Algorithmic Learning Theory Book

	Abduction and the Dualization Problem	1
	Signal Extraction and Knowledge Discovery Based on Statistical Modeling	3
	Association Computation for Information Access	15
	Efficient Data Representations That Preserve Information	16
	Can Learning in the Limit Be Done Efficiently?	17
	Intrinsic Complexity of Uniform Learning	39
	On Ordinal VC-Dimensional and Some Notions of Complexity	54
	Learning of Erasing Primitive Formal Systems from Positive Examples	69
	Changing the Inference Type - Keeping the Hypothesis Space	84
	Robust Inference of Relevant Attributes	99
	Efficient Learning of Ordered and Unordered Tree Patterns with Contractible Variables	114
	On the Learnability of Erasing Pattern Languages in the Query Model	129
	Learning of Finite Unions of Tree Patterns with Repeated Internal Structured Variables from Queries	144
	Kernel Trick Embedded Gaussian Mixture Model	159
	Efficiently Learning the Metric with Side-Information	175
	Learning Continuous Latent Variable Models with Bregman Divergences	190
	A Stochastic Gradient Descent Algorithm for Structural Risk Minimisation	205
	On the Complexity of Training a Single Perceptron with Programmable Synaptic Delays	221
	Learning a Subclass of Regular Patterns in Polynomial Time	234
	Identification with Probability One of Stochastic Deterministic Linear Languages	247
	Criterion of Calibration for Transductive Confidence Machine with Limited Feedback	259
	Well-Calibrated Predictions from Online Compression Models	268
	Transductive Confidence Machine Is Universal	283
	On the Existence and Convergence of Computable Universal Priors	298
	Author Index	313