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Publication search results
found 17 matches
- 2013
- Nicola Barbieri, Giuseppe Manco
, Ettore Ritacco
, Marco Carnuccio, Antonio Bevacqua:
Probabilistic topic models for sequence data. Mach. Learn. 93(1): 5-29 (2013) - Hendrik Blockeel
, Kristian Kersting, Siegfried Nijssen
, Filip Zelezný
:
Guest editor's introduction: special issue of the ECML PKDD 2013 journal track. Mach. Learn. 93(1): 1-3 (2013) - Mathieu Blondel, Kazuhiro Seki, Kuniaki Uehara:
Block coordinate descent algorithms for large-scale sparse multiclass classification. Mach. Learn. 93(1): 31-52 (2013) - Kai Brügge, Asja Fischer
, Christian Igel:
The flip-the-state transition operator for restricted Boltzmann machines. Mach. Learn. 93(1): 53-69 (2013) - Róbert Busa-Fekete, Balázs Kégl, Tamás Éltetö, György Szarvas:
Tune and mix: learning to rank using ensembles of calibrated multi-class classifiers. Mach. Learn. 93(2-3): 261-292 (2013) - Clément Calauzènes, Nicolas Usunier, Patrick Gallinari:
Calibration and regret bounds for order-preserving surrogate losses in learning to rank. Mach. Learn. 93(2-3): 227-260 (2013) - Salvatore Corrente, Salvatore Greco, Milosz Kadzinski
, Roman Slowinski
:
Robust ordinal regression in preference learning and ranking. Mach. Learn. 93(2-3): 381-422 (2013) - Maurizio Filippone
, Mingjun Zhong, Mark A. Girolami
:
A comparative evaluation of stochastic-based inference methods for Gaussian process models. Mach. Learn. 93(1): 93-114 (2013) - Mihajlo Grbovic, Nemanja Djuric, Shengbo Guo, Slobodan Vucetic:
Supervised clustering of label ranking data using label preference information. Mach. Learn. 93(2-3): 191-225 (2013) - José Hernández-Orallo, Peter A. Flach
, César Ferri
:
ROC curves in cost space. Mach. Learn. 93(1): 71-91 (2013) - Eyke Hüllermeier, Johannes Fürnkranz
:
Editorial: Preference learning and ranking. Mach. Learn. 93(2-3): 185-189 (2013) - Zhanglong Ji, Charles Elkan:
Differential privacy based on importance weighting. Mach. Learn. 93(1): 163-183 (2013) - Levente Kocsis, András György
, Andrea N. Bán:
BoostingTree: parallel selection of weak learners in boosting, with application to ranking. Mach. Learn. 93(2-3): 293-320 (2013) - Benjamin Letham, Cynthia Rudin, David Madigan:
Sequential event prediction. Mach. Learn. 93(2-3): 357-380 (2013) - Tapio Pahikkala
, Antti Airola, Michiel Stock, Bernard De Baets
, Willem Waegeman:
Efficient regularized least-squares algorithms for conditional ranking on relational data. Mach. Learn. 93(2-3): 321-356 (2013) - Nico Piatkowski
, Sangkyun Lee
, Katharina Morik:
Spatio-temporal random fields: compressible representation and distributed estimation. Mach. Learn. 93(1): 115-139 (2013) - Quan Sun, Bernhard Pfahringer:
Pairwise meta-rules for better meta-learning-based algorithm ranking. Mach. Learn. 93(1): 141-161 (2013)
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