Machine Learning and Knowledge Discovery in Databases - Taschenbuch

EAN (ISBN-13): 9783540874782
ISBN (ISBN-10): 354087478X
Gebundene Ausgabe
Taschenbuch
Erscheinungsjahr: 2008
Herausgeber: Springer Berlin
692 Seiten
Gewicht: 1,016 kg
Sprache: eng/Englisch

Buch in der Datenbank seit 2007-10-22T19:26:27+02:00 (Vienna)
Detailseite zuletzt geändert am 2022-03-05T19:36:05+01:00 (Vienna)
ISBN/EAN: 9783540874782

ISBN - alternative Schreibweisen:
3-540-87478-X, 978-3-540-87478-2
Alternative Schreibweisen und verwandte Suchbegriffe:
Autor des Buches: goethals, daelemans, katharina walter, dael
Titel des Buches: antwerp, europe 2008, belgium dat, machine learning, the machine seen, september 2008, knowledge discovery databases

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Daten vom Verlag:

Autor/in: Walter Daelemans; Katharina Morik
Titel: Lecture Notes in Artificial Intelligence; Lecture Notes in Computer Science; Machine Learning and Knowledge Discovery in Databases - European Conference, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part I
Verlag: Springer; Springer Berlin
692 Seiten
Erscheinungsjahr: 2008-09-04
Berlin; Heidelberg; DE
Sprache: Englisch
128,39 € (DE)
131,99 € (AT)
142,00 CHF (CH)
Contact supplier
XXIV, 692 p.

BC; Hardcover, Softcover / Informatik, EDV/Informatik; Künstliche Intelligenz; Verstehen; Informatik; Averaging; Support Vector Machine; active learning; algorithmic learning; association rule mining; bayesian learning; case-based learning; clustering; distributed computing; k-Means; machine learning; master data management; performance; performance evaluation; reinforcement learning; algorithm analysis and problem complexity; Artificial Intelligence; Database Management; Information Storage and Retrieval; Formal Languages and Automata Theory; Algorithms; Probability and Statistics in Computer Science; Datenbanken; Informationsrückgewinnung, Information Retrieval; Data Warehousing; Theoretische Informatik; Algorithmen und Datenstrukturen; Mathematik für Informatiker; Wahrscheinlichkeitsrechnung und Statistik; EA

Invited Talks (Abstracts).- Industrializing Data Mining, Challenges and Perspectives.- From Microscopy Images to Models of Cellular Processes.- Data Clustering: 50 Years Beyond K-means.- Learning Language from Its Perceptual Context.- The Role of Hierarchies in Exploratory Data Mining.- Machine Learning Journal Abstracts.- Rollout Sampling Approximate Policy Iteration.- New Closed-Form Bounds on the Partition Function.- Large Margin vs. Large Volume in Transductive Learning.- Incremental Exemplar Learning Schemes for Classification on Embedded Devices.- A Collaborative Filtering Framework Based on Both Local User Similarity and Global User Similarity.- A Critical Analysis of Variants of the AUC.- Improving Maximum Margin Matrix Factorization.- Data Mining and Knowledge Discovery Journal Abstracts.- Finding Reliable Subgraphs from Large Probabilistic Graphs.- A Space Efficient Solution to the Frequent String Mining Problem for Many Databases.- The Boolean Column and Column-Row Matrix Decompositions.- SkyGraph: An Algorithm for Important Subgraph Discovery in Relational Graphs.- Mining Conjunctive Sequential Patterns.- Adequate Condensed Representations of Patterns.- Two Heads Better Than One: Pattern Discovery in Time-Evolving Multi-aspect Data.- Regular Papers.- TOPTMH: Topology Predictor for Transmembrane ?-Helices.- Learning to Predict One or More Ranks in Ordinal Regression Tasks.- Cascade RSVM in Peer-to-Peer Networks.- An Algorithm for Transfer Learning in a Heterogeneous Environment.- Minimum-Size Bases of Association Rules.- Combining Classifiers through Triplet-Based Belief Functions.- An Improved Multi-task Learning Approach with Applications in Medical Diagnosis.- Semi-supervised Laplacian Regularization of Kernel Canonical Correlation Analysis.- Sequence Labelling SVMs Trained in One Pass.- Semi-supervised Classification from Discriminative Random Walks.- Learning Bidirectional Similarity for Collaborative Filtering.- Bootstrapping Information Extractionfrom Semi-structured Web Pages.- Online Multiagent Learning against Memory Bounded Adversaries.- Scalable Feature Selection for Multi-class Problems.- Learning Decision Trees for Unbalanced Data.- Credal Model Averaging: An Extension of Bayesian Model Averaging to Imprecise Probabilities.- A Fast Method for Training Linear SVM in the Primal.- On the Equivalence of the SMO and MDM Algorithms for SVM Training.- Nearest Neighbour Classification with Monotonicity Constraints.- Modeling Transfer Relationships Between Learning Tasks for Improved Inductive Transfer.- Mining Edge-Weighted Call Graphs to Localise Software Bugs.- Hierarchical Distance-Based Conceptual Clustering.- Mining Frequent Connected Subgraphs Reducing the Number of Candidates.- Unsupervised Riemannian Clustering of Probability Density Functions.- Online Manifold Regularization: A New Learning Setting and Empirical Study.- A Fast Algorithm to Find Overlapping Communities in Networks.- A Case Study in Sequential Pattern Mining for IT-Operational Risk.- Tight Optimistic Estimates for Fast Subgroup Discovery.- Watch, Listen & Learn: Co-training on Captioned Images and Videos.- Parameter Learning in Probabilistic Databases: A Least Squares Approach.- Improving k-Nearest Neighbour Classification with Distance Functions Based on Receiver Operating Characteristics.- One-Class Classification by Combining Density and Class Probability Estimation.- Efficient Frequent Connected Subgraph Mining in Graphs of Bounded Treewidth.- Proper Model Selection with Significance Test.- A Projection-Based Framework for Classifier Performance Evaluation.- Distortion-Free Nonlinear Dimensionality Reduction.- Learning with L q? vs L 1-Norm Regularisation with Exponentially Many Irrelevant Features.- Catenary Support Vector Machines.- Exact and Approximate Inference for Annotating Graphs with Structural SVMs.- Extracting Semantic Networks from Text Via Relational Clustering.- Ranking the Uniformity of Interval Pairs.- Multiagent Reinforcement Learning for Urban Traffic Control Using Coordination Graphs.- StreamKrimp: Detecting Change in Data Streams.