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Contenido proporcionado por The Thesis Review and Sean Welleck. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente The Thesis Review and Sean Welleck o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.
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[25] Tomas Mikolov - Statistical Language Models Based on Neural Networks

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Manage episode 302418420 series 2982803
Contenido proporcionado por The Thesis Review and Sean Welleck. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente The Thesis Review and Sean Welleck o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.
Tomas Mikolov is a Senior Researcher at the Czech Institute of Informatics, Robotics, and Cybernetics. His research has covered topics in natural language understanding and representation learning, including Word2Vec, and complexity. Tomas's PhD thesis is titles "Statistical Language Models Based on Neural Networks", which he completed in 2012 at the Brno University of Technology. We discuss compression and recurrent language models, the backstory behind Word2Vec, and his recent work on complexity & automata. Episode notes: https://cs.nyu.edu/~welleck/episode25.html Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview
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47 episodios

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Manage episode 302418420 series 2982803
Contenido proporcionado por The Thesis Review and Sean Welleck. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente The Thesis Review and Sean Welleck o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.
Tomas Mikolov is a Senior Researcher at the Czech Institute of Informatics, Robotics, and Cybernetics. His research has covered topics in natural language understanding and representation learning, including Word2Vec, and complexity. Tomas's PhD thesis is titles "Statistical Language Models Based on Neural Networks", which he completed in 2012 at the Brno University of Technology. We discuss compression and recurrent language models, the backstory behind Word2Vec, and his recent work on complexity & automata. Episode notes: https://cs.nyu.edu/~welleck/episode25.html Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview
  continue reading

47 episodios

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