An Efficient Method for Simplifying Support Vector Machines (English)
- New search for: Nguyen, D.
- New search for: Ho, T. B.
- New search for: Nguyen, D.
- New search for: Ho, T. B.
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In:
Machine learning; Proceedings of the 22nd international conference on machine learning: ICML 2005
;
617-624
;
2005
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ISBN:
- Conference paper / Print
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Title:An Efficient Method for Simplifying Support Vector Machines
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Contributors:
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Conference:International conference; 22nd, Machine learning; Proceedings of the 22nd international conference on machine learning: ICML 2005 ; 2005 ; Bonn, Germany
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Published in:
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Publisher:
- New search for: ACM
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Publication date:2005-01-01
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Size:8 pages
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ISBN:
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Type of media:Conference paper
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Type of material:Print
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Language:English
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Keywords:
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Source:
© Metadata Copyright the British Library Board and other contributors. All rights reserved.
Table of contents conference proceedings
The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.
- 1
-
Exploration and Apprenticeship Learning in Reinforcement LearningAbbeel, P. / Ng, A. Y. et al. | 2005
- 9
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Active Learning for Hidden Markov Models: Objective Functions and AlgorithmsAnderson, B. / Moore, A. W. et al. | 2005
- 17
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Tempering for Bayesian C&RTAngelopoulos, N. / Cussens, J. et al. | 2005
- 25
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Fast Condensed Nearest Neighbor RuleAngiulli, F. et al. | 2005
- 33
-
Predictive low-rank decomposition for kernel methodsBach, F. R. / Jordan, M. I. et al. | 2005
- 41
-
Multi-Way Distributional Clustering via Pairwise InteractionsBekkerman, R. / El-Yaniv, R. / McCallum, A. et al. | 2005
- 49
-
Error Limiting Reductions Between Classification TasksBeygelzimer, A. / Dani, V. / Hayes, T. / Langford, J. / Zadrozny, B. et al. | 2005
- 57
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Multi-Instance Tree LearningBlockeel, H. / Page, D. / Srinivasan, A. et al. | 2005
- 65
-
Action Respecting EmbeddingBowling, M. / Ghodsi, A. / Wilkinson, D. et al. | 2005
- 73
-
Clustering Through Ranking On ManifoldsBreitenbach, M. / Grudic, G. Z. et al. | 2005
- 81
-
Reducing Overfitting in Process Model InductionBridewell, W. / Asani, N. B. / Langley, P. / Todorovski, L. et al. | 2005
- 89
-
Learning to Rank using Gradient DescentBurges, C. / Shaked, T. / Renshaw, E. / Lazier, A. / Deeds, M. / Hamilton, N. / Hullender, G. et al. | 2005
- 97
-
Learning Class-Discriminative Dynamic Bayesian NetworksBurge, J. / Lane, T. et al. | 2005
- 105
-
Recognition and Reproduction of Gestures using a Probabilistic Framework combining PCA, ICA and HMMCalinon, S. / Billard, A. et al. | 2005
- 113
-
Predicting Probability Distributions for Surf Height Using an Ensemble of Mixture Density NetworksCarney, M. / Cunningham, P. / Dowling, J. / Lee, C. et al. | 2005
