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» Decision-Theoretic Rough Set Models
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SODA
2000
ACM
85views Algorithms» more  SODA 2000»
13 years 8 months ago
Improved bounds on the sample complexity of learning
We present a new general upper bound on the number of examples required to estimate all of the expectations of a set of random variables uniformly well. The quality of the estimat...
Yi Li, Philip M. Long, Aravind Srinivasan
SMI
2003
IEEE
143views Image Analysis» more  SMI 2003»
14 years 24 days ago
Rough Surface Modeling Using Surface Growth
In this paper, we present a novel modeling method for synthesizing rough surfaces using discrete surface growth models. We employ a two-pass method. Initial point cluster data is ...
Yootai Kim, Raghu Machiraju, David Thompson
COSIT
2009
Springer
165views GIS» more  COSIT 2009»
14 years 2 months ago
To Be and Not To Be: 3-Valued Relations on Graphs
Spatial information requires models which allow us to answer ‘maybe’ to questions asking whether a location lies within a region. At the same time, models must account for data...
John G. Stell
TSP
2008
123views more  TSP 2008»
13 years 7 months ago
A Rough Programming Approach to Power-Balanced Instruction Scheduling for VLIW Digital Signal Processors
The focus of this paper is on VLIW instruction scheduling that minimizes the variation of power consumed by the processor during the execution of a target program. We use rough set...
Shu Xiao, Edmund Ming-Kit Lai
AAAI
2010
13 years 9 months ago
Collaborative Expert Portfolio Management
We consider the task of assigning experts from a portfolio of specialists in order to solve a set of tasks. We apply a Bayesian model which combines collaborative filtering with a...
David H. Stern, Horst Samulowitz, Ralf Herbrich, T...