Intersections between theory and experiment

Part 1 Learning theory: Bayes decisions in a neural network-PAC setting, Svetlana Anulova et al average case analysis of kappa-CNF and kappa-DNF learning algorithms, Daniel S. Hirschberg et al filter likelihoods and exhaustive learning, David H. Wolpert. Part 2 Model selection and inductive bias: incorporating prior knowledge into networks of locally-tuned units, Martin Roscheisen et al using knowledge-based neural networks to refine roughly-correct information, Geoffrey G. Towell and Jude W. Shavlik sensitivity constraints in learning, Scott H. Clearwater and Yongwon Lee evaluation of learning biases using probabilistic domain knowledge, Marie desJardins detecting structure in small datasets by network fitting under complexity constraints, W. Finnoff and H.G. Zimmermann associative methods in reinforcement learning - an empirical study, Leslie Pack Kaelbling. Part 3 Learning algorithms: a schema for using multiple knowledge, Matjaz Gams et al probabilistic hill-climbing, William W. Cohen et al prototype selection using competitive learning, Michael Lemmon learning with instance-based encodings, Henry Tirri contrastive learning with graded random networks, Javier R. Movellan and James L. McClelland probability density estimation and local basis function neural networks, Padhraic Smyth. Part 4 Dynamics of learning: Hamiltonian dynamics of neural networks, Ulrich Ramacher learning properties of multi-layer perceptrons with and without feedback, D. Gawronska et al. Part 5 Applications: unsupervised learning for mobile robot navigation using probabilistic data association, Ingemar J. Cox and John J. Leonard evolution of a subsumption architecture that performs a wall following task for an autonomous mobile robot, John R. Koza a connectionist model of the learning of personal pronouns in English, Thomas R. Shultz et al neural network modelling of physiological processes, Volker Tresp et al projection pursuit learning - some theoretical issues, Ying Zhao and Christopher G. Atkeson a comparative study of the Kohonen self-organizing map and the elastic net, Yiu-fai Wong.