Probability learning in 1000 trials.

Probability learning in 1000 trials.

This paper reports a simple two-alternative noncontingent probability learning experiment with an uncon-ventional feature: each 5 made 1000 consecutive predictions, making possible very detailed analysis of responses which occurred after learning was essentially completed. Some abbreviations will be useful. The 5 1 predicts either L or R; after each prediction he observes either 1 or r. The pro...

Minimum Probability Flow Learning

Learning Probability Distributions

Learning Probability Distributions

Minimum Probability Flow Learning

Fitting probabilistic models to data is often difficult, due to the general intractability of the partition function and its derivatives. Here we propose a new parameter estimation technique that does not require computing an intractable normalization factor or sampling from the equilibrium distribution of the model. This is achieved by establishing dynamics that would transform the observed da...

Implementing Blended Learning for 1000 Mechanical Engineering Students

The module Techniques of Programming of the RWTH Aachen University is one of five case studies within the EU funded project Blend-XL – Finding a Balance in Blended Learning with eXtra Large Students Groups. During the project the module changed from a face-to-face module into a blended learning one. Therefore a blended learning concept has been developed which includes a special virtual learnin...