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NN
1997
Springer
174views Neural Networks» more  NN 1997»
13 years 11 months ago
Learning Dynamic Bayesian Networks
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
Zoubin Ghahramani
APPROX
2006
Springer
120views Algorithms» more  APPROX 2006»
13 years 11 months ago
Single-Source Stochastic Routing
Abstract. We introduce and study the following model for routing uncertain demands through a network. We are given a capacitated multicommodity flow network with a single source an...
Shuchi Chawla, Tim Roughgarden
GLOBECOM
2008
IEEE
13 years 7 months ago
Power Efficient Throughput Maximization in Multi-Hop Wireless Networks
Abstract-- We study the problem of total throughput maximization in arbitrary multi-hop wireless networks, with constraints on the total power usage (denoted by PETM), when nodes h...
Deepti Chafekar, V. S. Anil Kumar, Madhav V. Marat...
DISOPT
2007
155views more  DISOPT 2007»
13 years 7 months ago
Linear-programming design and analysis of fast algorithms for Max 2-CSP
The class Max (r, 2)-CSP (or simply Max 2-CSP) consists of constraint satisfaction problems with at most two r-valued variables per clause. For instances with n variables and m bin...
Alexander D. Scott, Gregory B. Sorkin
IVC
2000
179views more  IVC 2000»
13 years 7 months ago
A system to place observers on a polyhedral terrain in polynomial time
The Art Gallery Problem deals with determining the number of observers necessary to cover an art gallery room such that every point is seen by at least one observer. This problem ...
Maurício Marengoni, Bruce A. Draper, Allen ...