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» Quantization of Discrete Probability Distributions
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TIT
2008
80views more  TIT 2008»
13 years 7 months ago
Entropy Amplification Property and the Loss for Writing on Dirty Paper
Costa's celebrated "writing on dirty paper" (WDP) shows that the powerconstrained channel Y = X + S + Z, with Gaussian Z, has the same capacity as the standard AWGN...
Aaron S. Cohen, Ram Zamir
SIGMETRICS
2002
ACM
128views Hardware» more  SIGMETRICS 2002»
13 years 7 months ago
High-density model for server allocation and placement
It is well known that optimal server placement is NP-hard. We present an approximate model for the case when both clients and servers are dense, and propose a simple server alloca...
Craig W. Cameron, Steven H. Low, David X. Wei
TSP
2010
13 years 2 months ago
Energy efficient state estimation with wireless sensors through the use of predictive power control and coding
We study state estimation via wireless sensors over fading channels. Packet loss probabilities depend upon time-varying channel gains, packet lengths and transmission power levels ...
Daniel E. Quevedo, Anders Ahlén, Jan &Oslas...
NCA
2005
IEEE
14 years 1 months ago
Using Residual Times to Meet Deadlines in M/G/C Queues
In systems where customer service demands are only known probabilistically, there is very little to distinguish between jobs. Therefore, no universal optimum scheduling strategy o...
Sarah Tasneem, Lester Lipsky, Reda A. Ammar, Howar...
FOCS
2004
IEEE
13 years 11 months ago
Stochastic Optimization is (Almost) as easy as Deterministic Optimization
Stochastic optimization problems attempt to model uncertainty in the data by assuming that (part of) the input is specified in terms of a probability distribution. We consider the...
David B. Shmoys, Chaitanya Swamy