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» An algorithm for minimizing the Mumford-Shah functional
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NIPS
2007
13 years 10 months ago
The Price of Bandit Information for Online Optimization
In the online linear optimization problem, a learner must choose, in each round, a decision from a set D ⊂ Rn in order to minimize an (unknown and changing) linear cost function...
Varsha Dani, Thomas P. Hayes, Sham Kakade
NPL
2006
172views more  NPL 2006»
13 years 9 months ago
Adapting RBF Neural Networks to Multi-Instance Learning
In multi-instance learning, the training examples are bags composed of instances without labels, and the task is to predict the labels of unseen bags through analyzing the training...
Min-Ling Zhang, Zhi-Hua Zhou
SIAMJO
2002
92views more  SIAMJO 2002»
13 years 8 months ago
Generalized Bundle Methods
We study a class of generalized bundle methods for which the stabilizing term can be any closed convex function satisfying certain properties. This setting covers several algorithm...
Antonio Frangioni
INFOCOM
2005
IEEE
14 years 2 months ago
Smart power-saving mode for IEEE 802.11 wireless LANs
StaticPSM (Power-Saving Mode)schemes employed in the current IEEE 802.11 implementations could not provide any delag-performance guarantee because of their fixed wakeup intervals. ...
Daji Qiao, Kang G. Shin
TJS
2002
160views more  TJS 2002»
13 years 8 months ago
Adaptive Optimizing Compilers for the 21st Century
Historically, compilers have operated by applying a fixed set of optimizations in a predetermined order. We call such an ordered list of optimizations a compilation sequence. This...
Keith D. Cooper, Devika Subramanian, Linda Torczon