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ECML
1998
Springer
13 years 12 months ago
First-Order Learning for Web Mining
We present compelling evidence that the World Wide Web is a domain in which applications can benefit from using first-order learning methods, since the graph structure inherent in ...
Mark Craven, Seán Slattery, Kamal Nigam
UAI
2008
13 years 9 months ago
Learning Hidden Markov Models for Regression using Path Aggregation
We consider the task of learning mappings from sequential data to real-valued responses. We present and evaluate an approach to learning a type of hidden Markov model (HMM) for re...
Keith Noto, Mark Craven
ICML
2010
IEEE
13 years 5 months ago
Approximate Predictive Representations of Partially Observable Systems
We provide a novel view of learning an approximate model of a partially observable environment from data and present a simple implemenf the idea. The learned model abstracts away ...
Monica Dinculescu, Doina Precup
AAAI
2008
13 years 10 months ago
A Case Study on the Critical Role of Geometric Regularity in Machine Learning
An important feature of many problem domains in machine learning is their geometry. For example, adjacency relationships, symmetries, and Cartesian coordinates are essential to an...
Jason Gauci, Kenneth O. Stanley
AIIDE
2006
13 years 9 months ago
Designing a Reinforcement Learning-based Adaptive AI for Large-Scale Strategy Games
This paper investigates the challenges posed by the application of reinforcement learning to large-scale strategy games. In this context, we present steps and techniques which syn...
Charles A. G. Madeira, Vincent Corruble, Geber Ram...