'Title: Deep Learning Lecture 1: Brief history and basic concepts (1 hour) & Deep Learning Lecture 2: Key models (1.5-2 hours)
Speaker: Dr. Dong Yu (Microsoft Research)
Inviter： Prof. LI Wei
Time: Oct 23, 13：00-16：00
Location: 张江校区二教 301 室
Abstract:
Deep learning is a newly emerged area of research in machine learning and has recently shown huge success in a variety of areas such as speech recognition, image classification, and natural language processing.
In this first two lectures of the deep learning lecture series, I will briefly introduce the history of neural network and deep learning, describe the basic concepts, and illustrate the key models such as energy based models, restricted Boltzmann machines, deep autoencoders, deep neural networks, convolutional neural networks, recurrent neural networks, and long short-term memory recurrent networks.
Short Bio:
Dr. Dong Yu is a principal researcher at the Microsoft Research, a guest professor of university of science and technology of China, and an affiliated processor at Zhejiang University. His research has been focusing on speech recognition and applications of machine learning techniques. He has published two monographs and over 140 papers in these areas and is the co-inventor of more than 50 granted/pending patents. His recent work on the context-dependent deep neural network hidden Markov model (CD-DNN-HMM), which was recognized by the IEEE SPS 2013 best paper award, caused a paradigm shift on large vocabulary speech recognition.
Dr. Dong Yu is currently serving as a member of the IEEE Speech and Language Processing Technical Committee (2013-) and an associate editor of IEEE transactions on audio, speech, and language processing (2011-2015). He has served as an associate editor of IEEE signal processing magazine (2008-2011) and the lead guest editor of IEEE transactions on audio, speech, and language processing - special issue on deep learning for speech and language processing (2010-2011).
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