PPT-Navigation and Propagation in Networks

Navigation and Propagation in Networks Michael Goodrich Some slides adapted from slides by Jean Vaucher Panayiotis Tsaparas Jure Leskovec and Christos Faloutsos NE MA Review Milgrams experiment. Always relative to inertial space Most common inertial sensors Accelerometers G yros brPage 4br Accelerometers By attaching a mass to a spring measuring its deflection we get a simple accelerometer Figure Gade 2004 brPage 5br Accelerometers conti Kong Da, Xueyu Lei & Paul McKay. Digit Recognition. Convolutional Neural Network. Inspired by the visual cortex. Our example: Handwritten digit recognition. Reference: . LeCun. et al. . Back propagation Applied to Handwritten Zip Code Recognition. Author: . Zhe. -Si Shen, Wen-Xu Wang , . etc. Speaker: . Zhi-Qiang. You. Background Knowledge. SIS. . . CP(Contact Process). . . CST. Reconstruction Framework(SIS). See. Page 13-14. Viral Marketing in Social . Networks: . Truth . or Fiction?. Thang. N. . Dinh. , Dung T. Nguyen, My T. Thai. Dept. of Computer & Information Science & Engineering. University of Florida, Gainesville, FL. Rodriguez. Structure and Dynamics . of Information Pathways . in On-line Media. 05.09.12 Workshop Menorca. ,. . MPI for Intelligent Systems. 2. Propagation over networks. Social Networks. Recommendation Networks. Emmanuel Baccelli, Philippe Jacquet, Bernard Mans, and Georgios Rodolakis. Presented by: Mayank Shekhar. Contents. Information Propagation Speed. Significance. Dependency. Mathematical Model for Delay Tolerant Networks. An introduction to learning internal representations By error Propagation. Presented by:. Kunal Parmar. UHID: 1329834. 1. Outline of the Presentation. Introduction. Historical Background. Perceptron. Model representation and analysis. Presented by:. Ayushi Jain Rahul . Bobhate. Natasha Mandal . Ankur. . Sachdeva. Dung T. Nguyen, . Huiyuan. Zhang, . Soham. Das, My T. Thai, Thang N. . Dinh. Maksym Gabielkov, . Ashwin. Rao, . Arnaud Legout. EPI DIANA, Sophia Antipolis. {. maksym.gabielkov. , a. rnaud.legout. }@inria.fr. Friends. Producer. Consumers. Follow. . R. elationship in Twitter. Cheng-. Hsien. Lee. 12/14/10. Introduction. Motivation. Back Propagation. Feed-forward pass. Error-back-propagation pass:. MLP Structure. Training Data. Generate from a given A.I.. When . Vx. <0. Psychology 209. February 6, 2013. Homework . 4. Part 1 due Feb 13. Complete . Exercises 5.1 and 5.2.. It may be helpful to . c. arry . out some explorations of parameters, as suggested in Exercise . 5.3. This may help you achieve a solution in the last part of the homework, below. However, no write-up is required for this.. Submission Title:. . Automatic Navigation Solution for Driverless Airport Shuttle Bus Using . IoT/IoL Embedded Lighting Devices. Date . Submitted: . November 2018. . Source. :. Jaesang Cha (SNUST), Minwoo Lee (SNUST), Hyeongho Lee (Korea Univ.), . Submission Title:. . Automatic Navigation Solution for Driverless Airport Shuttle Bus Using . IoT/IoL Embedded Lighting Devices. Date . Submitted: . November 2018. . Source. :. Jaesang Cha (SNUST), Minwoo Lee (SNUST), Hyeongho Lee (Netvision Telecom Inc., Korea Univ.), . What are they?. Inspired by the Human Brain.. The human brain has about 86 Billion neurons and requires 20% of your body’s energy to function. . These neurons are connected to between 100 Trillion to 1 Quadrillion synapses!.