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ORCIDMachine Learning, Volume 90
Volume 90, Number 1, January 2013
- Adriana Birlutiu
, Perry Groot, Tom Heskes:
Efficiently learning the preferences of people. 1-28 - Kanta Naito, Shinto Eguchi:
Density estimation with minimization of U-divergence. 29-57 - Kun Deng, Yaling Zheng, Chris Bourke, Stephen Scott, Julie Masciale:
New algorithms for budgeted learning. 59-90 - Mahito Sugiyama, Eiju Hirowatari, Hideki Tsuiki, Akihiro Yamamoto:
Learning figures with the Hausdorff metric by fractals - towards computable binary classification. 91-126 - Kai Ming Ting, Guang-Tong Zhou, Fei Tony Liu, Swee Chuan Tan:
Mass estimation. 127-160
Volume 90, Number 2, February 2013
- Liu Yang, Steve Hanneke, Jaime G. Carbonell:
A theory of transfer learning with applications to active learning. 161-189 - Frank Dondelinger, Sophie Lèbre, Dirk Husmeier:
Non-homogeneous dynamic Bayesian networks with Bayesian regularization for inferring gene regulatory networks with gradually time-varying structure. 191-230 - Marie Devaine, Pierre Gaillard, Yannig Goude, Gilles Stoltz:
Forecasting electricity consumption by aggregating specialized experts - A review of the sequential aggregation of specialized experts, with an application to Slovakian and French country-wide one-day-ahead (half-)hourly predictions. 231-260 - Esma Aïmeur, Gilles Brassard, Sébastien Gambs:
Quantum speed-up for unsupervised learning. 261-287 - Steven C. H. Hoi, Rong Jin, Peilin Zhao, Tianbao Yang:
Online Multiple Kernel Classification. 289-316
Volume 90, Number 3, March 2013
- João Gama, Raquel Sebastião, Pedro Pereira Rodrigues:
On evaluating stream learning algorithms. 317-346 - Koby Crammer, Claudio Gentile:
Multiclass classification with bandit feedback using adaptive regularization. 347-383 - Todd Hester, Peter Stone:
TEXPLORE: real-time sample-efficient reinforcement learning for robots. 385-429 - Takafumi Kanamori, Taiji Suzuki, Masashi Sugiyama:
Computational complexity of kernel-based density-ratio estimation: a condition number analysis. 431-460
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