PPT-CS 7643: Deep Learning Dhruv Batra

Author : tatiana-dople | Published Date : 2018-09-21

Georgia Tech Topics Toeplitz matrices and convolutions matrix mult Dilateda trous convolutions Backprop in conv layers Transposed convolutions Administrativia

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CS 7643: Deep Learning Dhruv Batra: Transcript

Georgia Tech Topics Toeplitz matrices and convolutions matrix mult Dilateda trous convolutions Backprop in conv layers Transposed convolutions Administrativia HW1 extension . 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. 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 . Local Primal-Dual Gaps. Dhruv Batra (TTIC). Joint work with: . Daniel . Tarlow. (U Toronto), Sebastian . Nowozin. (MSRC), . Pushmeet. . Kohli. (MSRC), Vladimir . Kolmogorov. (UCL). Overview. Discrete . 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”. Larry . Zitnick. (Facebook AI Research). Devi Parikh. (Virginia Tech). Stanislaw . Antol. (Virginia Tech). Aishwarya Agrawal. (Virginia Tech). Overview of Challenge . Outline. Overview of Task and Dataset . Georgia Tech. Topics. : . Announcements. Transposed . convolutions. Administrativia. HW2 PS2 out. No class on Tuesday 10/03. Guest Lecture by Dr. Stefan Lee on 10/05. No papers to read. No student presentations. . Machine Learning. Stefan Lee. Virginia Tech. Topics: . Decision/Classification . Trees. Ensemble Methods: Bagging, . Boosting. Readings. : Murphy 16.1-. 16.2; Hastie . 9.2; Murphy . 16.4. Administrativia. ECE6504 – Deep Learning for Perception Ashwin Kalyan V Introduction to CAFFE (C) Dhruv Batra 2 Logistic Regression as a Cascade (C) Dhruv Batra 3 Slide Credit: Marc'Aurelio Ranzato , Yann LeCun Machine Learning. Dhruv Batra . Virginia Tech. Topics: . Supervised Learning. General Setup, learning from data. Nearest . Neighbour. Readings. : . Barber 14 (. kNN. ) . Administrativia. New class room. ,. 10-708 Recitation. 10. /30/. 2008. Contents. MRFs. Semantics / Comparisons with . BNs. Applications to vision. HW4 implementation. Semantics. Bayes. Nets. Semantics. Markov Nets. Semantics. Decomposition. 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”. 1980, he earned his Juris Doctor degree from the Fordham University School of Law. 2007, he chairs the National Advisory on South Asian Affairs, a foreign policy think tank, and interacts with the 1980 he earned his Juris Doctor degree from the Fordham University School of Law 2007 he chairs the National Advisory on South Asian Affairs a foreign policy think tank and interacts with the US Congr

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