Next
Livestream will start soon!
Livestream has already ended.
Presentation has not been recorded yet!
  • title: Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling
      0:00 / 0:00
      • Report Issue
      • Settings
      • Playlists
      • Bookmarks
      • Subtitles Off
      • Playback rate
      • Quality
      • Settings
      • Debug information
      • Server sl-yoda-v2-stream-003-alpha.b-cdn.net
      • Subtitles size Medium
      • Bookmarks
      • Server
      • sl-yoda-v2-stream-003-alpha.b-cdn.net
      • sl-yoda-v2-stream-003-beta.b-cdn.net
      • 1544410162.rsc.cdn77.org
      • 1005514182.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
            Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling
            • Settings
            • Sync diff
            • Quality
            • Settings
            • Server
            • Quality
            • Server

            Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling

            Jul 19, 2022

            Speakers

            SK

            Sajad Khodadadian

            Speaker · 0 followers

            PS

            Pranay Sharma

            Speaker · 0 followers

            GJ

            Gauri Joshi

            Speaker · 0 followers

            Organizer

            I2
            I2

            ICML 2022

            Account · 493 followers

            Like the format? Trust SlidesLive to capture your next event!

            Professional recording and live streaming, delivered globally.

            Sharing

            Recommended Videos

            Presentations on similar topic, category or speaker

            Deep Causal Metric Learning
            05:21

            Deep Causal Metric Learning

            Xiang Deng, …

            I2
            I2
            ICML 2022 3 years ago

            Total of 0 viewers voted for saving the presentation to eternal vault which is 0.0%

            Lightweight Projective Derivative Codes for Compressed Asynchronous Gradient Descent
            05:43

            Lightweight Projective Derivative Codes for Compressed Asynchronous Gradient Descent

            Pedro Soto, …

            I2
            I2
            ICML 2022 3 years ago

            Total of 0 viewers voted for saving the presentation to eternal vault which is 0.0%

            SSL Enables Learning from Sparse Rewards in Image-Goal Navigation
            04:38

            SSL Enables Learning from Sparse Rewards in Image-Goal Navigation

            Arjun Majumdar, …

            I2
            I2
            ICML 2022 3 years ago

            Total of 0 viewers voted for saving the presentation to eternal vault which is 0.0%

            Model Selection in Batch Policy Optimization
            05:04

            Model Selection in Batch Policy Optimization

            Jonathan Lee, …

            I2
            I2
            ICML 2022 3 years ago

            Total of 0 viewers voted for saving the presentation to eternal vault which is 0.0%

            Learning from Training Dynamics: Identifying Mislabeled Data Beyond Manually Designed Features
            03:33

            Learning from Training Dynamics: Identifying Mislabeled Data Beyond Manually Designed Features

            Qingrui Jia, …

            I2
            I2
            ICML 2022 3 years ago

            Total of 0 viewers voted for saving the presentation to eternal vault which is 0.0%

            Demystifying the Adversarial Robustness of Random Transformation Defenses
            05:59

            Demystifying the Adversarial Robustness of Random Transformation Defenses

            Chawin Sitawarin, …

            I2
            I2
            ICML 2022 3 years ago

            Total of 0 viewers voted for saving the presentation to eternal vault which is 0.0%

            Interested in talks like this? Follow ICML 2022