Comments To appear in The Journal of Machine Learning Research

On Graphical Models via Univariate Exponential Family Distributions

Eunho Yang, Pradeep Ravikumar, Genevera I. Allen, Zhandong Liu

Comments Journal of Machine Learning Research

Convex Calibration Dimension for Multiclass Loss Matrices

Harish G. Ramaswamy, Shivani Agarwal

Comments Accepted to JMLR, pending editing

Risk Bounds for the Majority Vote: From a PAC-Bayesian Analysis to a Learning Algorithm

Pascal Germain, Alexandre Lacasse, François Laviolette, Mario Marchand, Jean-Francis Roy

Comments Published in JMLR http://jmlr.org/papers/v16/germain15a.html

Journal ref Journal of Machine Learning Research 2015, vol. 16, p. 787-860

A New Approach to Probabilistic Programming Inference

Frank Wood, Jan Willem van de Meent, Vikash Mansinghka

Comments Updated version of the 2014 AISTATS paper (to reflect changes in new language syntax). 10 pages, 3 figures. Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, JMLR Workshop and Conference Proceedings, Vol 33, 2014

Adding vs. Averaging in Distributed Primal-Dual Optimization

Chenxin Ma, Virginia Smith, Martin Jaggi, Michael I. Jordan, Peter Richtárik, Martin Takáč

Comments ICML 2015: JMLR W&CP volume37, Proceedings of The 32nd International Conference on Machine Learning, pp. 1973-1982

A Chaining Algorithm for Online Nonparametric Regression

Pierre Gaillard, Sébastien Gerchinovitz

Comments Published in the proceedings of COLT 2015: http://jmlr.org/proceedings/papers/v40/Gaillard15.html

Scalable Nonparametric Bayesian Inference on Point Processes with Gaussian Processes

Yves-Laurent Kom Samo, Stephen Roberts

Comments To appear at the International Conference on Machine Learning (ICML), 2015

Journal ref JMLR W&CP, vol 37, 2015

JUMP-Means: Small-Variance Asymptotics for Markov Jump Processes

Jonathan H. Huggins, Karthik Narasimhan, Ardavan Saeedi, Vikash K. Mansinghka

Comments In Proceedings of the 32nd International Conference on Machine Learning (ICML 2015)

Journal ref JMLR: W&CP Volume 37, 2015 pp. 693-701