- 121
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Hedged learning: Regret minimization with learning expertsChang, Y.-H. / Kaelbling, L. P. et al. | 2005
- 129
-
Variational Bayesian Image ModellingCheng, L. / Jiao, F. / Schuurmans, D. / Wang, S. et al. | 2005
- 137
-
Preference Learning with Gaussian ProcessesChu, W. / Ghahramani, Z. et al. | 2005
- 145
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New Approaches to Support Vector Ordinal RegressionChu, W. / Keerthi, S. S. et al. | 2005
- 153
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A General Regression Technique for Learning TransductionsCortes, C. / Mohri, M. / Weston, J. et al. | 2005
- 161
-
Learning to Compete, Compromise, and Cooperate in Repeated General-Sum GamesCrandall, J. W. / Goodrich, M. A. et al. | 2005
- 169
-
Learning as Search Optimization: Approximate Large Margin Methods for Structured PredictionDaume, H. / Marcu, D. et al. | 2005
- 177
-
Multimodal Oriented Discriminant AnalysisDe la Torre, F. / Kanade, T. et al. | 2005
- 185
-
A Practical Generalization of Fourier-based LearningDrake, A. / Ventura, D. et al. | 2005
- 193
-
Combining Model-Based and Instance-Based Learning for First Order RegressionDriessens, K. / Dzeroski, S. et al. | 2005
- 201
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Reinforcement learning with Gaussian processesEngel, Y. / Mannor, S. / Meir, R. et al. | 2005
- 209
-
Experimental Comparison between Bagging and Monte Carlo Ensemble ClassificationEsposito, R. / Saitta, L. et al. | 2005
- 217
-
Supervised Clustering with Support Vector MachinesFinley, T. / Joachims, T. et al. | 2005
- 225
-
Optimal Assignment Kernels For Attributed Molecular GraphsFrohlich, H. / Wegner, J. K. / Sieker, F. / Zell, A. et al. | 2005
- 233
-
Closed-form dual perturb and combine for tree-based modelsGeurts, P. / Wehenkel, L. et al. | 2005
- 241
-
Hierarchic Bayesian Models for Kernel LearningGirolami, M. / Rogers, S. et al. | 2005
- 249
-
Online Feature Selection for Pixel ClassificationGlocer, K. / Eads, D. / Theiler, J. et al. | 2005
- 257
-
Learning Strategies for Story Comprehension: A Reinforcement Learning ApproachGrois, E. / Wilkins, D. C. et al. | 2005
- 265
-
Near-Optimal Sensor Placements in Gaussian ProcessesGuestrin, C. / Krause, A. / Singh, A. P. et al. | 2005
- 273
-
Robust One-Class Clustering Using Hybrid Global and Local SearchGupta, G. / Ghosh, J. et al. | 2005
- 281
-
Statistical and Computational Analysis of Locality Preserving ProjectionHe, X. / Cai, D. / Min, W. et al. | 2005
- 289
-
Intrinsic Dimensionality Estimation of Submanifolds in ^dHein, M. / Audibert, J.-Y. et al. | 2005
- 297
-
Bayesian Hierarchical ClusteringHeller, K. A. / Ghahramani, Z. et al. | 2005
- 305
-
Online Learning over GraphsHerbster, M. / Pontil, M. / Wainer, L. et al. | 2005
- 313
-
Adapting Two-Class Classification Methods to Many Class ProblemsHill, S. I. / Doucet, A. et al. | 2005
- 321
-
A Martingale Framework for Concept Change Detection in Time-Varying Data StreamsHo, S.-S. et al. | 2005
- 329
-
Multi-Class protein fold detection using adaptive codesle, E. / Weston, J. / Noble, W. S. / Leslie, C. et al. | 2005
- 337
-
Learning Approximate Preconditions for Methods in Hierarchical PlansIlghami, O. / Munoz-Avila, H. / Nau, D. S. / Aha, D. W. et al. | 2005
- 345
-
Evaluating Machine Learning for Information ExtractionIreson, N. / Ciravegna, F. / Califf, M. E. / Freitag, D. / Kushmerick, N. / Lavelli, A. et al. | 2005
- 353
-
Learn to Weight Terms in Information Retrieval Using Category InformationJin, R. / Chai, J. Y. / Si, L. et al. | 2005
- 361
-
