PPT-Regularization ECE 6504 Deep Learning for Perception

Author : lois-ondreau | Published Date : 2018-11-09

Xiao Lin Peng Zhang Virginia Tech Papers Srivastava et al Dropout A simple way to prevent neural networks from overfitting JMLR 2014 Hinton Brain Sex and Machine

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Regularization ECE 6504 Deep Learning for Perception: Transcript

Xiao Lin Peng Zhang Virginia Tech Papers Srivastava et al Dropout A simple way to prevent neural networks from overfitting JMLR 2014 Hinton Brain Sex and Machine Learning . 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 . Information Processing & Artificial Intelligence. New-Generation Models & Methodology for Advancing . AI & SIP. Li Deng . Microsoft Research, Redmond, . USA. Tianjin University, July 4, 2013 (Day 3). 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. David Kauchak. CS 451 – Fall 2013. Admin. Assignment 5. Math so far…. Model-based machine learning. pick a model. pick a criteria to optimize (aka objective function). develop a learning algorithm. Regularization for Unsupervised Learning of Probabilistic Grammars. Kewei. . Tu. Vasant. . Honavar. Departments of Statistics and Computer Science. University of California, Los Angeles. Department of Computer Science. Professor Qiang Yang. Outline. Introduction. Supervised Learning. Convolutional Neural Network. Sequence Modelling: RNN and its extensions. Unsupervised Learning. Autoencoder. Stacked . Denoising. . Continuous. Scoring in Practical Applications. Tuesday 6/28/2016. By Greg Makowski. Greg@Ligadata.com. www.Linkedin.com/in/GregMakowski. Community @. . http. ://. Kamanja.org. . . Try out. Future . The Future of Real-Time Rendering?. 1. Deep Learning is Changing the Way We Do Graphics. [Chaitanya17]. [Dahm17]. [Laine17]. [Holden17]. [Karras17]. [Nalbach17]. Video. “. Audio-Driven Facial Animation by Joint End-to-End Learning of Pose and Emotion”. 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. …. Fall 2018/19. 3. Improving Neural Networks. (Some figures adapted from . NNDL book. ). Various Approaches to . Improve Neural Networks. Noriko Tomuro. 2. Cost functions. Quadratic. Cross Entropy. Log likelihood. 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. Garima Lalwani Karan Ganju Unnat Jain. Today’s takeaways. Bonus RL recap. Functional Approximation. Deep Q Network. Double Deep Q Network. Dueling Networks. Recurrent DQN. Solving “Doom”. Outline. What is Deep Learning. Tensors: Data Structures for Deep Learning. Multilayer Perceptron. Activation Functions for Deep Learning. Model Training in Deep Learning. Regularization for Deep Learning. 2. R. eligious Holidays: please contact if this affects your HW due dates.. For 209 students: . please submit 209 HW separately from 109 HW in different assignments on Canvas.. A-sec this week: optional to cover 2.

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