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» Machine-Learning Applications of Algorithmic Randomness
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AAAI
2000
13 years 9 months ago
Decision Making under Uncertainty: Operations Research Meets AI (Again)
Models for sequential decision making under uncertainty (e.g., Markov decision processes,or MDPs) have beenstudied in operations research for decades. The recent incorporation of ...
Craig Boutilier
AI
2010
Springer
13 years 8 months ago
Understanding the scalability of Bayesian network inference using clique tree growth curves
Bayesian networks (BNs) are used to represent and ef ciently compute with multi-variate probability distributions in a wide range of disciplines. One of the main approaches to per...
Ole J. Mengshoel
BMCBI
2010
162views more  BMCBI 2010»
13 years 8 months ago
Moara: a Java library for extracting and normalizing gene and protein mentions
Background: Gene/protein recognition and normalization are important preliminary steps for many biological text mining tasks, such as information retrieval, protein-protein intera...
Mariana L. Neves, José María Carazo,...
BMCBI
2008
106views more  BMCBI 2008»
13 years 8 months ago
A machine vision system for automated non-invasive assessment of cell viability via dark field microscopy, wavelet feature selec
Background: Cell viability is one of the basic properties indicating the physiological state of the cell, thus, it has long been one of the major considerations in biotechnologica...
Ning Wei, Erwin Flaschel, Karl Friehs, Tim W. Natt...
NECO
2007
150views more  NECO 2007»
13 years 7 months ago
Reinforcement Learning, Spike-Time-Dependent Plasticity, and the BCM Rule
Learning agents, whether natural or artificial, must update their internal parameters in order to improve their behavior over time. In reinforcement learning, this plasticity is ...
Dorit Baras, Ron Meir