Abstract is missing.
- Machine Learning for RoboticsPieter Abbeel. 1 [doi]
- Declarative Modeling for Machine Learning and Data MiningLuc De Raedt. 2-3 [doi]
- Machine Learning Methods for Music Discovery and RecommendationDouglas Eck. 4 [doi]
- Solving Problems with Visual Analytics: Challenges and ApplicationsDaniel A. Keim. 5-6 [doi]
- Analyzing Text and Social Network Data with Probabilistic ModelsPadhraic Smyth. 7-8 [doi]
- Discovering Descriptive Tile Trees - By Mining Optimal Geometric SubtilesNikolaj Tatti, Jilles Vreeken. 9-24 [doi]
- Efficient Discovery of Association Rules and Frequent Itemsets through Sampling with Tight Performance GuaranteesMatteo Riondato, Eli Upfal. 25-41 [doi]
- Smoothing Categorical DataArno Siebes, René Kersten. 42-57 [doi]
- An Experimental Comparison of Hybrid Algorithms for Bayesian Network Structure LearningMaxime Gasse, Alex Aussem, Haytham Elghazel. 58-73 [doi]
- Bayesian Network Classifiers with Reduced Precision ParametersSebastian Tschiatschek, Peter Reinprecht, Manfred Mücke, Franz Pernkopf. 74-89 [doi]
- Combining Subjective Probabilities and Data in Training Markov Logic NetworksTivadar Papai, Shalini Ghosh, Henry A. Kautz. 90-105 [doi]
- Score-Based Bayesian Skill LearningShengbo Guo, Scott Sanner, Thore Graepel, Wray L. Buntine. 106-121 [doi]
- A Note on Extending Generalization Bounds for Binary Large-Margin Classifiers to Multiple ClassesÜrün Dogan, Tobias Glasmachers, Christian Igel. 122-129 [doi]
- Extension of the Rocchio Classification Method to Multi-modal Categorization of Documents in Social MediaAmin Mantrach, Jean-Michel Renders. 130-142 [doi]
- Label-Noise Robust Logistic Regression and Its ApplicationsJakramate Bootkrajang, Ata Kabán. 143-158 [doi]
- Sentiment Classification with Supervised Sequence EmbeddingDmitriy Bespalov, Yanjun Qi, Bing Bai, Ali Shokoufandeh. 159-174 [doi]
- The Bitvector Machine: A Fast and Robust Machine Learning Algorithm for Non-linear ProblemsStefan Edelkamp, Martin Stommel. 175-190 [doi]
- Embedding Monte Carlo Search of Features in Tree-Based Ensemble MethodsFrancis Maes, Pierre Geurts, Louis Wehenkel. 191-206 [doi]
- Hypergraph Spectra for Semi-supervised Feature SelectionZhihong Zhang, Edwin R. Hancock, Xiao Bai. 207-222 [doi]
- Learning Neighborhoods for Metric LearningJun Wang 0017, Adam Woznica, Alexandros Kalousis. 223-236 [doi]
- Massively Parallel Feature Selection: An Approach Based on Variance PreservationZheng Zhao, James Cox, David Duling, Warren Sarle. 237-252 [doi]
- PCA, Eigenvector Localization and Clustering for Side-Channel Attacks on Cryptographic Hardware DevicesDimitrios Mavroeidis, Lejla Batina, Twan van Laarhoven, Elena Marchiori. 253-268 [doi]
- Classifying Stem Cell Differentiation Images by Information DistanceXianglilan Zhang, Hongnan Wang, Tony J. Collins, Zhigang Luo, Ming Li. 269-282 [doi]
- Distance Metric Learning RevisitedQiong Cao, Yiming Ying, Peng Li. 283-298 [doi]
- Geodesic Analysis on the Gaussian RKHS HypersphereNicolas Courty, Thomas Burger, Pierre-François Marteau. 299-313 [doi]
- Boosting Nearest Neighbors for the Efficient Estimation of PosteriorsRoberto D'Ambrosio, Richard Nock, Wafa Bel Haj Ali, Frank Nielsen, Michel Barlaud. 314-329 [doi]
- Diversity Regularized Ensemble PruningNan Li, Yang Yu, Zhi-Hua Zhou. 330-345 [doi]
- Ensembles on Random PatchesGilles Louppe, Pierre Geurts. 346-361 [doi]
- An Efficiently Computable Support Measure for Frequent Subgraph Pattern MiningYuyi Wang, Jan Ramon. 362-377 [doi]
- Efficient Graph Kernels by RandomizationMarion Neumann, Novi Patricia, Roman Garnett, Kristian Kersting. 378-393 [doi]
