Abstract is missing.
- Learning in One-Shot Strategic Form GamesAlon Altman, Avivit Bercovici-Boden, Moshe Tennenholtz. 6-17 [doi]
- A Selective Sampling Strategy for Label RankingMassih-Reza Amini, Nicolas Usunier, François Laviolette, Alexandre Lacasse, Patrick Gallinari. 18-29 [doi]
- Combinatorial Markov Random FieldsRon Bekkerman, Mehran Sahami, Erik G. Learned-Miller. 30-41 [doi]
- Learning Stochastic Tree Edit DistanceMarc Bernard, Amaury Habrard, Marc Sebban. 42-53 [doi]
- Pertinent Background Knowledge for Learning Protein GrammarsChristopher H. Bryant, Daniel Fredouille, Alex Wilson, Channa K. Jayawickreme, Steven Jupe, Simon Topp. 54-65 [doi]
- Improving Bayesian Network Structure Search with Random Variable Aggregation HierarchiesJohn Burge, Terran Lane. 66-77 [doi]
- Sequence Discrimination Using Phase-Type DistributionsJérôme Callut, Pierre Dupont. 78-89 [doi]
- Languages as Hyperplanes: Grammatical Inference with String KernelsAlexander Clark, Christophe Costa Florêncio, Chris Watkins. 90-101 [doi]
- Toward Robust Real-World Inference: A New Perspective on Explanation-Based LearningGerald DeJong. 102-113 [doi]
- Fisher Kernels for Relational DataUwe Dick, Kristian Kersting. 114-125 [doi]
- Evaluating Misclassifications in Imbalanced DataWilliam Elazmeh, Nathalie Japkowicz, Stan Matwin. 126-137 [doi]
- Improving Control-Knowledge Acquisition for Planning by Active LearningRaquel Fuentetaja, Daniel Borrajo. 138-149 [doi]
- PAC-Learning of Markov Models with Hidden StateRicard Gavaldà, Philipp W. Keller, Joelle Pineau, Doina Precup. 150-161 [doi]
- A Discriminative Approach for the Retrieval of Images from Text QueriesDavid Grangier, Florent Monay, Samy Bengio. 162-173 [doi]
- TildeCRF: Conditional Random Fields for Logical SequencesBernd Gutmann, Kristian Kersting. 174-185 [doi]
- Unsupervised Multiple-Instance Learning for Functional Profiling of Genomic DataCorneliu Henegar, Karine Clément, Jean-Daniel Zucker. 186-197 [doi]
- Bayesian Learning of Markov Network StructureAleks Jakulin, Irina Rish. 198-209 [doi]
- Approximate Policy Iteration for Closed-Loop Learning of Visual TasksSébastien Jodogne, Cyril Briquet, Justus H. Piater. 210-221 [doi]
- Task-Driven Discretization of the Joint Space of Visual Percepts and Continuous ActionsSébastien Jodogne, Justus H. Piater. 222-233 [doi]
- EM Algorithm for Symmetric Causal Independence ModelsRasa Jurgelenaite, Tom Heskes. 234-245 [doi]
- Deconvolutive Clustering of Markov StatesAta Kabán, Xin Wang. 246-257 [doi]
- Patching Approximate Solutions in Reinforcement LearningMin Sub Kim, William T. B. Uther. 258-269 [doi]
- Fast Variational Inference for Gaussian Process Models Through KL-CorrectionNathaniel J. King, Neil D. Lawrence. 270-281 [doi]
- Bandit Based Monte-Carlo PlanningLevente Kocsis, Csaba Szepesvári. 282-293 [doi]
- Bayesian Learning with Mixtures of TreesJussi Kollin, Mikko Koivisto. 294-305 [doi]
- Transductive Gaussian Process Regression with Automatic Model SelectionQuoc V. Le, Alexander J. Smola, Thomas Gärtner, Yasemin Altun. 306-317 [doi]
- Efficient Convolution Kernels for Dependency and Constituent Syntactic TreesAlessandro Moschitti. 318-329 [doi]
