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ECML
2006
Springer
15 years 10 months ago
Active Learning with Irrelevant Examples
Abstract. Active learning algorithms attempt to accelerate the learning process by requesting labels for the most informative items first. In real-world problems, however, there ma...
Dominic Mazzoni, Kiri Wagstaff, Michael C. Burl
GECCO
2006
Springer
174views Optimization» more  GECCO 2006»
15 years 10 months ago
On the analysis of the (1+1) memetic algorithm
Memetic algorithms are evolutionary algorithms incorporating local search to increase exploitation. This hybridization has been fruitful in countless applications. However, theory...
Dirk Sudholt
AAAI
2007
15 years 9 months ago
Using Expectation Maximization to Find Likely Assignments for Solving CSP's
We present a new probabilistic framework for finding likely variable assignments in difficult constraint satisfaction problems. Finding such assignments is key to efficient sea...
Eric I. Hsu, Matthew Kitching, Fahiem Bacchus, She...
FLAIRS
2008
15 years 9 months ago
Conditional and Composite Constraints with Preferences
Preferences in constraint problems are common but significant in many real world applications. In this paper, we extend our conditional and composite CSP (CCCSP) framework, managi...
Malek Mouhoub, Amrudee Sukpan
APLAS
2008
ACM
15 years 8 months ago
The Complexity of Coverage
Abstract. We study the problem of generating a test sequence that achieves maximal coverage for a reactive system under test. We formulate the problem as a repeated game between th...
Krishnendu Chatterjee, Luca de Alfaro, Rupak Majum...