Zulip Chat Archive

Stream: Machine Learning for Theorem Proving

Topic: MATH-AI workshop@ICLR


view this post on Zulip Yuhuai Tony Wu (Feb 09 2021 at 21:21):

In case relevant people in this stream haven't seen the notification in #Math-AI@ICLR , there will be a workshop on MATH & AI at ICLR this May, and the submission date is in about 2 weeks. The CFP is copied below.


Dear all,

We’re excited to announce the first Math-AI workshop at ICLR 2021! Please consider to submit a paper.

Thanks!

Website: http://mathai-iclr.github.io/

Call for Papers:

The Math-AI workshop is intended to provide a forum for discussing missing elements and major bottlenecks towards demonstrating mathematical reasoning ability in AI systems. We hope that the outcome of the workshop will lead us in meaningful directions towards a generic approach to mathematical reasoning, and shed light on general reasoning mechanisms for artificial intelligence. In particular, we are interested but not limited to the following areas of questions:

Mathematical reasoning vs. general intelligence?

  • What is a potential path from mathematical reasoning to general artificial intelligence?
  • What is special about mathematical reasoning compared to other reasoning tasks?
  • What are the pros and cons of studying mathematical reasoning?
  • Can the lessons learned from mathematical reasoning generalize to other reasoning tasks?

What machine learning techniques are we missing in the quest for machines that perform mathematical reasoning?

  • How to deal with large action space – hopeless exploration in mathematical reasoning?
  • How to design methods that allow flexible planning and jumpy reasoning?
  • How to collect large scale datasets for mathematical reasoning?
  • Can one augment the dataset by designing good synthetic datasets?
  • How do we utilize informal mathematical datasets?
  • Human-like theorem proving vs formal theorem proving using ITPs (interactive theorem provers), trade-offs?
  • Do we need a special theorem proving assistant for machine learning?

We are also interested in works on other reasoning problems that share similar structures, and can bring great insights to mathematical reasoning, such as

  • Program synthesis
  • Code verification
  • Retrosynthesis problem
  • Text games

Important Dates:

  • Paper submission opens: Jan 26, 11:59PM PST
  • Deadline for paper submission: Feb 26, 11:59PM PST
  • Review decisions released: March 26, 11:59PM PST
  • Deadline for camera ready: April 26, 11:59PM PST
  • Workshop: May 8, 2021

Speakers & Panelists:

Yoshua Bengio, MILA.
Timothy Gowers, Collège de France.
Mateja Jamnik, University of Cambridge
Jay McClelland, Stanford University
Alison Pease, University of Dundee
Stanislas Polu, OpenAI
Markus Rabe, Google
Christian Szegedy, Google
Josef Urban, CIIRC

Organizers:

Kshitij Bansal, Google
John Harrison, Amazon
Wenda Li, University of Cambridge
David McAllester, TTI Chicago
Melanie Mitchell, Santa Fe Institute
Yuhuai (Tony) Wu, University of Toronto


Last updated: May 09 2021 at 22:13 UTC