Overview
The 31st International Conference on Algorithmic Learning Theory (ALT 2020) is set to occur in San Diego, California, from February 9 to 11, 2020. This event will be held alongside the Information Theory and Applications (ITA 2020) workshop, featuring a collaborative symposium on February 8 that focuses on Information Theory Applied to Learning Theory. This symposium will include invited talks and a poster session, providing authors of ALT submissions a platform to showcase their work to a wider audience.
Background & Relevance
Algorithmic learning theory is a vital area within machine learning that encompasses both theoretical foundations and practical applications. The exploration of learning algorithms, statistical methods, and optimization techniques is crucial for advancing the field. The ALT conference serves as a key venue for researchers to present innovative ideas and contribute to the ongoing discourse in this domain. The intersection of learning theory with other mathematical fields and real-world applications underscores its significance in the broader AI landscape.
Key Details
- Conference Dates: February 9-11, 2020
- Location: Catamaran Resort Hotel and Spa, San Diego, CA, USA
- Symposium Date: February 8, 2020
- Submission Deadline: September 20, 2019, 4:59 PM EST
- Author Notification: November 24, 2019
- Conference Website: ALT 2020 Website
Eligibility & Participation
The conference invites submissions from researchers working on various aspects of machine learning. This includes theoretical contributions, algorithmic advancements, and experimental studies that elucidate theoretical results or highlight intriguing behaviors warranting further investigation. Authors of accepted papers will be encouraged to present their findings as full-length talks and may also participate in the poster session.
Submission or Application Guidelines
- Dual Submission Policy: Submissions to ALT 2020 must not be under review for other conferences or journals with published proceedings. However, works available as technical reports or on platforms like arXiv are acceptable.
- Formatting: There is no page limit, but it is recommended that the first 12 pages clearly present the main contributions and arguments, as referees will primarily review these pages.
- Review Process: Each submission will be evaluated by the program committee based on clarity, significance, and originality. The review process is not double-blind, and authors should include their names and affiliations in their submissions.
Additional Context / Real-World Relevance
The ALT conference plays a crucial role in fostering collaboration and knowledge sharing among researchers in algorithmic learning theory. By addressing theoretical and practical challenges, the conference contributes to the development of robust machine learning systems applicable across various domains, including economics, social sciences, and game theory. The emphasis on interdisciplinary connections highlights the importance of learning theory in understanding complex systems.
Conclusion
Researchers are encouraged to submit their work to ALT 2020, a premier conference dedicated to algorithmic learning theory. This event offers a unique opportunity to engage with peers, present innovative research, and contribute to the advancement of the field. Interested participants should prepare their submissions in accordance with the guidelines and mark their calendars for this significant gathering in the AI/ML community.
Category: CFP & Deadlines
Tags: algorithmic learning theory, machine learning, deep learning, reinforcement learning, statistical learning, optimization methods, poster session, PMLR, E.M. Gold Award
