In Section 5, as a major example in the hybrid deep network cate-gory, we present in detail the deep neural networks with unsupervised and largely generative pre-training to boost the effectiveness of …

This monograph discusses the emerging theory of deep learning. It originated from notes by the lecturers at a graduate seminar taught at Princeton University in Fall 2019 in conjunction with a …

• Deep learning has revolutionized pattern recognition, introducing technology that now powersawiderangeoftechnologies,includingcomputervision,naturallanguageprocess- …

With this approach we intend to offer a comprehensive framework for defining deep tech and deep-tech ventures, which is based not only on quantifiable economic criteria, but also on other qualitative and …

Dueling network architectures for deep reinforcement learning: separates value and advantage estimation in Q-function.

In this paper, it is our goal to empirically study the pros and cons of off-the-shelf optimization algorithms in the context of unsupervised feature learning and deep learning.

This article presents a comprehensive review of historical and recent state-of-the-art approaches in visual, audio, and text processing; social network analysis; and natural language processing, …