PPT-Deep learning

Author : calandra-battersby | Published Date : 2016-11-14

による読唇システム情報理工学部機械情報工学科 H412092 　パリアスカ　ケンジ研究背景近日画像認識や音声認識の分野において注目を集めている

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Deep learning: Transcript

による読唇システム情報理工学部機械情報工学科 H412092 　パリアスカ　ケンジ研究背景近日画像認識や音声認識の分野において注目を集めている. Quoc V. Le. Stanford University and Google. Purely supervised. Quoc V. . Le. Almost abandoned between 2000-2006. - . Overfitting. , slow, many local minima, gradient vanishing. In 2006, Hinton, et. al. proposed RBMs to . to Speech . EE 225D - . Audio Signal Processing in Humans and Machines. Oriol Vinyals. UC Berkeley. This is my biased view about deep learning and, more generally, machine learning past and current research!. Aaron Crandall, 2015. What is Deep Learning?. Architectures with more mathematical . transformations from source to target. Sparse representations. Stacking based learning . approaches. Mor. e focus on handling unlabeled data. The End of the Joan of Arc . Teacher Recruitment Strategy. BEST-NC Innovation Lab. September 28, 2016. Cary, NC. Southern Regional Education Board. Andy Baxter, Vice President for Educator Effectiveness. CS 501:CS Seminar. Min Xian. Assistant Professor. Department of Computer Science. University of Idaho. Image from NVIDIA. Researchers:. Geoff Hinton. Yann . LeCun. Andrew Ng. Yoshua. . Bengio. …. Aaron Schumacher. Data Science DC. 2017-11-14. Aaron Schumacher. planspace.org has these slides. Plan. applications. : . what. t. heory. applications. : . how. onward. a. pplications: what. Backgammon. Aaron Crandall, 2015. What is Deep Learning?. Architectures with more mathematical . transformations from source to target. Sparse representations. Stacking based learning . approaches. Mor. e focus on handling unlabeled data. New-Generation Models & Methodology for Advancing . AI & SIP. Li Deng . Microsoft Research, Redmond, . USA. Tianjin University, July 2-5, 2013. (including joint work with colleagues at MSR, U of Toronto, etc.) . Secada combs | bus-550. AI Superpowers: china, silicon valley, and the new world order. Kai Fu Lee. Author of AI Superpowers. Currently Chairman and CEO of . Sinovation. Ventures and President of . Sinovation. Topic 3. 4/15/2014. Huy V. Nguyen. 1. outline. Deep learning overview. Deep v. shallow architectures. Representation learning. Breakthroughs. Learning principle: greedy layer-wise training. Tera. . scale: data, model, . John-William . Sidhom. , MD/PhD Candidate ’21. Department of Biomedical Engineering. Johns Hopkins University School of Medicine. Sidney Kimmel Comprehensive Cancer Center. Johns Hopkins University. Assistant Professor. Computer Science and Engineering Department. Indian Institute of Technology Kharagpur. http://cse.iitkgp.ac.in/~adas/. Biological Neural Network. Image courtesy: F. . A. . Makinde. Eli Gutin. MIT 15.S60. (adapted from 2016 course by Iain Dunning). Goals today. Go over basics of neural nets. Introduce . TensorFlow. Introduce . Deep Learning. Look at key applications. Practice coding in Python. Patient Cohort Retrieval . Sanda. . Harabagiu. , . PhD. , Travis Goodwin, Ramon Maldonado, Stuart Taylor . The . Human Language Technology Research Institute. University of Texas at Dallas. Human Language Technology.

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