dblp: Machine Learning, Volume 105 (original) (raw)

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Volume 105, Number 1, October 2016

Special Issue on Discovery Science

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    Saso Dzeroski, Dragi Kocev, Pance Panov:
    Special issue on discovery science. 1-2
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    Prem Raj Adhikari, Anze Vavpetic, Jan Kralj, Nada Lavrac, Jaakko Hollmén:
    Explaining mixture models through semantic pattern mining and banded matrix visualization. 3-39
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    Matthijs van Leeuwen, Tijl De Bie, Eirini Spyropoulou, Cédric Mesnage:
    Subjective interestingness of subgraph patterns. 41-75
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    Eneldo Loza Mencía, Frederik Janssen:
    Learning rules for multi-label classification: a stacking and a separate-and-conquer approach. 77-126
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    Rita P. Ribeiro, Pedro Mota Pereira, João Gama:
    Sequential anomalies: a study in the Railway Industry. 127-153

Volume 105, Number 2, November 2016

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    Xiu-Shen Wei, Zhi-Hua Zhou:
    An empirical study on image bag generators for multi-instance learning. 155-198
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    Young Woong Park, Diego Klabjan:
    An aggregate and iterative disaggregate algorithm with proven optimality in machine learning. 199-232
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    Suleiman A. Khan, Eemeli Leppäaho, Samuel Kaski:
    Bayesian multi-tensor factorization. 233-253
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    Hua Mao, Yingke Chen, Manfred Jaeger, Thomas D. Nielsen, Kim G. Larsen, Brian Nielsen:
    Learning deterministic probabilistic automata from a model checking perspective. 255-299
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    Ye Zhu, Kai Ming Ting:
    Commentary: a decomposition of the outlier detection problem into a set of supervised learning problems. 301-304

Volume 105, Number 3, December 2016

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    Markus Schneider, Wolfgang Ertel, Fabio Ramos:
    Expected similarity estimation for large-scale batch and streaming anomaly detection. 305-333
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    Junichiro Hirayama, Aapo Hyvärinen, Shin Ishii:
    Sparse and low-rank matrix regularization for learning time-varying Markov networks. 335-366
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    Prashanth L. A., Mohammad Ghavamzadeh:
    Variance-constrained actor-critic algorithms for discounted and average reward MDPs. 367-417
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    Alex Foss, Marianthi Markatou, Bonnie Ray, Aliza Heching:
    A semiparametric method for clustering mixed data. 419-458
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    Erfan Soltanmohammadi, Mort Naraghi-Pour, Mihaela van der Schaar:
    Context-based unsupervised ensemble learning and feature ranking. 459-485

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