PPT-Nitish

Srivastava Elman Mansimov Ruslan Salakhutdinov University of Toronto Unsupervised Learning of Video Representations using LSTMs Agenda Quick Intro Supervised vs Unsupervised Problem Definition. torontoedu Department of Computer Science University of Toronto Toronto Ontario M5S 3G4 Canada Geo64256rey Hinton Abstract We introduce a type of Deep Boltzmann Ma chine DBM that is suitable for extracting distributed semantic representations from a torontoedu Ruslan Salakhutdinov Department of Statistics and Computer Science University of Toronto rsalakhucstorontoedu Abstract A Deep Boltzmann Machine is described for learning a generative model of data that consists of multiple and diverse inpu torontoedu Department of Computer Science University of Toronto Toronto Ontario M5S 3G4 Canada Geo64256rey Hinton Abstract We introduce a type of Deep Boltzmann Ma chine DBM that is suitable for extracting distributed semantic representations from a lastnameinsightcentreorg Abstract More than 40 web search queries pivot around a single en tity which can be interpreted with the available knowledge bases such as DBpedia and Freebase With the advent of these knowledge repos itories major search eng torontoedu Abstract Attention has long been proposed by psychologists to be important for ef64257ciently dealing with the massive amounts of sensory stimulus in the neocortex Inspired by the attention models in visual neuroscience and the need for ob Subtle Facial Expression using Motion Magnification Nitish Gupta Rahul Maji Advisor: Dr. Amitabha Mukerjee 1 Motivation • Facial Expression Recognition o active area of research o has wide Regional/District News Manjhi rubbishes Nitish's call for JD(U)meet, calls parallel meet on Feb 20 Cabinet colleague Jitan RamManjhi to succeed him. Mr.them to meet the challengesIf Mr. Manjhi can get