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ICML
2004
IEEE
14 years 8 months ago
Training conditional random fields via gradient tree boosting
Conditional Random Fields (CRFs; Lafferty, McCallum, & Pereira, 2001) provide a flexible and powerful model for learning to assign labels to elements of sequences in such appl...
Thomas G. Dietterich, Adam Ashenfelter, Yaroslav B...
INFOCOM
2008
IEEE
14 years 1 months ago
Iso-Contour Queries and Gradient Descent with Guaranteed Delivery in Sensor Networks
—We study the problem of data-driven routing and navigation in a distributed sensor network over a continuous scalar field. Specifically, we address the problem of searching fo...
Rik Sarkar, Xianjin Zhu, Jie Gao, Leonidas J. Guib...
ATAL
2008
Springer
13 years 9 months ago
MB-AIM-FSI: a model based framework for exploiting gradient ascent multiagent learners in strategic interactions
Future agent applications will increasingly represent human users autonomously or semi-autonomously in strategic interactions with similar entities. Hence, there is a growing need...
Doran Chakraborty, Sandip Sen
ASPDAC
2004
ACM
101views Hardware» more  ASPDAC 2004»
14 years 24 days ago
A sub-mW MPEG-4 motion estimation processor core for mobile video application
This paper describes a sub-mW motion estimation processor core for MPEG-4 video encoding. It features a Gradient Descent Search algorithm whose computation power is only 7% of the...
Yuki Kuroda, Junichi Miyakoshi, Masayuki Miyama, K...
NIPS
1998
13 years 8 months ago
Gradient Descent for General Reinforcement Learning
A simple learning rule is derived, the VAPS algorithm, which can be instantiated to generate a wide range of new reinforcementlearning algorithms. These algorithms solve a number ...
Leemon C. Baird III, Andrew W. Moore