PDF-Modeling Documents with a Deep Boltzmann Machine Nitish Srivastava Ruslan Salakh

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. Restricted Boltzmann machines RBMs are probabilistic graphical models that can be interpreted as stochastic neural networks Theincreaseincomputationalpowerandthedevelopmentoffasterlearn ing algorithms have made them applicable to relevant machine le torontoedu Geoffrey Hinton Department of Computer Science University of Toronto hintoncstorontoedu Abstract We present a new learning algorithm for Boltz mann machines that contain many layers of hid den variables Datadependent expectations are estim , Ashish Kapoor and Krysta Svore. Microsoft Research. ASCR Workshop. Washington DC. 1412.3489. Quantum Deep Learning. How do we make computers that . see. , . listen. , and . understand. ?. Goal. : Learn . S. M. Ali . Eslami. Nicolas Heess. John Winn. March 2013. Heriott. -Watt University. Goal. Define a probabilistic distribution on images like this:. 2. What can one do with an ideal shape model?. 3. Segmentation. 1. Boltzmann Machine. Relaxation net with visible and hidden units. Learning algorithm. Avoids local minima (and speeds up learning) by using simulated annealing with stochastic nodes. Node activation: Logistic Function. Integrable. . Zoo. Paul Fendley. o. r:. . Discrete . Holomophicity. from . Topology. Outline. Integrability. and the Yang-Baxter . equation. Knot and link invariants such as the Jones . polynomial. to Speech . EE 225D - . Audio Signal Processing in Humans and Machines. Oriol Vinyals. UC Berkeley. This is my biased view about deep learning and, more generally, machine learning past and current research!. 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. Contact us at: contact.omics@omicsonline.org. OMICS . International . through its Open Access Initiative is committed to make genuine and reliable contributions to the scientific community. OMICS International hosts over . The End of the Joan of Arc . Teacher Recruitment Strategy. BEST-NC Innovation Lab. September 28, 2016. Cary, NC. Southern Regional Education Board. Andy Baxter, Vice President for Educator Effectiveness. Rajdeep. . Dasgupta. CIDER Community Workshop, CA. May 08, 2016. Volcanic degassing. hazards. long-term climate. Bio-essential elements. Origin of life. Mantle melting. Chemical differentiation. Properties of asthenosphere. Principal Source:. Boltzmann’s Atom. David Lindley, The Free Press, . New York 2001. Atom. Greek ‘Uncutable’ . Universe composed of indivisible objects. Philosophy and Atomic Theory. Titus Lucretius . Radiation that is emitted by features on earth. Water. Clouds. Land surface. Infrared spectrum of energy. Connection to Stefan-Boltzmann. E = energy radiating in W m. -2 . (Typical units of OLR). = emissivity (if a blackbody = 1). Yonggang Cui. 1. , Zoe N. Gastelum. 2. , Ray Ren. 1. , Michael R. Smith. 2. , . Yuewei. Lin. 1. , Maikael A. Thomas. 2. , . Shinjae. Yoo. 1. , Warren Stern. 1. 1 . Brookhaven National Laboratory, Upton, USA.