- Why Is Rule Learning Optimistic and How to Correct ItMartin Mozina, Janez Demsar, Jure Zabkar, Ivan Bratko. 330-340 [doi]
- Automatically Evolving Rule Induction AlgorithmsGisele L. Pappa, Alex Alves Freitas. 341-352 [doi]
- Bayesian Active Learning for Sensitivity AnalysisTobias Pfingsten. 353-364 [doi]
- Mixtures of Kikuchi ApproximationsRoberto Santana, Pedro Larrañaga, José Antonio Lozano. 365-376 [doi]
- Boosting in PN SpacesMartin Scholz. 377-388 [doi]
- Prioritizing Point-Based POMDP SolversGuy Shani, Ronen I. Brafman, Solomon Eyal Shimony. 389-400 [doi]
- Graph Based Semi-supervised Learning with Sharper EdgesHyunjung Shin, N. Jeremy Hill, Gunnar Rätsch. 401-412 [doi]
- Margin-Based Active Learning for Structured Output SpacesDan Roth, Kevin Small. 413-424 [doi]
- Skill Acquisition Via Transfer Learning and Advice TakingLisa Torrey, Jude W. Shavlik, Trevor Walker, Richard Maclin. 425-436 [doi]
- Constant Rate Approximate Maximum Margin AlgorithmsPetroula Tsampouka, John Shawe-Taylor. 437-448 [doi]
- Batch Classification with Applications in Computer Aided DiagnosisVolkan Vural, Glenn Fung, Balaji Krishnapuram, Jennifer G. Dy, R. Bharat Rao. 449-460 [doi]
- Improving the Ranking Performance of Decision TreesBin Wang, Harry Zhang. 461-472 [doi]
- Multiple-Instance Learning Via Random WalkDong Wang, Jianmin Li, Bo Zhang. 473-484 [doi]
- Localized Alternative Cluster Ensembles for Collaborative StructuringMichael Wurst, Katharina Morik, Ingo Mierswa. 485-496 [doi]
- Distributional Features for Text CategorizationXiao-Bing Xue, Zhi-Hua Zhou. 497-508 [doi]
- Subspace Metric Ensembles for Semi-supervised Clustering of High Dimensional DataBojun Yan, Carlotta Domeniconi. 509-520 [doi]
- An Adaptive Kernel Method for Semi-supervised ClusteringBojun Yan, Carlotta Domeniconi. 521-532 [doi]
- To Select or To Weigh: A Comparative Study of Model Selection and Model Weighing for SPODE EnsemblesYing Yang, Geoffrey I. Webb, Jesús Cerquides, Kevin B. Korb, Janice R. Boughton, Kai Ming Ting. 533-544 [doi]
- Ensembles of Nearest Neighbor ForecastsDragomir Yankov, Dennis DeCoste, Eamonn J. Keogh. 545-556 [doi]
- Learning Process Models with Missing DataWill Bridewell, Pat Langley, Steve Racunas, Stuart R. Borrett. 557-565 [doi]
- Case-Based Label RankingKlaus Brinker, Eyke Hüllermeier. 566-573 [doi]
- Cascade Evaluation of Clustering AlgorithmsLaurent Candillier, Isabelle Tellier, Fabien Torre, Olivier Bousquet. 574-581 [doi]
- Making Good Probability Estimates for RegressionMichael Carney, Padraig Cunningham. 582-589 [doi]
- Fast Spectral Clustering of Data Using Sequential Matrix CompressionBo Chen, Bin Gao, Tie-Yan Liu, Yu-Fu Chen, Wei-Ying Ma. 590-597 [doi]
- An Information-Theoretic Framework for High-Order Co-clustering of Heterogeneous ObjectsAntonio D. Chiaravalloti, Gianluigi Greco, Antonella Guzzo, Luigi Pontieri. 598-605 [doi]
- Efficient Inference in Large Conditional Random FieldsTrevor Cohn. 606-613 [doi]
- A Kernel-Based Approach to Estimating Phase Shifts Between Irregularly Sampled Time Series: An Application to Gravitational LensesJuan C. Cuevas-Tello, Peter Tiño, Somak Raychaudhury. 614-621 [doi]
