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» The possible and the impossible in multi-agent learning
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JMLR
2002
117views more  JMLR 2002»
13 years 7 months ago
Learning to Construct Fast Signal Processing Implementations
A single signal processing algorithm can be represented by many mathematically equivalent formulas. However, when these formulas are implemented in code and run on real machines, ...
Bryan Singer, Manuela M. Veloso
PRL
2011
12 years 10 months ago
A Bayes-true data generator for evaluation of supervised and unsupervised learning methods
Benchmarking pattern recognition, machine learning and data mining methods commonly relies on real-world data sets. However, there are some disadvantages in using real-world data....
Janick V. Frasch, Aleksander Lodwich, Faisal Shafa...
AAAI
2006
13 years 8 months ago
On the Difficulty of Modular Reinforcement Learning for Real-World Partial Programming
In recent years there has been a great deal of interest in "modular reinforcement learning" (MRL). Typically, problems are decomposed into concurrent subgoals, allowing ...
Sooraj Bhat, Charles Lee Isbell Jr., Michael Matea...
ICDAR
2005
IEEE
14 years 1 months ago
Text Recognition of Low-resolution Document Images
Cheap and versatile cameras make it possible to easily and quickly capture a wide variety of documents. However, low resolution cameras present a challenge to OCR because it is vi...
Charles E. Jacobs, Patrice Y. Simard, Paul A. Viol...
RSFDGRC
2005
Springer
190views Data Mining» more  RSFDGRC 2005»
14 years 26 days ago
Finding Rough Set Reducts with SAT
Abstract. Feature selection refers to the problem of selecting those input features that are most predictive of a given outcome; a problem encountered in many areas such as machine...
Richard Jensen, Qiang Shen, Andrew Tuson