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» Gradient estimation in global optimization algorithms
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ECCV
2002
Springer
14 years 9 months ago
Hyperdynamics Importance Sampling
Sequential random sampling (`Markov Chain Monte-Carlo') is a popular strategy for many vision problems involving multimodal distributions over high-dimensional parameter spac...
Cristian Sminchisescu, Bill Triggs
CVPR
2000
IEEE
14 years 9 months ago
Dynamic Layer Representation with Applications to Tracking
A dynamic layer representation is proposed in this paper for tracking moving objects. Previous work on layered representations has largely concentrated on two-/multiframe batch fo...
Hai Tao, Harpreet S. Sawhney, Rakesh Kumar
GCB
2000
Springer
137views Biometrics» more  GCB 2000»
13 years 11 months ago
Detecting Sporadic Recombination in DNA Alignments with Hidden Markov Models
Conventional phylogenetic tree estimation methods assume that all sites in a DNA multiple alignment have the same evolutionary history. This assumption is violated in data sets fro...
Dirk Husmeier, Frank Wright
KDD
2012
ACM
207views Data Mining» more  KDD 2012»
11 years 10 months ago
Robust multi-task feature learning
Multi-task learning (MTL) aims to improve the performance of multiple related tasks by exploiting the intrinsic relationships among them. Recently, multi-task feature learning alg...
Pinghua Gong, Jieping Ye, Changshui Zhang
TSP
2010
13 years 2 months ago
Distributed sparse linear regression
The Lasso is a popular technique for joint estimation and continuous variable selection, especially well-suited for sparse and possibly under-determined linear regression problems....
Gonzalo Mateos, Juan Andrés Bazerque, Georg...