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ECCV
2008
Springer
16 years 2 months ago
Training Hierarchical Feed-Forward Visual Recognition Models Using Transfer Learning from Pseudo-Tasks
Abstract. Building visual recognition models that adapt across different domains is a challenging task for computer vision. While feature-learning machines in the form of hierarchi...
Amr Ahmed, Kai Yu, Wei Xu, Yihong Gong, Eric P. Xi...
109
Voted
SIGSOFT
2006
ACM
16 years 1 months ago
Scenarios, goals, and state machines: a win-win partnership for model synthesis
Models are increasingly recognized as an effective means for elaborating requirements and exploring designs. For complex systems, model building is far from an easy task. Efforts ...
Christophe Damas, Bernard Lambeau, Axel van Lamswe...
102
Voted
TSMC
2010
14 years 7 months ago
A Benchmark Diagnostic Model Generation System
Abstract--It is critical to use automated generators for synthetic models and data, given the sparsity of benchmark models for empirical analysis and the cost of generating models ...
Jun Wang, Gregory M. Provan
119
Voted
HAIS
2009
Springer
15 years 5 months ago
Pareto-Based Multi-output Model Type Selection
In engineering design the use of approximation models (= surrogate models) has become standard practice for design space exploration, sensitivity analysis, visualization and optimi...
Dirk Gorissen, Ivo Couckuyt, Karel Crombecq, Tom D...
91
Voted
CIA
2006
Springer
15 years 4 months ago
Market-Inspired Approach to Collaborative Learning
The paper describes a decentralized peer-to-peer multi-agent learning method based on inductive logic programming and knowledge trading. The method uses first-order logic for model...
Jan Tozicka, Michal Jakob, Michal Pechoucek