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ICDM
2008
IEEE
97views Data Mining» more  ICDM 2008»
14 years 2 months ago
Semi-supervised Learning from General Unlabeled Data
We consider the problem of Semi-supervised Learning (SSL) from general unlabeled data, which may contain irrelevant samples. Within the binary setting, our model manages to better...
Kaizhu Huang, Zenglin Xu, Irwin King, Michael R. L...
ICCD
2001
IEEE
121views Hardware» more  ICCD 2001»
14 years 4 months ago
Determining Schedules for Reducing Power Consumption Using Multiple Supply Voltages
Dynamic power is the main source of power consumption in CMOS circuits. It depends on the square of the supply voltage. It may significantly be reduced by scaling down the supply ...
Noureddine Chabini, El Mostapha Aboulhamid, Yvon S...
CORR
2008
Springer
115views Education» more  CORR 2008»
13 years 7 months ago
Adaptive Sum Power Iterative Waterfilling for MIMO Cognitive Radio Channels
Abstract--In this paper, the sum capacity of the Gaussian Multiple Input Multiple Output (MIMO) Cognitive Radio Channel (MCC) is expressed as a convex problem with finite number of...
Rajiv Soundararajan, Sriram Vishwanath
FOCS
2000
IEEE
14 years 17 hour ago
Extracting Randomness from Samplable Distributions
Randomness extractors convert weak sources of randomness into an almost uniform distribution; the conversion uses a small amount of pure randomness. In algorithmic applications, t...
Luca Trevisan, Salil P. Vadhan
FOCS
2005
IEEE
14 years 1 months ago
Sampling-based Approximation Algorithms for Multi-stage Stochastic
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
Chaitanya Swamy, David B. Shmoys