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Machine Learning, Volume 106
Volume 106, Number 1, January 2017
- Mohamed Hamza Ibrahim
, Christopher Joseph Pal, Gilles Pesant:
Improving probabilistic inference in graphical models with determinism and cycles. 1-54 - Kai Ming Ting, Takashi Washio, Jonathan R. Wells, Sunil Aryal
Defying the gravity of learning curve: a characteristic of nearest neighbour anomaly detectors. 55-91 - Vitaly Kuznetsov, Mehryar Mohri:
Generalization bounds for non-stationary mixing processes. 93-117 - Olivier Wintenberger:
Optimal learning with Bernstein online aggregation. 119-141 - Deiner Mena, Elena Montañés, José Ramón Quevedo, Juan José del Coz
A family of admissible heuristics for A* to perform inference in probabilistic classifier chains. 143-169
Volume 106, Number 2, February 2017
- Ilja Kuzborskij, Francesco Orabona
Fast rates by transferring from auxiliary hypotheses. 171-195 - Aline Paes
On the use of stochastic local search techniques to revise first-order logic theories from examples. 197-241 - Ashwin Srinivasan, Michael Bain:
An empirical study of on-line models for relational data streams. 243-276 - Amol Pande, Liang Li, Jeevanantham Rajeswaran, John Ehrlinger, Udaya B. Kogalur, Eugene Blackstone, Hemant Ishwaran
Boosted multivariate trees for longitudinal data. 277-305 - Masayuki Karasuyama, Hiroshi Mamitsuka
Adaptive edge weighting for graph-based learning algorithms. 307-335
Volume 106, Number 3, March 2017
- Jinlong Huang, Qingsheng Zhu, Lijun Yang, Dongdong Cheng, Quanwang Wu:
QCC: a novel clustering algorithm based on Quasi-Cluster Centers. 337-357 - Pedro Ribeiro Mendes Júnior
Nearest neighbors distance ratio open-set classifier. 359-386 - Dongwoo Kim
Hierarchical Dirichlet scaling process. 387-418 - Jie Shen, Huan Xu
Online optimization for max-norm regularization. 419-457
Volume 106, Number 4, April 2017
- Geoffrey Holmes, Tie-Yan Liu, Hang Li, Irwin King
Introduction: special issue of selected papers from ACML 2015. 459-461 - Marthinus Christoffel du Plessis, Gang Niu, Masashi Sugiyama
Class-prior estimation for learning from positive and unlabeled data. 463-492 - Inbal Horev
Geometry-aware principal component analysis for symmetric positive definite matrices. 493-522 - Shaowu Liu
Preference Relation-based Markov Random Fields for Recommender Systems. 523-546 - Shaowu Liu, Gang Li
Erratum to: Preference Relation-based Markov Random Fields for Recommender Systems. 547 - Wojciech Kotlowski
Surrogate regret bounds for generalized classification performance metrics. 549-572 - Fei Yu, Min-Ling Zhang
Maximum margin partial label learning. 573-593 - Yiu-ming Cheung
Proximal average approximated incremental gradient descent for composite penalty regularized empirical risk minimization. 595-622
Volume 106, Number 5, May 2017
- Robert J. Durrant, Kee-Eung Kim, Geoffrey Holmes, Stephen Marsland, Masashi Sugiyama
Foreword: special issue for the journal track of the 8th Asian conference on machine learning (ACML 2016). 623-625 - Qi Mao, Li Wang
A unified probabilistic framework for robust manifold learning and embedding. 627-650 - Chenghao Liu, Tao Jin
Collaborative topic regression for online recommender systems: an online and Bayesian approach. 651-670 - Yuping Wu, Hsuan-Tien Lin:
Progressive random k-labelsets for cost-sensitive multi-label classification. 671-694 - Sen Yang, Lijun Zhang
Non-redundant multiple clustering by nonnegative matrix factorization. 695-712 - Sahely Bhadra
Multi-view kernel completion. 713-739
Volume 106, Number 6, June 2017
- Nathalie Japkowicz
Special issue on discovery science. 741-743 - Aljaz Osojnik
Multi-label classification via multi-target regression on data streams. 745-770 - Pawel Matuszyk, Myra Spiliopoulou:
Stream-based semi-supervised learning for recommender systems. 771-798 - Morteza Zihayat, Yan Chen, Aijun An
Memory-adaptive high utility sequential pattern mining over data streams. 799-836 - Mohammed Ghesmoune, Hanene Azzag, Salima Benbernou, Mustapha Lebbah, Tarn Duong
Big Data: from collection to visualization. 837-862 - Simon Cousins
High-probability minimax probability machines. 863-886 - Carlos Eduardo Cancino Chacón
An evaluation of linear and non-linear models of expressive dynamics in classical piano and symphonic music. 887-909 - Daniel Berrar
