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GECCO
2009
Springer
110views Optimization» more  GECCO 2009»
14 years 1 months ago
EMO shines a light on the holes of complexity space
Typical domains used in machine learning analyses only partially cover the complexity space, remaining a large proportion of problem difficulties that are not tested. Since the ac...
Núria Macià, Albert Orriols-Puig, Es...
DEXAW
1998
IEEE
155views Database» more  DEXAW 1998»
14 years 1 months ago
Business-Oriented Component-Based Software Development and Evolution
Huge size and high complexity of legacy software are the main sources of today's software evolution problems. While we can ease software evolution with re-engineering tools, ...
Stan Jarzabek, Martin Hitz
JAIR
2011
144views more  JAIR 2011»
13 years 3 months ago
Non-Deterministic Policies in Markovian Decision Processes
Markovian processes have long been used to model stochastic environments. Reinforcement learning has emerged as a framework to solve sequential planning and decision-making proble...
Mahdi Milani Fard, Joelle Pineau
CVIU
2006
158views more  CVIU 2006»
13 years 8 months ago
Sequential mean field variational analysis of structured deformable shapes
A novel approach is proposed to analyzing and tracking the motion of structured deformable shapes, which consist of multiple correlated deformable subparts. Since this problem is ...
Gang Hua, Ying Wu
ICMCS
2005
IEEE
284views Multimedia» more  ICMCS 2005»
14 years 2 months ago
Conditionally Positive Definite Kernels for SVM Based Image Recognition
Kernel based methods such as Support Vector Machine (SVM) have provided successful tools for solving many recognition problems. One of the reason of this success is the use of ker...
Sabri Boughorbel, Jean-Philippe Tarel, Nozha Bouje...