A Smoothed Boosting Algorithm Using Probabilistic Output CodesJin, R. / Zhang, J. et al. | 2005
- 369
-
Efficient discriminative learning of Bayesian network classifier via Boosted Augmented Naive BayesJing, Y. / Pavlovic, V. / Rehg, J. M. et al. | 2005
- 377
-
A Support Vector Method for Multivariate Performance MeasuresJoachims, T. et al. | 2005
- 385
-
Error Bounds for Correlation ClusteringJoachims, T. / Hopcroft, J. et al. | 2005
- 393
-
Interactive Learning of Mappings from Visual Percepts to ActionsJodogne, S. / Piater, J. H. et al. | 2005
- 401
-
A Causal Approach to Hierarchical Decomposition of Factored MDPsJonsson, A. / Barto, A. et al. | 2005
- 409
-
A Comparison of Tight Generalization Error BoundsKaariainen, M. / Langford, J. et al. | 2005
- 417
-
Generalized LARS as an Effective Feature Selection Tool for Text Classification With SVMsKeerthi, S. S. et al. | 2005
- 425
-
Ensembles of Biased ClassifiersKhoussainov, R. / Hess, A. / Kushmerick, N. et al. | 2005
- 433
-
Computational Aspects of Bayesian Partition ModelsKoivisto, M. / Sood, K. et al. | 2005
- 441
-
Learning the Structure of Markov Logic NetworksKok, S. / Domingos, P. et al. | 2005
- 449
-
Using Additive Expert Ensembles to Cope with Concept DriftKolter, J. / Maloof, M. et al. | 2005
- 457
-
Semi-supervised Graph Clustering: A Kernel ApproachKulis, B. / Basu, S. / Dhillon, I. S. / Mooney, R. J. et al. | 2005
- 465
-
A Brain Computer Interface with Online Feedback based on MagnetoencephalographyLal, T. N. / Schroder, M. / Hill, N. J. / Preissl, H. / Hinterberger, T. / Mellinger, J. / Bogdan, M. / Rosenstiel, W. / Hofmann, T. / Birbaumer, N. et al. | 2005
- 473
-
Relating Reinforcement Learning Performance to Classification PerformanceLangford, J. / Zadrozny, B. et al. | 2005
- 481
-
PAC-Bayes Risk Bounds for Sample-Compressed Gibbs ClassifiersLaviolette, F. / Marchand, M. et al. | 2005
- 489
-
Heteroscedastic Gaussian Process RegressionLe, Q. V. / Smola, A. J. / Canu, S. et al. | 2005
- 497
-
Predicting Relative Performance of Classifiers from SamplesLeite, R. / Brazdil, P. et al. | 2005
- 505
-
Logistic Regression with an Auxiliary Data SourceLiao, X. / Xue, Y. / Carin, L. et al. | 2005
- 513
-
Predicting Protein Folds with Structural Repeats Using a Chain Graph ModelLiu, Y. / Xing, E. P. / Carbonell, J. et al. | 2005
- 521
-
Unsupervised Evidence IntegrationLong, P. M. / Varadan, V. / Gilman, S. / Treshock, M. / Servedio, R. A. et al. | 2005
- 529
-
Naive Bayes Models for Probability EstimationLowd, D. / Domingos, P. et al. | 2005
- 537
-
ROC Confidence Bands: An Empirical EvaluationMacskassy, S. A. / Provost, F. / Rosset, S. et al. | 2005
- 545
-
Modeling Word Burstiness Using the Dirichlet DistributionMadsen, R. E. / Kauchak, D. / Elkan, C. et al. | 2005
- 553
-
Proto-Value Functions: Developmental Reinforcement LearningMahadevan, S. et al. | 2005
- 561
-
The cross entropy method for classificationMannor, S. / Peleg, D. / Rubinstein, R. Y. et al. | 2005
- 569
-
Bounded Real-Time Dynamic Programming: RTDP with monotone upper bounds and performance guaranteesMcMahan, H. B. / Likhachev, M. / Gordon, G. J. et al. | 2005
- 577
-
Comparing Clusterings - An Axiomatic ViewMeila, M. et al. | 2005
- 585
-
Weighted Decomposition KernelsMenchetti, S. / Costa, F. / Frasconi, P. et al. | 2005
- 593
-
High Speed Obstacle Avoidance using Monocular Vision and Reinforcement learningMichels, J. / Saxena, A. / Ng, A. Y. et al. | 2005
- 601
-
Dynamic Preferences in Multi-Criteria Reinforcement LearningNatarajan, S. / Tadepalli, P. et al. | 2005
- 609
-
Learning First-Order Probabilistic Models with Combining RulesNatarajan, S. / Tadepalli, P. / Altendorf, E. / Dietterich, T. G. / Fern, A. / Restificar, A. et al. | 2005
