Connectionists: Masashi Sugiyama speaking on March 2 in Developing Minds global online lecture series

[Jochen Triesch]

Dear colleagues,

On March 2, the Developing Minds global online lecture series will feature Masashi Sugiyama, RIKEN/The University of Tokyo:
"Theory and Algorithm towards Reliable Machine Learning“

The live event will take place via zoom at:
08:00 am EST (Eastern Standard Time)
13:00 UTC (Universal Coordinated Time)
14:00 CET (Central European Time)
22:00 JST (Japan Standard Time)

To participate please register here:
https://sites.google.com/view/developing-minds-series/home

Abstract:
When training and deploying machine learning systems in the real world, we face several types of uncertainty.  For example, the available training data may contain insufficient information, label noise, and bias.  In this talk, I will give an overview of our theory and algorithm research towards reliable machine learning, including weakly supervised learning, noisy label learning, and transfer learning. Finally, I will discuss how researchers in AI and robotics can benefit from each other in this highly interdisciplinary research field, which spans computer science, cognitive science, psychology, and neuroscience.

Bio:
Masashi Sugiyama received his Ph.D. in Computer Science from the Tokyo Institute of Technology in 2001. He has been a professor at the University of Tokyo since 2014, and simultaneously the director of the RIKEN Center for Advanced Intelligence Project (AIP) since 2016. His research interests include theories and algorithms of machine learning, exemplified by Machine Learning in Non-Stationary Environments (MIT Press, 2012), Density Ratio Estimation in Machine Learning (Cambridge University Press, 2012), Statistical Reinforcement Learning: Modern Machine Learning Approaches (Chapman and Hall/CRC, 2015), and Machine Learning from Weak Supervision (MIT Press, 2022). He has served as program co-chair for the Neural Information Processing Systems (NeurIPS) conference in 2015, the International Conference on Artificial Intelligence and Statistics (AISTATS) in 2019, and the Asian Conference on Machine Learning (ACML) in 2010 and 2020.

The talk will also be recored and the recording made available via the web page:
https://sites.google.com/view/developing-minds-series/home

Best regards,
  Jochen Triesch

--
Prof. Dr. Jochen Triesch
Johanna Quandt Chair for Theoretical Life Sciences
Frankfurt Institute for Advanced Studies and
Goethe University Frankfurt
http://fias.uni-frankfurt.de/~triesch/
Tel: +49 (0)69 798-47531
Fax: +49 (0)69 798-47611