Machine learning -- ECML 2005 16th European Conference on Machine Learning, Porto, Portugal, October 3-7, 2005 : proceedings /
The European Conference on Machine Learning (ECML) and the European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD) were jointly organized this year for the?fth time in a row, after some years of mutual independence before. After Freiburg (2001), Helsinki (2002), Cav...
| Corporate Authors: | European Conference on Machine Learning Porto, Portugal) |
|---|---|
| Other Authors: | European Conference on Machine Learning, Gama, João., SpringerLink (Online service) |
| Format: | eBook |
| Language: | English |
| Published: |
Berlin ; New York :
Springer,
©2005.
Berlin ; New York : [2005] |
| Physical Description: |
1 online resource (xxiii, 769 pages) : illustrations. |
| Series: |
Lecture notes in computer science ;
3720. Lecture notes in computer science. Lecture notes in artificial intelligence. |
| Subjects: |
Table of Contents:
- Invited Talks
- Data Analysis in the Life Sciences
- Sparking Ideas
- Machine Learning for Natural Language Processing (and Vice Versa?)
- Statistical Relational Learning: An Inductive Logic Programming Perspective
- Recent Advances in Mining Time Series Data
- Focus the Mining Beacon: Lessons and Challenges from the World of E-Commerce
- Data Streams and Data Synopses for Massive Data Sets (Invited Talk)
- Long Papers
- Clustering and Metaclustering with Nonnegative Matrix Decompositions
- A SAT-Based Version Space Algorithm for Acquiring Constraint Satisfaction Problems
- Estimation of Mixture Models Using Co-EM
- Nonrigid Embeddings for Dimensionality Reduction
- Multi-view Discriminative Sequential Learning
- Robust Bayesian Linear Classifier Ensembles
- An Integrated Approach to Learning Bayesian Networks of Rules
- Thwarting the Nigritude Ultramarine: Learning to Identify Link Spam
- Rotational Prior Knowledge for SVMs
- On the LearnAbility of Abstraction Theories from Observations for Relational Learning
- Beware the Null Hypothesis: Critical Value Tables for Evaluating Classifiers
- Kernel Basis Pursuit
- Hybrid Algorithms with Instance-Based Classification
- Learning and Classifying Under Hard Budgets
- Training Support Vector Machines with Multiple Equality Constraints
- A Model Based Method for Automatic Facial Expression Recognition
- Margin-Sparsity Trade-Off for the Set Covering Machine
- Learning from Positive and Unlabeled Examples with Different Data Distributions
- Towards Finite-Sample Convergence of Direct Reinforcement Learning
- Infinite Ensemble Learning with Support Vector Machines
- A Kernel Between Unordered Sets of Data: The Gaussian Mixture Approach
- Active Learning for Probability Estimation Using Jensen-Shannon Divergence
- Natural Actor-Critic
- Inducing Head-Driven PCFGs with Latent Heads: Refining a Tree-Bank Grammar for Parsing
- Learning (k, l)-Contextual Tree Languages for Information Extraction
- Neural Fitted Q Iteration
- First Experiences with a Data Efficient Neural Reinforcement Learning Method
- MCMC Learning of Bayesian Network Models by Markov Blanket Decomposition
- On Discriminative Joint Density Modeling
- Model-Based Online Learning of POMDPs
- Simple Test Strategies for Cost-Sensitive Decision Trees
- Likelihood and -Updating Algorithms: Statistical Inference in Latent Variable Models
- An Optimal Best-First Search Algorithm for Solving Infinite Horizon DEC-POMDPs
- Ensemble Learning with Supervised Kernels
- Using Advice to Transfer Knowledge Acquired in One Reinforcement Learning Task to Another
- A Distance-Based Approach for Action Recommendation
- Multi-armed Bandit Algorithms and Empirical Evaluation
- Annealed Discriminant Analysis
- Network Game and Boosting
- Model Selection in Omnivariate Decision Trees
- Bayesian Network Learning with Abstraction Hierarchies and Context-Specific Independence
- Short Papers
- Learning to Complete Sentences
- The Huller: A Simple and Efficient Online SVM
- Inducing Hidden Markov Models to Model Long-Term Dependencies
- A Similar Fragments Merging Approach to Learn Automata on Proteins
- Nonnegative Lagrangian Relaxation of K-Means and Spectral Clustering
- Severe Class Imbalance: Why Better Algorithms Aren't the Answer
- Approximation Algorithms for Minimizing Empirical Error by Axis-Parallel Hyperplanes
- A Comparison of Approaches for Learning Probability Trees
- Counting Positives Accurately Despite Inaccurate Classification
- Optimal Stopping and Constraints for Diffusion Models of Signals with Discontinuities
- An Evolutionary Function Approximation Approach to Compute Prediction in XCSF
- Using Rewards for Belief State Updates in Partially Observable Markov Decision Processes
- Active Learning in Partially Observable Markov Decision Processes
- Machine Learning of Plan Robustness Knowledge About Instances
- Two Contributions of Constraint Programming to Machine Learning
- A Clustering Model Based on Matrix Approximation with Applications to Cluster System Log Files
- Detecting Fraud in Health Insurance Data: Learning to Model Incomplete Benford's Law Distributions
- Efficient Case Based Feature Construction
- Fitting the Smallest Enclosing Bregman Ball
- Similarity-Based Alignment and Generalization
- Fast Non-negative Dimensionality Reduction for Protein Fold Recognition
- Mode Directed Path Finding
- Classification with Maximum Entropy Modeling of Predictive Association Rules
- Classification of Ordinal Data Using Neural Networks
- Independent Subspace Analysis on Innovations
- On Applying Tabling to Inductive Logic Programming
- Learning Models of Relational Stochastic Processes
- Error-Sensitive Grading for Model Combination
- Strategy Learning for Reasoning Agents
- Combining Bias and Variance Reduction Techniques for Regression Trees
- Analysis of Generic Perceptron-Like Large Margin Classifiers
- Multimodal Function Optimizing by a New Hybrid Nonlinear Simplex Search and Particle Swarm Algorithm.