Confidence curves: an alternative to null hypothesis significance testing for the comparison of classifiers. 911-949
Volume 106, Number 7, July 2017
- Arkajyoti Saha, Swagatam Das
Feature-weighted clustering with inner product induced norm based dissimilarity measures: an optimization perspective. 951-992 - Jesse H. Krijthe
Projected estimators for robust semi-supervised classification. 993-1008 - Shinya Suzumura, Kohei Ogawa, Masashi Sugiyama
Homotopy continuation approaches for robust SV classification and regression. 1009-1038 - Dimitris Bertsimas, Jack Dunn:
Optimal classification trees. 1039-1082 - Ran Tian
The mechanism of additive composition. 1083-1130
Volume 106, Number 8, August 2017
- Céline Rouveirol, Ruggero G. Pensa, Rushed Kanawati:
Introduction to the special issue on dynamic networks and knowledge discovery. 1131-1132 - Venkata M. V. Gunturi
Scalable computational techniques for centrality metrics on temporally detailed social network. 1133-1169 - Mehdi Kaytoue
Exceptional contextual subgraph mining. 1171-1211 - Giulio Rossetti
Tiles: an online algorithm for community discovery in dynamic social networks. 1213-1241
Volume 106, Numbers 9-10, October 2017
- Kurt Driessens
Introduction to the special issue dedicated to the Journal Track of ECML PKDD 2017. 1243-1244 - Michele Donini
Learning deep kernels in the space of dot product polynomials. 1245-1269 - Tijana Vujicic, Jesse Glass, Fang Zhou, Zoran Obradovic:
Gaussian conditional random fields extended for directed graphs. 1271-1288 - Nayyar Abbas Zaidi
Efficient parameter learning of Bayesian network classifiers. 1289-1329 - Lavanya Sita Tekumalla, Vaibhav Rajan
Vine copulas for mixed data : multi-view clustering for mixed data beyond meta-Gaussian dependencies. 1331-1357 - Björn Weghenkel
Graph-based predictable feature analysis. 1359-1380 - Beilun Wang, Ritambhara Singh, Yanjun Qi:
A constrained $$\ell $$ ℓ 1 minimization approach for estimating multiple sparse Gaussian or nonparanormal graphical models. 1381-1417 - Matthias Bussas, Christoph Sawade, Nicolas Kühn, Tobias Scheffer, Niels Landwehr
Varying-coefficient models for geospatial transfer learning. 1419-1440 - Samuel Kolb, Sergey Paramonov
Learning constraints in spreadsheets and tabular data. 1441-1468 - Heitor Murilo Gomes
Adaptive random forests for evolving data stream classification. 1469-1495 - Toon van Craenendonck
Constraint-based clustering selection. 1497-1521 - Sebastijan Dumancic
An expressive dissimilarity measure for relational clustering using neighbourhood trees. 1523-1545 - Douglas de O. Cardoso
Weightless neural networks for open set recognition. 1547-1567 - Devin Schwab
Offline reinforcement learning with task hierarchies. 1569-1598 - Pedram Daee, Tomi Peltola, Marta Soare, Samuel Kaski:
Knowledge elicitation via sequential probabilistic inference for high-dimensional prediction. 1599-1620 - Stephan Mandt
Sparse probit linear mixed model. 1621-1642 - Matthew J. Holland, Kazushi Ikeda:
Robust regression using biased objectives. 1643-1679 - NhatHai Phan, Xintao Wu
Preserving differential privacy in convolutional deep belief networks. 1681-1704 - Herke van Hoof
Generalized exploration in policy search. 1705-1724 - Kuan-Hao Huang
Cost-sensitive label embedding for multi-label classification. 1725-1746 - Alon Zweig
Group online adaptive learning. 1747-1770
Volume 106, Number 11, November 2017
- Michael Grabchak, Zhiyi Zhang:
Asymptotic properties of Turing's formula in relative error. 1771-1785 - Junyu Xuan
A Bayesian nonparametric model for multi-label learning. 1787-1815 - Giorgio Corani
Statistical comparison of classifiers through Bayesian hierarchical modelling. 1817-1837 - Masanori Kawakita
A note on model selection for small sample regression. 1839-1862
Volume 106, Number 12, December 2017
- Katsumi Inoue
Special issue on inductive logic programming. 1863-1865 - Sergey Paramonov
Relational data factorization. 1867-1904 - Davide Nitti
Planning in hybrid relational MDPs. 1905-1932 - Francesco Orsini
kProbLog: an algebraic Prolog for machine learning. 1933-1969 - Golnoosh Farnadi
Soft quantification in statistical relational learning. 1971-1991
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