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UID:77@cds.iisc.ac.in
DTSTART;TZID=Asia/Kolkata:20241105T170000
DTEND;TZID=Asia/Kolkata:20241107T190000
DTSTAMP:20241024T133607Z
URL:https://cds.iisc.ac.in/events/short-course-on-graph-theory-and-machine
 -learning-from-fundamentals-to-advanced-applications/
SUMMARY:Short Course on Graph Theory and Machine Learning: From Fundamental
 s to Advanced Applications
DESCRIPTION:Instructor: Prof. Ananda S. Chowdhury\, Professor\, Jadavpur Un
 iversity (https://sites.google.com/site/anandachowdhury/)\nRoom No: 102 (S
 eminar Hall)\, CDS\n\nContents of the course:\n\n1. Lecture 1: Tuesday\, N
 ovember 5  (5:00 PM to 7-00 PM)\nWill start with basics of graphs\, talk 
 about sparse/dense graphs\, connectivity in graphs\, then discuss labeling
  problems in a weakly supervised setup and focus on Random Walks\, mention
  how we can improvise on such a setup with and without deep learning\, sho
 w some use cases\, and will (try to) include a demo\n\n2. Lecture 2: Wedne
 sday\, November 6  (5:00 PM to 7-00 PM)\nThe focus will be on Graph Cuts\
 , will talk about basic formulation including graph construction and energ
 y optimization\, then discuss typical problems\, like segmentation\, regis
 tration\, where you can apply graph cuts\, mention how we can improvise on
  such a setup with and without deep learning\, show some use cases\, and w
 ill (try to) include a demo\n\n3. Lecture 3: Thursday\, November 7 (5-00 P
 M to 7-00 PM)\nThe focus will be on Graph Convolution Networks\, will ment
 ion both the forward and the backward pass\, will discuss typical problems
  in GCN like node labeling\, edge labeling\, and graph labeling mention ho
 w we can improvise on such a setup\, show some use cases\, and will (try t
 o) include a demo\n\nAbout the Instructor: \nProf. Ananda S. Chowdhury is
  a seasoned researcher in the field of Computer Vision and Pattern Recogni
 tion. He currently leads the Imaging\, Vision\, and Pattern Recognition (I
 VPR) group at Jadavpur University. He is a senior member of IEEE\, an IAP
 R TC-member of Graph-based Representations in Pattern Recognition (GbR)\, 
 and a life member of the Indian Unit for Pattern Recognition and Artificia
 l Intelligence (IUPRAI). He serves as an Associate Editor for IEEE Transac
 tions on Image Processing and an Area Editor for Pattern Recognition Lette
 rs. His previous editorial roles include positions with Pattern Recognitio
 n Letters\, and IEEE Signal Processing Letters. He completed his post-doct
 oral fellowship at the National Institutes of Health\, USA\, and earned hi
 s Ph.D. in Computer Science from the University of Georgia\, USA. His rese
 arch interests span a wide range of theoretical and application problems i
 n Computer Vision and Pattern Recognition\, with a focus on Biomedical\, M
 ultimedia\, and Surveillance applications. His work explores graph-theoret
 ic models\, level sets\, probabilistic methods\, and deep learning algorit
 hms. He is the author of two books\, first one being Graph Based Multimedi
 a Analysis (https://www.amazon.in/Graph-Multimedia-Analysis-Ananda-Chowdhu
 ry/dp/0443214956/) and second one being Computer Vision-Guided Virtual Cra
 niofacial Surgery: A Graph-Theoretic and Statistical Perspective (https://
 www.amazon.in/Computer-Vision-Guided-Virtual-Craniofacial-Surgery-ebook/dp
 /B00F5QQPC6/)\, both are recognised as a reference text books for developi
 ng algorithms based on graph theory for challenging problems in multi-medi
 a analysis like summarisation and action recognition. More details about h
 im can be found here: https://sites.google.com/site/anandachowdhury/home\
 n\nCOURSE REGISTRATION LINK: https://forms.gle/tCc4neqVWWJ49smM6 (the cou
 rse is free\, but registration is mandatory)\n\nFor questions and clarific
 ations\, contact: Phaneendra Yalavarthy\, e-mail: yalavarthy@iisc.ac.in
CATEGORIES:Events
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