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COLT
2000
Springer
13 years 11 months ago
Barrier Boosting
Boosting algorithms like AdaBoost and Arc-GV are iterative strategies to minimize a constrained objective function, equivalent to Barrier algorithms. Based on this new understandi...
Gunnar Rätsch, Manfred K. Warmuth, Sebastian ...
ICDM
2006
IEEE
130views Data Mining» more  ICDM 2006»
14 years 1 months ago
Boosting for Learning Multiple Classes with Imbalanced Class Distribution
Classification of data with imbalanced class distribution has posed a significant drawback of the performance attainable by most standard classifier learning algorithms, which ...
Yanmin Sun, Mohamed S. Kamel, Yang Wang 0007
MJ
2008
148views more  MJ 2008»
13 years 7 months ago
Drive current boosting of n-type tunnel FET with strained SiGe layer at source
Though silicon tunnel field effect transistor (TFET) has attracted attention for sub-60 mV/decade subthreshold swing and very small OFF current (IOFF), its practical application i...
Nayan Patel, A. Ramesha, Santanu Mahapatra
PAMI
2012
11 years 9 months ago
Learning Optimal Embedded Cascades
—The problem of automatic and optimal design of embedded object detector cascades is considered. Two main challenges are identified: optimization of the cascade configuration and...
Mohammad Javad Saberian, Nuno Vasconcelos
GPC
2007
Springer
14 years 1 months ago
A Thin Client Approach to Supporting Adaptive Session Mobility
Recent growth in computing devices from the smartphone to the desktop computer has led to users interacting with multiple computing devices throughout the course of the day. Modern...
Daniel MacCormac, Mark Deegan, Fred Mtenzi, Brenda...