PPT-Distributed Representations for

Natural Language Processing Tomas Mikolov Facebook ML Prague 2016 Structure of this talk Motivation Word2vec Architecture Evaluation Examples Discussion Motivation Representation of text is very important for performance of many realworld applications search ads recommendation ranking spam filtering . Access to resources of various machines is done explicitly by Remote logging into the appropriate remote machine Transferring data from remote machines to local machines via the File Transfer Protocol FTP mechanism Tightly Coupled Distributed System Mountain View mikolovgooglecom Ilya Sutskever Google Inc Mountain View ilyasugooglecom Kai Chen Google Inc Mountain View kaigooglecom Greg Corrado Google Inc Mountain View gcorradogooglecom Jeffrey Dean Google Inc Mountain View jeffgooglecom Abstrac Easy to understand Easy to code by hand Often used to represent inputs to a net Easy to learn This is what mixture models do Each cluster corresponds to one neuron Easy to associate with other representations or responses But localist models are ver brPage 1br Spin representations and Pauli antisymmetry pp pn np nn pn np rr n nn mmArrrr prp mmAmmA ppp ppn pnp npp nnp npn pnn nnn brPage 2br rrr rrr rrr 1 Reducible representations In degenerate groupsProducts of irreducible representations may give reducible representationsProducts of wave functions may be represented by reducible representations Nee Representation. How the media shows us things about society – but this is through careful mediation. Hence . re-presentation.. For representation to be meaningful to audiences there needs to be a shared recognition of people, situations, ideas etc.. Transition to motherhood, beginning during pregnancy and lasting several months after the birth of the baby, is developmental crisis with marked reorganization of the mental world. It includes forming mental representations of the baby and of self-as-a-mother, a process which is . Daniel Lowd. University of Oregon. April 20, 2015. Caveats. The purpose of this talk is to inspire meaningful discussion.. I may be completely wrong.. My background:. Markov logic networks, probabilistic graphical models. Tahereh Zahmatkesh. McMaster University - CAS . 769. March 2015. Outline. March 2015. Distributed Reset - CAS 769. 2. March 2015. Distributed Reset - CAS 769. 3. Introduction. Distributed reset. : any of the . A: Analyse all the sources using ABC and decide which is the best representation referring to all factors, own knowledge is used to support Judgment. B: Analyse all of the sources and comparing them. Some reference to ABC. Compared to own knowledge.. and their Compositionality. Presenter: Haotian Xu. Roadmap. Overview. The Skip-gram Model with Different . Objective Functions. Subsampling of Frequent Words. Learning Phrases. CNN for Text Classification. and Unsupervised Learning. Chapter 5, . Anastasio. Learning objectives. :. explain the difference between “sparse” and “distributed” neuronal encoding. explain the difference in purpose between Hopfield networks and two-layer neural networks. McMaster University - CAS . 769. March 2015. Outline. March 2015. Distributed Reset - CAS 769. 2. March 2015. Distributed Reset - CAS 769. 3. Introduction. Distributed reset. : any of the . processes. 2How can new representations be acquired When that question is asked about new concepts Fodor famously argued that hypothesis testing is the only option Fodor 1975 1981 That led him to embrace radica