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ICASSP
2009
IEEE
14 years 14 days ago
Optimized opportunistic multicast scheduling (OMS) over heterogeneous cellular networks
Optimized opportunistic multicast scheduling (OMS) has been studied previously by the authors for homogeneous cellular networks, where the problem of efficiently transmitting a co...
Tze-Ping Low, Man-On Pun, Yao-Win Peter Hong, C.-C...
TWC
2010
13 years 3 months ago
Optimized opportunistic multicast scheduling (OMS) over wireless cellular networks
Optimized opportunistic multicast scheduling (OMS) is studied for cellular networks, where the problem of efficiently transmitting a common set of fountain-encoded data from a sin...
Tze-Ping Low, Man-On Pun, Yao-Win Peter Hong, C.-C...
SIAMCO
2002
121views more  SIAMCO 2002»
13 years 8 months ago
Consistent Approximations and Approximate Functions and Gradients in Optimal Control
As shown in [7], optimal control problems with either ODE or PDE dynamics can be solved efficiently using a setting of consistent approximations obtained by numerical discretizati...
Olivier Pironneau, Elijah Polak
TKDE
2012
245views Formal Methods» more  TKDE 2012»
11 years 11 months ago
Semi-Supervised Maximum Margin Clustering with Pairwise Constraints
—The pairwise constraints specifying whether a pair of samples should be grouped together or not have been successfully incorporated into the conventional clustering methods such...
Hong Zeng, Yiu-ming Cheung
JMLR
2006
124views more  JMLR 2006»
13 years 8 months ago
A Direct Method for Building Sparse Kernel Learning Algorithms
Many kernel learning algorithms, including support vector machines, result in a kernel machine, such as a kernel classifier, whose key component is a weight vector in a feature sp...
Mingrui Wu, Bernhard Schölkopf, Gökhan H...