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JMLR
2006
169views more  JMLR 2006»
14 years 11 months ago
Bayesian Network Learning with Parameter Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
NECO
2007
150views more  NECO 2007»
14 years 10 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
IROS
2006
IEEE
152views Robotics» more  IROS 2006»
15 years 5 months ago
Locomotion Imitation of Humanoid Using Goal-directed Self-adjusting Adaptor
- We propose a novel framework for imitation learning that helps a humanoid robot achieve its goal of learning. There are apparent discrepancies in shapes and sizes among humans an...
Woosung Yang, Nak Young Chong, ChangHwan Kim, Bum-...
NETWORKING
2004
15 years 18 days ago
On Detection of Anomalous Routing Dynamics in BGP
BGP, the de facto inter-domain routing protocol, is the core component of current Internet infrastructure. BGP traffic deserves thorough exploration, since abnormal BGP routing dy...
Ke Zhang, Amy Yen, Xiaoliang Zhao, Daniel Massey, ...
JMS
2010
90views more  JMS 2010»
14 years 9 months ago
Prediction of Clinical Conditions after Coronary Bypass Surgery using Dynamic Data Analysis
This work studies the impact of using dynamic information as features in a machine learning algorithm for the prediction task of classifying critically ill patients in two classes ...
Kristien Van Loon, Fabián Güiza, Geert...