- 617
-
An Efficient Method for Simplifying Support Vector MachinesNguyen, D. / Ho, T. B. et al. | 2005
- 625
-
Predicting Good Probabilities With Supervised LearningNiculescu-Mizil, A. / Caruana, R. et al. | 2005
- 633
-
Recycling Data for Multi-Agent LearningOntanon, S. / Plaza, E. et al. | 2005
- 641
-
A Graphical Model for Chord Progressions Embedded in a Psychoacoustic SpacePaiement, J.-F. / Eck, D. / Bengio, S. / Barber, D. et al. | 2005
- 649
-
Q-Learning of Sequential Attention for Visual Object Recognition from Informative Local DescriptorsPaletta, L. / Fritz, G. / Seifert, C. et al. | 2005
- 657
-
Discriminative versus Generative Parameter and Structure Learning of Bayesian Network ClassifiersPernkopf, F. / Bilmes, J. et al. | 2005
- 665
-
Optimizing Abstaining Classifiers using ROC AnalysisPietraszek, T. et al. | 2005
- 673
-
Independent Subspace Analysis Using Geodesic Spanning TreesPoczos, B. / Lorincz, A. et al. | 2005
- 681
-
A Model for Handling Approximate, Noisy or Incomplete Labeling in Text ClassificationRamakrishnan, G. / Chitrapura, K. P. / Krishnapuram, R. / Bhattacharyya, P. et al. | 2005
- 689
-
Healing the Relevance Vector Machine through AugmentationRasmussen, C. E. / Quinonero-Candela, J. et al. | 2005
- 697
-
Supervised versus Multiple Instance Learning: An Empirical ComparisonRay, S. / Craven, M. et al. | 2005
- 705
-
Generalized Skewing for Functions with Continuous and Nominal AttributesRay, S. / Page, D. et al. | 2005
- 713
-
Fast Maximum Margin Matrix Factorization for Collaborative PredictionRennie, J. D. M. / Srebro, N. et al. | 2005
- 721
-
Coarticulation: An Approach for Generating Concurrent Plans in Markov Decision ProcessesRohanimanesh, K. / Mahadevan, S. et al. | 2005
- 729
-
Why Skewing Works: Learning Difficult Boolean Functions with Greedy Tree LearnersRosell, B. / Hellerstein, L. / Ray, S. / Page, D. et al. | 2005
- 737
-
Integer Linear Programming Inference for Conditional Random FieldsRoth, D. / Yih, W.-T. et al. | 2005
- 745
-
Learning Hierarchical Multi-Category Text Classification ModelsRousu, J. / Saunders, C. / Szedmak, S. / Shawe-Taylor, J. et al. | 2005
- 753
-
Expectation Maximization Algorithms for Conditional LikelihoodsSalojarvi, J. / Puolamaki, K. / Kaski, S. et al. | 2005
- 761
-
Estimating and computing density based distance metricsSajama / Orlitsky, A. et al. | 2005
- 769
-
Supervised dimensionality reduction using mixture modelsSajama / Orlitsky, A. et al. | 2005
- 777
-
Object Correspondence as a Machine Learning ProblemScholkopf, B. / Steinke, F. / Blanz, V. et al. | 2005
- 785
-
Analysis and Extension of Spectral Methods for Nonlinear Dimensionality ReductionSha, F. / Saul, L. K. et al. | 2005
- 793
-
Non-Negative Tensor Factorization with Applications to Statistics and Computer VisionShashua, A. / Hazan, T. et al. | 2005
- 801
-
Fast Inference and Learning in Large-State-Space HMMsSiddiqi, S. M. / Moore, A. W. et al. | 2005
- 809
-
New D-Separation Identification Results for Learning Continuous Latent Variable ModelsSilva, R. / Scheines, R. et al. | 2005
- 817
-
Identifying Useful Subgoals in Reinforcement Learning by Local Graph PartitioningSimsek, O. / Wolfe, A. P. / Barto, A. G. et al. | 2005
- 825
-
Beyond the Point Cloud: from Transductive to Semi-supervised LearningSindhwani, V. / Niyogi, P. / Belkin, M. et al. | 2005
- 833
-
Active Learning for Sampling in Time-Series Experiments With Application to Gene Expression AnalysisSingh, R. / Palmer, N. / Gifford, D. / Berger, B. / Bar-Joseph, Z. et al. | 2005
- 841
-
