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ML
2012
ACM
413views Machine Learning» more  ML 2012»
13 years 5 months ago
Gradient-based boosting for statistical relational learning: The relational dependency network case
Dependency networks approximate a joint probability distribution over multiple random variables as a product of conditional distributions. Relational Dependency Networks (RDNs) are...
Sriraam Natarajan, Tushar Khot, Kristian Kersting,...
SASO
2009
IEEE
15 years 4 months ago
Controlling Particle Swarm Optimization with Learned Parameters
—Controlling particle swarm optimization is typically an unintuitive task, involving a process of adjusting low-level parameters of the system that often do not have obvious corr...
Kevin Winner, Don Miner, Marie desJardins
ICCAD
2008
IEEE
107views Hardware» more  ICCAD 2008»
15 years 4 months ago
Importance sampled circuit learning ensembles for robust analog IC design
This paper presents ISCLEs, a novel and robust analog design method that promises to scale with Moore’s Law, by doing boosting-style importance sampling on digital-sized circuit...
Peng Gao, Trent McConaghy, Georges G. E. Gielen
ICRA
2006
IEEE
177views Robotics» more  ICRA 2006»
15 years 3 months ago
Autonomous Shape Model Learning for Object Localization and Recognition
— Mobile robots do not adequately represent the objects in their environment; this weakness hinders a robot’s ability to utilize past experience. In this paper, we describe a s...
Joseph Modayil, Benjamin Kuipers
ICDAR
2005
IEEE
15 years 3 months ago
Language Identification of Character Images Using Machine Learning Techniques
In this paper, we propose a new approach for identifying the language type of character images. We do this by classifying individual character images to determine the language bou...
Ying-Ho Liu, Fu Chang, Chin-Chin Lin