- Cost-Sensitive Decision Tree Learning for Forensic ClassificationJason V. Davis, Jungwoo Ha, Christopher J. Rossbach, Hany E. Ramadan, Emmett Witchel. 622-629 [doi]
- The Minimum Volume Covering Ellipsoid Estimation in Kernel-Defined Feature SpacesAlexander N. Dolia, Tijl De Bie, Christopher J. Harris, John Shawe-Taylor, D. M. Titterington. 630-637 [doi]
- Right of Inference: Nearest Rectangle Learning RevisitedByron J. Gao, Martin Ester. 638-645 [doi]
- Reinforcement Learning for MDPs with ConstraintsPeter Geibel. 646-653 [doi]
- Efficient Non-linear Control Through NeuroevolutionFaustino J. Gomez, Jürgen Schmidhuber, Risto Miikkulainen. 654-662 [doi]
- Efficient Prediction-Based Validation for Document ClusteringDerek Greene, Padraig Cunningham. 663-670 [doi]
- On Testing the Missing at Random AssumptionManfred Jaeger. 671-678 [doi]
- B-Matching for Spectral ClusteringTony Jebara, Vlad Shchogolev. 679-686 [doi]
- Multi-class Ensemble-Based Active LearningChristine Körner, Stefan Wrobel. 687-694 [doi]
- Active Learning with Irrelevant ExamplesDominic Mazzoni, Kiri Wagstaff, Michael C. Burl. 695-702 [doi]
- Classification with Support HyperplanesGeorgi I. Nalbantov, Jan C. Bioch, Patrick J. F. Groenen. 703-710 [doi]
- (Agnostic) PAC Learning Concepts in Higher-Order LogicKee Siong Ng. 711-718 [doi]
- Evaluating Feature Selection for SVMs in High DimensionsRoland Nilsson, José M. Peña, Johan Björkegren, Jesper Tegnér. 719-726 [doi]
- Revisiting Fisher Kernels for Document SimilaritiesMartin Nyffenegger, Jean-Cédric Chappelier, Éric Gaussier. 727-734 [doi]
- Scaling Model-Based Average-Reward Reinforcement Learning for Product DeliveryScott Proper, Prasad Tadepalli. 735-742 [doi]
- Robust Probabilistic CalibrationStefan Rüping. 743-750 [doi]
- Missing Data in Kernel PCAGuido Sanguinetti, Neil D. Lawrence. 751-758 [doi]
- Exploiting Extremely Rare Features in Text CategorizationPéter Schönhofen, András A. Benczúr. 759-766 [doi]
- Efficient Large Scale Linear Programming Support Vector MachinesSuvrit Sra. 767-774 [doi]
- An Efficient Approximation to Lookahead in Relational LearnersJan Struyf, Jesse Davis, C. David Page Jr.. 775-782 [doi]
- Improvement of Systems Management Policies Using Hybrid Reinforcement LearningGerald Tesauro, Nicholas K. Jong, Rajarshi Das, Mohamed N. Bennani. 783-791 [doi]
- Diversified SVM Ensembles for Large Data SetsIvor W. Tsang, András Kocsor, James T. Kwok. 792-800 [doi]
- Dynamic Integration with Random ForestsAlexey Tsymbal, Mykola Pechenizkiy, Padraig Cunningham. 801-808 [doi]
- Bagging Using Statistical QueriesAnneleen Van Assche, Hendrik Blockeel. 809-816 [doi]
- Guiding the Search in the NO Region of the Phase Transition Problem with a Partial Subsumption TestSamuel Wieczorek, Gilles Bisson, Mirta B. Gordon. 817-824 [doi]
- Spline Embedding for Nonlinear Dimensionality ReductionShiming Xiang, Feiping Nie, Changshui Zhang, Chunxia Zhang. 825-832 [doi]
- Cost-Sensitive Learning of SVM for RankingJun Xu, Yunbo Cao, Hang Li, Yalou Huang. 833-840 [doi]
- Variational Bayesian Dirichlet-Multinomial Allocation for Exponential Family MixturesShipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Kriegel. 841-848 [doi]