Compact approximations to Bayesian predictive distributionsSnelson, E. / Ghahramani, Z. et al. | 2005
- 849
-
Large Scale Genomic Sequence SVM ClassifiersSonnenburg, S. / Ratsch, G. / Scholkopf, B. et al. | 2005
- 857
-
A Theoretical Analysis of Model-Based Interval EstimationStrehl, A. L. / Littman, M. L. et al. | 2005
- 865
-
Explanation-Augmented SVM: an Approach to Incorporating Domain Knowledge into SVM LearningSun, Q. / DeJong, G. et al. | 2005
- 873
-
Unifying the Error-Correcting and Output-Code AdaBoost within the Margin FrameworkSun, Y. / Todorovic, S. / Li, J. / Wu, D. et al. | 2005
- 881
-
Finite Time Bounds for Sampling Based Fitted Value IterationSzepesvari, C. / Munos, R. et al. | 2005
- 889
-
TD(Lambda) Networks: Temporal-Difference Networks with Eligibility TracesTanner, B. / Sutton, R. S. et al. | 2005
- 897
-
Learning Structured Prediction Models: A Large Margin ApproachTaskar, B. / Chatalbashev, V. / Koller, D. / Guestrin, C. et al. | 2005
- 905
-
Learning Discontinuities with Products-of-Sigmoids for Switching between Local ModelsToussaint, M. / Vijayakumar, S. et al. | 2005
- 913
-
Core Vector Regression for Very Large Regression ProblemsTsang, I. W. / Kwok, J. T. / Lai, K. T. et al. | 2005
- 921
-
Propagating Distributions on a Hypergraph by Dual Information RegularizationTsuda, K. et al. | 2005
- 929
-
Hierarchical Dirichlet Model for Document ClassificationVeeramachaneni, S. / Sona, D. / Avesani, P. et al. | 2005
- 937
-
Implicit Surface Modelling as an Eigenvalue ProblemWalder, C. / Chapelle, O. / Scholkopf, B. et al. | 2005
- 945
-
New Kernels for Protein Structural Motif Discovery and Function ClassificationWang, C. / Scott, S. D. et al. | 2005
- 953
-
Exploiting Syntactic, Semantic and Lexical Regularities in Language Modeling via Directed Markov Random FieldsWang, S. / Greiner, R. / Schuurmans, D. / Cheng, L. et al. | 2005
- 961
-
Bayesian Sparse Sampling for On-line Reward OptimizationWang, T. / Lizotte, D. J. / Bowling, M. / Schuurmans, D. et al. | 2005
- 969
-
Learning Predictive Representations from a HistoryWiewiora, E. et al. | 2005
- 977
-
Incomplete-Data Classification using Logistic RegressionWilliams, D. / Liao, X. / Xue, Y. / Carin, L. et al. | 2005
- 985
-
Learning Predictive State Representations in Dynamical Systems Without ResetWolfe, B. / James, M. R. / Singh, S. et al. | 2005
- 993
-
Linear Asymmetric Classifier for Cascade DetectorsWu, J. / Mullin, M. D. / Rehg, J. M. et al. | 2005
- 1001
-
Building Sparse Large Margin ClassifiersWu, M. / Scholkopf, B. / Bakir, G. et al. | 2005
- 1009
-
Dirichlet Enhanced Relational LearningXu, Z. / Tresp, V. / Yu, K. / Yu, S. / Kriegel, H.-P. et al. | 2005
- 1017
-
Learning Gaussian Processes from Multiple TasksYu, K. / Tresp, V. / Schwaighofer, A. et al. | 2005
- 1025
-
Augmenting Naive Bayes for RankingZhang, H. / Jiang, L. / Su, J. et al. | 2005
- 1033
-
A New Mallows Distance Based Metric For Comparing ClusteringsZhou, D. / Li, J. / Zha, H. et al. | 2005
- 1041
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Learning from Labeled and Unlabeled Data on a Directed GraphZhou, D. / Huang, J. / Scholkopf, B. et al. | 2005
- 1049
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2D Conditional Random Fields for Web Information ExtractionZhu, J. / Nie, Z. / Wen, J.-R. / Zhang, B. / Ma, W.-Y. et al. | 2005
- 1057
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Harmonic mixtures: combining mixture models and graph-based methods for inductive and scalable semi-supervised learningZhu, X. / Lafferty, J. et al. | 2005
- 1065
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Large Margin Non-Linear EmbeddingZien, A. / Quinonero-Candela, J. et al. | 2005