Table of Contens

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M. Blum
Turning PAC learning into PERFECT learning (Invited Lecture) 1 - 1


A. Ambainis, K. Apsitis, R. Freivalds, W. Gasarch, and C.H. Smith
Team learning as a game 2 - 17
E. Hirowatari and S. Arikawa
Inferability of recursive real-valued functions 18 - 31
S. Jain, S. Lange, and J. Nessel
Learning of r.e. languages from good examples 32 - 47
S. Kobayashi and T. Yokomori
Identifiability of subspaces and homomorphic images of
zero-reversible languages
48 - 61


L. Pitt
On exploiting knowledge and concept use in learning theory
(invited lecture)
62 - 84


C. Domingo, T. Tsukiji, and O. Watanabe
Partial Occam's razor and its applications 85 - 99
M. Sitharam and T. Straney
Derandomized learning of Boolean functions 100 - 115
R. Parekh and V. Honavar
Learning DFA from simple examples 116 - 131


F. Denis and R. Gilleron
PAC learning under helpful distributions 132 - 145
H. Qiao, N.S.V. Rao, and V. Protopopescu
PAC learning using Nadaraya-Watson estimator based on orthonormal systems 146 - 160
E. Boros, T. Ibaraki, and K. Makino
Monotone extensions of Boolean data sets 161 - 175


M. Sato
Classical Brouwer-Heyting-Kolmogorov interpretation (invited lecture) 176 - 196


Y. Mukouchi
Inferring a system from examples with time passage 197 - 211
S. Matsumoto, Y. Hayashi, and T. Shoudai
Polynomial time inductive inference of regular term tree languages from positive data 212 - 227
J. Case, S. Jain, and A. Sharma
Synthesizing noise-tolerant language learners 228 - 243
A. Ambainis, K. Apsitis, C. Calude, R. Freivalds, M. Karpinski, T. Larfeldt, I. Sala,
and J. Smotrovs
Effects of Kolmogorov complexity present in inductive inference as well 244 - 259


T. Erlebach, P. Rossmanith, H. Stadtherr, A. Steger, and T. Zeugmann
Learning one-variable pattern languages very efficiently on average,
in parallel, and by asking queries

260 - 276
J. Köbler and W. Lindner
Oracles in $\Sigma_2^p$ are sufficient for exact learning 277 - 290
V. Arvind and N.,V. Vinodchandran
Exact learning via teaching assistants 291 - 306
A. Nakamura
An efficient exact learning algorithm for ordered binary decision diagrams 307 - 322


V. Vovk
Probability theory for the Brier game 323 - 338
X. Zhang and M. Numao
Learning and revising theories in noisy domains 339 - 351
L. Gurvits
A note on a scale-sensitive dimension of linear bounded functionals in Banach spaces 352 - 363


W. Maass
On the relevance of time in neural computation and learning (invited lecture) 364 - 384


E. Takimoto, K. Hirai, and A. Maruoka
A simple algorithm for predicting nearly as well as the best pruning labeled
with the best prediction values of a decision tree
385 - 400
S. Kwek
Learning disjunctions of features 401 - 415
H. Sakamoto
Learning simple deterministic finite-memory automata 416 - 431


H. Arimura
Learning acyclic first-order Horn sentences from entailment 432 - 445
T. Hegedüs and P. Indyk
On learning disjunctions of zero-one threshold functions with queries 446 - 460
Author Index
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