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» Using Classifiers to Solve Warehouse Location Problems
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DAGSTUHL
1994
15 years 4 months ago
Competitive Strategies for Autonomous Systems
A strategy for working with incomplete information is called competitive if it solves each problem instance at a cost not exceeding the cost of an optimal solution (with full info...
Christian Icking, Rolf Klein
TCAD
2008
97views more  TCAD 2008»
15 years 2 months ago
Encoding Large Asynchronous Controllers With ILP Techniques
State encoding is one of the most difficult problems in the synthesis of asynchronous controllers. This paper presents a method that can solve the problem of large controllers spec...
Josep Carmona, Jordi Cortadella
AUSAI
2008
Springer
15 years 5 months ago
Learning to Find Relevant Biological Articles without Negative Training Examples
Classifiers are traditionally learned using sets of positive and negative training examples. However, often a classifier is required, but for training only an incomplete set of pos...
Keith Noto, Milton H. Saier Jr., Charles Elkan
CVPR
2010
IEEE
15 years 11 months ago
Locality-constrained Linear Coding for Image Classification
The traditional SPM approach based on bag-of-features (BoF) must use nonlinear classifiers to achieve good image classification performance. This paper presents a simple but effec...
Jinjun Wang, Jianchao Yang, Kai Yu, Fengjun Lv
AUSDM
2008
Springer
211views Data Mining» more  AUSDM 2008»
15 years 5 months ago
LBR-Meta: An Efficient Algorithm for Lazy Bayesian Rules
LBR is a highly accurate classification algorithm, which lazily constructs a single Bayesian rule for each test instance at classification time. However, its computational complex...
Zhipeng Xie