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ICASSP
2011
IEEE
14 years 10 months ago
Application specific loss minimization using gradient boosting
Gradient boosting is a flexible machine learning technique that produces accurate predictions by combining many weak learners. In this work, we investigate its use in two applica...
Bin Zhang, Abhinav Sethy, Tara N. Sainath, Bhuvana...
ECBS
2007
IEEE
209views Hardware» more  ECBS 2007»
16 years 23 days ago
Aspect-Oriented Modeling of Ubiquitous Web Applications: The aspectWebML Approach
Ubiquitous web applications (UWA) are required to be customizable, meaning their services need to be adaptable towards the context of use, e.g., user, location, time, and device. ...
Andrea Schauerhuber, Manuel Wimmer, Wieland Schwin...
KESAMSTA
2007
Springer
16 years 17 days ago
Mobile Collaboration Framework for u-Healthcare Agent Services and Its Application Using PDAs
In this paper, we suggested a mobile collaboration framework based on distributed object group framework (DOGF). This paper focuses on the use of this framework to support mobile c...
Chang-Won Jeong, Dong-Ho Kim, Su-Chong Joo
CORR
2011
Springer
167views Education» more  CORR 2011»
15 years 1 months ago
Fully Simulatable Quantum-Secure Coin-Flipping and Applications
We propose a coin-flip protocol which yields a string of strong, random coins and is fully simulatable against poly-sized quantum adversaries on both sides. It can be implemented ...
Carolin Lunemann, Jesper Buus Nielsen
CVPR
2005
IEEE
16 years 8 months ago
Learning a Similarity Metric Discriminatively, with Application to Face Verification
We present a method for training a similarity metric from data. The method can be used for recognition or verification applications where the number of categories is very large an...
Sumit Chopra, Raia Hadsell, Yann LeCun