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PPSN
1990
Springer
15 years 6 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 2 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 15 days 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 4 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 4 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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