Call for Papers |
The Algorithmic Learning Theory (ALT) 2024 conference will be held in San Diego, CA on February 25-28th 2024. The conference is dedicated to all theoretical and algorithmic aspects of machine learning. We invite submissions with contributions to new or existing learning problems including, but not limited to:
Design and analysis of learning algorithms. Statistical and computational learning theory. Online learning algorithms and theory. Optimization methods for learning. Unsupervised, semi-supervised, and active learning. Interactive learning, planning and control, and reinforcement learning. Privacy-preserving data analysis. Learning with additional societal and strategic considerations: e.g., fairness, economics. Robustness of learning algorithms to adversarial agents. Artificial neural networks, including deep learning. High-dimensional and non-parametric statistics. Adaptive data analysis and selective inference. Learning with algebraic or combinatorial structure. Bayesian methods in learning. Learning in distributed and streaming settings. Game theory and learning. Learning from complex data: e.g., networks, time series. Theoretical analysis of probabilistic graphical models. While the primary focus of the conference is theoretical, authors are welcome to support their analysis by including relevant experimental results. Accepted papers will be published electronically in the Proceedings of Machine Learning Research (PMLR), and will be presented at the conference as a full-length talk. Authors of accepted papers will have the option of opting out of the proceedings in favor of a 1-page extended abstract, which will point to an open access archival version of the full paper reviewed for ALT. Important dates Paper submission deadline: September 26, 2023, Anywhere On Earth Author feedback: Nov 11-17, 2023 Author notification: Mid-December, 2023 Conference format The conference will be in-person and will not be hybrid. At least one author of each accepted paper will be required to present their paper in-person at the conference. When travel is not possible, we encourage authors to find alternative presenters in the community attending the conference. Dual submission policy Conferences: In general, submissions that are substantially similar to papers that have been previously published, accepted for publication, or submitted in parallel to other peer-reviewed conferences with proceedings may not be submitted to ALT. Journals: Submissions that are substantially similar to papers that are already published in a journal at the time of submission may not be submitted to ALT. Rebuttal phase This year there will be a rebuttal phase during the review process. Authors will have an opportunity to provide a short response to the initial reviews. |
Summary |
ALT 2024 : 35th Annual Conference on Algorithmic Learning Theory will take place in San Diego, California, USA. It’s a 4 days event starting on Feb 25, 2024 (Sunday) and will be winded up on Feb 28, 2024 (Wednesday). ALT 2024 falls under the following areas: LEARNING THEORY, MACHINE LEARNING, NEURAL NETWORKS, BAYESIAN METHODS, etc. Submissions for this Conference can be made by Sep 26, 2023. Authors can expect the result of submission by Dec 15, 2023. Please check the official event website for possible changes before you make any travelling arrangements. Generally, events are strict with their deadlines. It is advisable to check the official website for all the deadlines. Other Details of the ALT 2024
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Credits and Sources |
[1] ALT 2024 : 35th Annual Conference on Algorithmic Learning Theory |