Algorithmic Learning Theory

Grammatical inference: An old and new paradigm.- Efficient learning of real time one-counter automata.- Learning strongly deterministic even linear languages from positive examples.- Language learning from membership queries and characteristic examples.- Learning unions of tree patterns using queries.- Inductive constraint logic.- Incremental learning of logic programs.- Learning orthogonal F-Horn formulas.- Learning nested differences in the presence of malicious noise.- Learning sparse linear combinations of basis functions over a finite domain.- Inferring a DNA sequence from erroneous copies (abstract).- Machine induction without revolutionary paradigm shifts.- Probabilistic language learning under monotonicity constraints.- Noisy inference and oracles.- Simulating teams with many conjectures.- Complexity of network training for classes of Neural Networks.- Learning ordered binary decision diagrams.- Simple PAC learning of simple decision lists.- The complexity of learning minor closed graph classes.- Technical and scientific issues of KDD (or: Is KDD a science?).- Analogical logic program synthesis algorithm that can refute inappropriate similarities.- Reflecting and self-confident inductive inference machines.- On approximately identifying concept classes in the limit.- Application of kolmogorov complexity to inductive inference with limited memory.