- Graph Mining for Object Tracking in VideosFabien Diot, Élisa Fromont, Baptiste Jeudy, Emmanuel Marilly, Olivier Martinot. 394-409 [doi]
- Hypergraph Learning with Hyperedge ExpansionLi Pu, Boi Faltings. 410-425 [doi]
- Nearly Exact Mining of Frequent Trees in Large NetworksAshraf M. Kibriya, Jan Ramon. 426-441 [doi]
- Reachability Analysis and Modeling of Dynamic Event NetworksKathy Macropol, Ambuj K. Singh. 442-457 [doi]
- CC-MR - Finding Connected Components in Huge Graphs with MapReduceThomas Seidl, Brigitte Boden, Sergej Fries. 458-473 [doi]
- Fast Near Neighbor Search in High-Dimensional Binary DataAnshumali Shrivastava, Ping Li 0001. 474-489 [doi]
- Fully Sparse Topic ModelsKhoat Than, Tu Bao Ho. 490-505 [doi]
- Learning Compact Class Codes for Fast Inference in Large Multi Class ClassificationM. Cissé, Thierry Artières, Patrick Gallinari. 506-520 [doi]
- ParCube: Sparse Parallelizable Tensor DecompositionsEvangelos E. Papalexakis, Christos Faloutsos, Nicholas D. Sidiropoulos. 521-536 [doi]
- Stochastic Coordinate Descent Methods for Regularized Smooth and Nonsmooth LossesQing Tao, Kang Kong, Dejun Chu, Gao-wei Wu. 537-552 [doi]
- Sublinear Algorithms for Penalized Logistic Regression in Massive DatasetsHaoruo Peng, Zhengyu Wang, Edward Y. Chang, Shuchang Zhou, Zhihua Zhang. 553-568 [doi]
- Author Name Disambiguation Using a New Categorical Distribution SimilarityShaohua Li, Gao Cong, Chunyan Miao. 569-584 [doi]
- Lifted Online Training of Relational Models with Stochastic Gradient MethodsBabak Ahmadi, Kristian Kersting, Sriraam Natarajan. 585-600 [doi]
- Scalable Relation Prediction Exploiting Both Intrarelational Correlation and Contextual InformationXueyan Jiang, Volker Tresp, Yi Huang, Maximilian Nickel, Hans-Peter Kriegel. 601-616 [doi]
- Relational Differential PredictionHoussam Nassif, Vítor Santos Costa, Elizabeth S. Burnside, David Page. 617-632 [doi]
- Efficient Training of Graph-Regularized Multitask SVMsChristian Widmer, Marius Kloft, Nico Görnitz, Gunnar Rätsch. 633-647 [doi]
- Geometry Preserving Multi-task Metric LearningPeipei Yang, Kaizhu Huang, Cheng-Lin Liu. 648-664 [doi]
- Learning and Inference in Probabilistic Classifier Chains with Beam SearchAbhishek Kumar, Shankar Vembu, Aditya Krishna Menon, Charles Elkan. 665-680 [doi]
- Learning Multiple Tasks with Boosted Decision TreesJean Baptiste Faddoul, Boris Chidlovskii, Rémi Gilleron, Fabien Torre. 681-696 [doi]
- Multi-Task Boosting by Exploiting Task RelationshipsYu Zhang, Dit-Yan Yeung. 697-710 [doi]
- Sparse Gaussian Processes for Multi-task LearningYuyang Wang, Roni Khardon. 711-727 [doi]
- Collective Information Extraction with Context-Specific ConsistenciesPeter Klügl, Martin Toepfer, Florian Lemmerich, Andreas Hotho, Frank Puppe. 728-743 [doi]
- Supervised Learning of Semantic RelatednessRan El-Yaniv, David Yanay. 744-759 [doi]
- Unsupervised Bayesian Part of Speech Inference with Particle GibbsGregory Dubbin, Phil Blunsom. 760-773 [doi]
- WikiSent: Weakly Supervised Sentiment Analysis through Extractive Summarization with WikipediaSubhabrata Mukherjee, Pushpak Bhattacharyya. 774-793 [doi]
- Adaptive Two-View Online Learning for Math Topic ClassificationTam T. Nguyen, Kuiyu Chang, Siu Cheung Hui. 794-809 [doi]
- BDUOL: Double Updating Online Learning on a Fixed BudgetPeilin Zhao, Steven C. H. Hoi. 810-826 [doi]
- Handling Time Changing Data with Adaptive Very Fast Decision RulesPetr Kosina, João Gama. 827-842 [doi]
- Improved Counter Based Algorithms for Frequent Pairs Mining in Transactional Data StreamsKonstantin Kutzkov. 843-858 [doi]
- Mirror Descent for Metric Learning: A Unified ApproachGautam Kunapuli, Jude W. Shavlik. 859-874 [doi]