Next
Transfer and Multitask Learning
Livestream will start soon!
Livestream has already ended.
Presentation has not been recorded yet!
  • title: Applications
      0:00 / 0:00
      • Report Issue
      • Settings
      • Playlists
      • Bookmarks
      • Subtitles Off
      • Playback rate
      • Quality
      • Settings
      • Debug information
      • Server sl-yoda-v2-stream-007-alpha.b-cdn.net
      • Subtitles size Medium
      • Bookmarks
      • Server
      • sl-yoda-v2-stream-007-alpha.b-cdn.net
      • sl-yoda-v2-stream-007-beta.b-cdn.net
      • 1678031076.rsc.cdn77.org
      • 1932936657.rsc.cdn77.org
      • Subtitles
      • Off
      • English
      • Playback rate
      • Quality
      • Subtitles size
      • Large
      • Medium
      • Small
      • Mode
      • Video Slideshow
      • Audio Slideshow
      • Slideshow
      • Video
      My playlists
        Bookmarks
          00:00:00
            Applications
            • Settings
            • Sync diff
            • Quality
            • Settings
            • Server
            • Quality
            • Server

            Applications

            Jun 12, 2019

            Sprecher:innen

            AK

            Alexei Koulakov

            Sprecher:in · 0 Follower:innen

            AP

            Andrew Phillips

            Sprecher:in · 0 Follower:innen

            AG

            Anna Goldenberg

            Sprecher:in · 7 Follower:innen

            Über

            Exploiting Worker Correlation for Label Aggregation in Crowdsourcing Crowdsourcing has emerged as a core component of data science pipelines. From collected noisy worker labels, aggregation models that incorporate worker reliability parameters aim to infer a latent true annotation. In this paper, we argue that existing crowdsourcing approaches do not sufficiently model worker correlations observed in practical settings; we propose in response an enhanced Bayesian classifier combination (EBCC) m…

            Organisator

            I2
            I2

            ICML 2019

            Konto · 3,2k Follower:innen

            Kategorien

            KI und Datenwissenschaft

            Kategorie · 10,8k Präsentationen

            Über ICML 2019

            The International Conference on Machine Learning (ICML) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence known as machine learning. ICML is globally renowned for presenting and publishing cutting-edge research on all aspects of machine learning used in closely related areas like artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, and robotics. ICML is one of the fastest growing artificial intelligence conferences in the world. Participants at ICML span a wide range of backgrounds, from academic and industrial researchers, to entrepreneurs and engineers, to graduate students and postdocs.

            Gefällt euch das Format? Vertraut auf SlidesLive, um euer nächstes Event festzuhalten!

            Professionelle Aufzeichnung und Livestreaming – weltweit.

            Freigeben

            Empfohlene Videos

            Präsentationen, deren Thema, Kategorie oder Sprecher:in ähnlich sind

            Fairness
            1:12:54

            Fairness

            Aaron Roth, …

            I2
            I2
            ICML 2019 6 years ago

            Ewigspeicher-Fortschrittswert: 1 = 0.1%

            Applications
            1:18:40

            Applications

            Adam Roberts, …

            I2
            I2
            ICML 2019 6 years ago

            Ewigspeicher-Fortschrittswert: 0 = 0.0%

            Locality driven coded computation
            10:47

            Locality driven coded computation

            Michael Rudow

            I2
            I2
            ICML 2019 6 years ago

            Ewigspeicher-Fortschrittswert: 0 = 0.0%

            Online Learning 1
            1:01:51

            Online Learning 1

            Adrian Rivera Cardoso, …

            I2
            I2
            ICML 2019 6 years ago

            Ewigspeicher-Fortschrittswert: 0 = 0.0%

            Deep Learning for Wildlife Conservation and Restoration Efforts
            07:38

            Deep Learning for Wildlife Conservation and Restoration Efforts

            Clement Duhart

            I2
            I2
            ICML 2019 6 years ago

            Ewigspeicher-Fortschrittswert: 0 = 0.0%

            Personalization at Amazon Music
            18:29

            Personalization at Amazon Music

            Kat Ellis

            I2
            I2
            ICML 2019 6 years ago

            Ewigspeicher-Fortschrittswert: 1 = 0.1%

            Interessiert an Vorträgen wie diesem? ICML 2019 folgen