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UAI
2008
15 years 7 months ago
Learning Hidden Markov Models for Regression using Path Aggregation
We consider the task of learning mappings from sequential data to real-valued responses. We present and evaluate an approach to learning a type of hidden Markov model (HMM) for re...
Keith Noto, Mark Craven
ISCAS
2005
IEEE
144views Hardware» more  ISCAS 2005»
15 years 12 months ago
A method for online secondary path modeling in active noise control systems
— This paper proposes a new method for online secondary path modeling in active noise control (ANC) systems. The proposed method is a modified version of the basic method, propo...
Muhammad Tahir Akhtar, Masahide Abe, Masayuki Kawa...
ICAI
2008
15 years 7 months ago
Computationally Efficient Path-Following using Adaptive Color Models
The ability to follow man-made paths and roads is an important capability for a number of robotic tasks. To operate in outdoor environments designed for humans, autonomous robots m...
Stuart Glaser, Eitan Marder-Eppstein, William Smar...
JCNS
2010
103views more  JCNS 2010»
15 years 1 months ago
Efficient computation of the maximum a posteriori path and parameter estimation in integrate-and-fire and more general state-spa
A number of important data analysis problems in neuroscience can be solved using state-space models. In this article, we describe fast methods for computing the exact maximum a pos...
Shinsuke Koyama, Liam Paninski
CVPR
1996
IEEE
15 years 10 months ago
Global Minimum for Active Contour Models: A Minimal Path Approach
A new boundary detection approach for shape modeling is presented. It detects the global minimum of an active contour model's energy between two end points. Initialization is ...
Laurent D. Cohen, Ron Kimmel