Titlebook: Artificial Neural Networks - ICANN 2010; 20th International C Konstantinos Diamantaras,Wlodek Duch,Lazaros S. Il Conference proceedings 201

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書目名稱Artificial Neural Networks - ICANN 2010影響因子(影響力)




書目名稱Artificial Neural Networks - ICANN 2010影響因子(影響力)學(xué)科排名




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書目名稱Artificial Neural Networks - ICANN 2010讀者反饋




書目名稱Artificial Neural Networks - ICANN 2010讀者反饋學(xué)科排名

小教堂

H. R. Koelz,P. G. Lankisch,S. Müller-LissnerTri-Class SVMs. The proposed framework is applied to facial expressions recognition task. The results show that . can exploit effectively the independent views and the unlabeled data to improve the recognition accuracy of facial expressions.

placebo

大酒杯

expound

Electrical Circuits of Ordinary Capacitorsng algorithm which has been found to have numerous advantages over Evolution Strategies. Our empirical results confirm the promise of this approach, and we discuss how it can be scaled up to expert-level Go players.

evanescent

發(fā)誓放棄

調(diào)色板

Hidden Markov Model for Human Decision Process in a Partially Observable Environment), which incorporates inference of a hidden variable in the environment and switching between exploration and exploitation. Our HMM-based model well reproduced the human behaviors, suggesting the human subjects actually performed exploration and exploitation to effectively adapt to this uncertain environment.

BRAWL

Representing, Learning and Extracting Temporal Knowledge from Neural Networks: A Case Studyis again symbolically represented, incorporating both initial model and learned specification, as shown by our case study. The case study illustrates how the integration of methodologies and principles from distinct AI areas can be relevant to build robust intelligent systems.

SUE

Multi-Dimensional Deep Memory Atari-Go Players for Parameter Exploring Policy Gradientsng algorithm which has been found to have numerous advantages over Evolution Strategies. Our empirical results confirm the promise of this approach, and we discuss how it can be scaled up to expert-level Go players.