Algorithmic Learning Theory 18th International Conference, ALT 2007, Sendai, Japan, October 1-4, 2007, Proceedings
This volume contains the papers presented at the 18th International Conf- ence on Algorithmic Learning Theory (ALT 2007), which was held in Sendai (Japan) during October 1–4, 2007. The main objective of the conference was to provide an interdisciplinary forum for high-quality talks with a strong the...
| Other Authors: | , , |
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| Format: | eBook |
| Language: | English |
| Published: |
Berlin, Heidelberg
Springer Berlin Heidelberg
2007, 2007
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| Edition: | 1st ed. 2007 |
| Series: | Lecture Notes in Artificial Intelligence
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| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- Online Regression Competitive with Changing Predictors
- Unsupervised Learning
- Cluster Identification in Nearest-Neighbor Graphs
- Multiple Pass Streaming Algorithms for Learning Mixtures of Distributions in
- Language Learning
- Learning Efficiency of Very Simple Grammars from Positive Data
- Learning Rational Stochastic Tree Languages
- Query Learning
- One-Shot Learners Using Negative Counterexamples and Nearest Positive Examples
- Polynomial Time Algorithms for Learning k-Reversible Languages and Pattern Languages with Correction Queries
- Learning and Verifying Graphs Using Queries with a Focus on Edge Counting
- Exact Learning of Finite Unions of Graph Patterns from Queries
- Kernel-Based Learning
- Polynomial Summaries of Positive Semidefinite Kernels
- Learning Kernel Perceptrons on Noisy Data Using Random Projections
- Continuityof Performance Metrics for Thin Feature Maps
- Other Directions
- Editors’ Introduction
- Editors’ Introduction
- Invited Papers
- A Theory of Similarity Functions for Learning and Clustering
- Machine Learning in Ecosystem Informatics
- Challenge for Info-plosion
- A Hilbert Space Embedding for Distributions
- Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity and Creativity
- Invited Papers
- Feasible Iteration of Feasible Learning Functionals
- Parallelism Increases Iterative Learning Power
- Prescribed Learning of R.E. Classes
- Learning in Friedberg Numberings
- Complexity Aspects of Learning
- Separating Models of Learning with Faulty Teachers
- Vapnik-Chervonenkis Dimension of Parallel Arithmetic Computations
- Parameterized Learnability of k-Juntas and Related Problems
- On Universal Transfer Learning
- Online Learning
- Tuning Bandit Algorithms in Stochastic Environments
- Following the Perturbed Leader to Gamble at Multi-armed Bandits
- Multiclass Boosting Algorithms for Shrinkage Estimators of Class Probability
- Pseudometrics for State Aggregation in Average Reward Markov Decision Processes
- On Calibration Error of Randomized Forecasting Algorithms