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» Iterative Learning Control - Monotonicity and Optimization
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151
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ATAL
2005
Springer
15 years 8 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson
133
Voted
KDD
2005
ACM
117views Data Mining» more  KDD 2005»
16 years 3 months ago
Rule extraction from linear support vector machines
We describe an algorithm for converting linear support vector machines and any other arbitrary hyperplane-based linear classifiers into a set of non-overlapping rules that, unlike...
Glenn Fung, Sathyakama Sandilya, R. Bharat Rao
ICSM
2006
IEEE
15 years 8 months ago
Using the Case-Based Ranking Methodology for Test Case Prioritization
The test case execution order affects the time at which the objectives of testing are met. If the objective is fault detection, an inappropriate execution order might reveal most ...
Paolo Tonella, Paolo Avesani, Angelo Susi
137
Voted
ECCV
2010
Springer
15 years 5 months ago
Clustering Complex Data with Group-Dependent Feature Selection
Abstract. We describe a clustering approach with the emphasis on detecting coherent structures in a complex dataset, and illustrate its effectiveness with computer vision applicat...
126
Voted
ICPR
2010
IEEE
15 years 17 days ago
User Adaptive Clustering for Large Image Databases
Abstract--Searching large image databases is a time consuming process when done manually. Current CBIR methods mostly rely on training data in specific domains. When source and dom...
Mohammad Mehdi Saboorian, Mansour Jamzad, Hamid R....