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PPSN
1990
Springer
15 years 9 months ago
Feature Construction for Back-Propagation
T h e ease of learning concepts f r o m examples in empirical machine learning depends on the attributes used for describing the training d a t a . We show t h a t decision-tree b...
Selwyn Piramuthu
HPCC
2011
Springer
14 years 4 months ago
Achieving Performance and Availability Guarantees with Spot Instances
Abstract—In the Infrastructure-as-a-Service (IaaS) cloud computing market, spot instances refer to virtual servers that are rented via an auction. Spot instances allow IaaS provi...
Michele Mazzucco, Marlon Dumas

Publication
211views
17 years 3 months ago
Congestion Avoidance in Computer Networks with A Connecitonless Network Layer: Part IV: A Selective Binary Feedback Scheme for G
With increasingly widespread use of computer networks, and the use of varied technology for the interconnection of computers, congestion is a significant problem. In this report, w...
K. Ramakrishnan and R. Jain,
CVPR
2004
IEEE
16 years 7 months ago
An Algorithm for Multiple Object Trajectory Tracking
Most tracking algorithms are based on the maximum a posteriori (MAP) solution of a probabilistic framework called Hidden Markov Model, where the distribution of the object state a...
Mei Han, Wei Xu, Hai Tao, Yihong Gong
CVPR
2005
IEEE
16 years 7 months ago
Local Color Transfer via Probabilistic Segmentation by Expectation-Maximization
We address the problem of regional color transfer between two natural images by probabilistic segmentation. We use a new Expectation-Maximization (EM) scheme to impose both spatia...
Yu-Wing Tai, Jiaya Jia, Chi-Keung Tang
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