ΑΙhub.org
 

What’s coming up at #ICML2023?


by
20 July 2023



share this:

ICML logo
This year’s International Conference on Machine Learning (ICML) will take place in Honolulu, Hawai’i from 23-29 July. As well as four invited talks, the programme boasts oral and poster presentations, affinity events, tutorials and workshops.

Invited talks

  • Marzyeh Ghassemi – Taking the Pulse Of Ethical ML in Health
  • Shakir Mohamed – Machine Learning with Social Purpose
  • Jennifer Doudna – The Future of ML in Biology: CRISPR for Health and Climate
  • John Schulman – Proxy objectives in reinforcement learning from human feedback

Affinity events

There are three affinity group workshops scheduled for this year:

Tutorials

The tutorials will take place on Monday 24 July. There are nine to choose from this year:

  • Optimal Transport in Learning, Control, and Dynamical Systems
  • Reinforcement Learning from Human Feedback: A Tutorial
  • Tutorial on Multimodal Machine Learning: Principles, Challenges, and Open Questions
  • Disinformation, Fake News and Computational Propaganda: Challenges and Opportunities for Machine Learning Research
  • How to DP-fy ML: A Practical Tutorial to Machine Learning with Differential Privacy
  • Self-Supervised Learning in Vision: from Research Advances to Best Practices
  • Discovering Agent-Centric Latent States in Theory and in Practice
  • Recent Advances in the Generalization Theory of Neural Networks
  • Responsible AI for Generative AI in Practice: Lessons Learned and Open Challenges

Workshops

The workshops will take place on Friday 28 and Saturday 29 July.

You can find out more about the conference here.



tags: , ,


Lucy Smith is Senior Managing Editor for AIhub.
Lucy Smith is Senior Managing Editor for AIhub.

            AIhub is supported by:



Subscribe to AIhub newsletter on substack



Related posts :

A multi-armed robot for assisting with agricultural tasks

and   27 Mar 2026
How can a robot safely manipulate branches to reveal hidden flowers while remaining aware of interaction forces and minimizing damage?

Resource-constrained image generation and visual understanding: an interview with Aniket Roy

  26 Mar 2026
Aniket tells us about his research exploring how modern generative models can be adapted to operate efficiently while maintaining strong performance.

RWDS Big Questions: how do we highlight the role of statistics in AI?

  25 Mar 2026
Next in our series, the panel explores the statistical underpinning of AI.

A history of RoboCup with Manuela Veloso

  24 Mar 2026
Find out how RoboCup got started and how the competition has evolved, from one of the co-founders.

Information-driven design of imaging systems

  23 Mar 2026
Framework that enables direct evaluation and optimization of imaging systems based on their information content.

Machine learning framework to predict global imperilment status of freshwater fish

  20 Mar 2026
“With our model, decision makers can deploy resources in advance before a species becomes imperiled.”

Interview with AAAI Fellow Yan Liu: machine learning for time series

  19 Mar 2026
Hear from 2026 AAAI Fellow Yan Liu about her research into time series, the associated applications, and the promise of physics-informed models.

A principled approach for data bias mitigation

  18 Mar 2026
Find out more about work presented at AIES 2025 which proposes a new way to measure data bias, along with a mitigation algorithm with mathematical guarantees.



AIhub is supported by:







Subscribe to AIhub newsletter on substack




 















©2026.02 - Association for the Understanding of Artificial Intelligence