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ICML
2006
IEEE
16 years 7 months ago
Probabilistic inference for solving discrete and continuous state Markov Decision Processes
Inference in Markov Decision Processes has recently received interest as a means to infer goals of an observed action, policy recognition, and also as a tool to compute policies. ...
Marc Toussaint, Amos J. Storkey
ICML
2000
IEEE
16 years 7 months ago
Maximum Entropy Markov Models for Information Extraction and Segmentation
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
Andrew McCallum, Dayne Freitag, Fernando C. N. Per...
ICML
1998
IEEE
16 years 7 months ago
A Fast, Bottom-Up Decision Tree Pruning Algorithm with Near-Optimal Generalization
In this work, we present a new bottom-up algorithmfor decision tree pruning that is very e cient requiring only a single pass through the given tree, and prove a strong performanc...
Michael J. Kearns, Yishay Mansour
WWW
2004
ACM
16 years 7 months ago
Post-processing inkml for random-access navigation of voluminous handwritten ink documents
The goal of this research is the improvement of browsing voluminous InkML data in two areas: ease of rendering continuous inkflow for replay-browsing, and ease of random access na...
Khaireel A. Mohamed, Lioudmila Belenkaia, Thomas O...
WWW
2004
ACM
16 years 7 months ago
E-learning personalization based on itineraries and long-term navigational behavior
In this paper we describe a practical framework for studying the navigational behavior of the users of an e-learning environment integrated in a virtual campus. The students navig...
Enric Mor, Julià Minguillón