Machine learning has relied heavily on a traditional view of the learning process, whereby observations are assumed to be i.i.d., typically given as a dataset split into a training and validation set with the explicit focus to maximize performance on the latter. While this view proved to be immensely beneficial for the field, it represents just a fraction of the realistic scenarios of interest. Over the past few decades, increased attention has been given to alternative paradigms that help explore different aspects of the learning process, from lifelong learning, continual learning, and meta-learning to transfer learning, multi-task learning and out-of-distribution generalization to name just a few.
The Conference on Lifelong Learning Agents (CoLLAs) focuses on these learning paradigms that aim to move beyond the traditional, single-distribution machine learning setting and to allow learning to be more robust, more efficient in terms of compute and data, more versatile in terms of being able to handle multiple problems and be well-defined and well-behaved in more realistic non-stationary settings compared to the traditional view.
We invite submissions to the 2nd edition of CoLLAs that describe applications, new theories, methodology or new insights into existing algorithms and/or benchmarks. Accepted papers will be published in the Proceedings of Machine Learning Research (PMLR). Topics of submission may include, but are not limited to, Reinforcement Learning, Supervised Learning or Unsupervised Learning approaches for:
The conference also welcomes submissions at the intersection of machine learning and neuroscience and applications of the topics of interest to real-world problems. Submitted papers will be evaluated based on their novelty, technical quality, and potential impact. Experimental methods and results are expected to be reproducible, and authors are strongly encouraged to make code and data available. We also encourage submissions of proof-of-concept research that puts forward novel ideas and demonstrates potential, as well as in-depth analysis of existing methods and concepts.Key Dates
The planned dates are as follows:
Papers will be selected via double-blind peer-review process. All accepted papers will be presented at the Conference as contributed talks or as posters and will be published in the Proceedings (PMLR). Additionally there is a non-archival workshop track, which will also go through the review process.
The reviews process will be hosted on OpenReview with submissions and reviews being private until a decision is made. Reviews and discussions of the accepted papers will be made available after acceptance. In addition to accept/reject, a paper can be marked for conditional acceptance. In this case, the authors have a fixed amount of time to incorporate a clear list of demands from the Program Chairs, and if these updates are present the paper will automatically get accepted. Rejected papers that initially received a conditional acceptance (where authors decided not to add the required modifications) can be presented in the workshop track if the authors chose to. The authors will still be able to present a poster on their work as part of this track. This system is aimed to produce a fairer treatment of borderline papers and to save the time spent in going through the entire reviewing process from scratch when resubmitting to a future edition of the conference or a different relevant conference.
During the rebuttal period, authors are allowed to update their papers once. All updates should be clearly marked using the macros provided in the latex style files. However, reviewers are not required to read the new version.
Physical and Virtual Attendance
Collas 2023 will be mainly an in-person event, in Montreal Canada. We believe that in-person interactions are important to grow the community. However, we recognize that participating in person might not be possible for everyone for various reasons, including health concerns around COVID. Therefore participants will have the option to participate virtually at the conference and present virtually their work by providing a prerecorded video. However this will not be a fully hybrid event, and not all elements will be available to virtual participants. More information about the organization soon.Formatting and Supplementary Material
Submissions should have a recommended length of 9 single-column CoLLAs-formatted pages, plus unlimited pages for references and appendices. We enforce a maximum length of 10 pages, where the 10th page can be used if it helps with the formatting of the paper. The camera ready version will have a strict 10 page limit. So please do not use the entire 10th page during the initial submission. The appendices should be within the same pdf file as the main publication, however, an additional zip file can be submitted that can include multiple files of different formats (e.g. videos or code). Note that reviewers are under no obligation to examine the appendix and the supplementary material.
Please format the paper using the official LaTeX style files that can be found on overleaf here or on GitHub here. We do not support submissions in formats other than LaTeX. Please do not modify the layout given by the style file. For any questions, you can reach us at: con...@lifelong-ml.cc.
Submissions will be through OpenReview.Abstract and Title
Authors should include a full title for their paper, as well as a complete abstract by the abstract submission deadline. Submission titles should not be modified after the abstract submission deadline, and abstracts should not be modified by more than 50% after the abstract submission deadline. Submissions violating these rules may be deleted after the paper submission deadline without review. The author list can be updated until the paper submission deadline. Only the ordering of the authors can be changed when submitting the camera-ready version of the paper.Anonymization Requirements
All submissions must be anonymized and may not contain any information with the intention or consequence of violating the double-blind reviewing policy, including (but not limited to) citing previous works of the authors or sharing links in a way that can infer any author’s identity or institution, actions that reveal the identities of the authors to potential reviewers.
Authors are allowed to post versions of their work on preprint servers such as Arxiv. They are also allowed to give talks to restricted audiences on the work(s) submitted to CoLLAs during the review. If you have posted or plan to post a non-anonymized version of your paper online before the CoLLAs decisions are made, the submitted version must not refer to the non-anonymized version.
CoLLAs strongly discourages advertising the preprint on social media or in the press while under submission to CoLLAs. Under no circumstances should your work be explicitly identified as CoLLAs submission at any time during the review period, i.e. from the time you submit the abstract to the communication of the accept/reject decisions.Dual Submissions
It is not appropriate to submit papers that are identical (or substantially similar) to versions that have been previously published, accepted for publication, or submitted in parallel to other conferences or journals. Such submissions violate our dual submission policy, and the organizers have the right to reject such submissions or to remove them from the proceedings.Code of Conduct and Ethics
All participants in CoLLAs, including authors, will be required to adhere to CoLLAs code of conduct & ethics. Plagiarism in any form is strictly forbidden as it is an unethical use of privileged information by reviewers, such as sharing it or using it for any other purpose than the reviewing process. All suspected unethical behaviours will be investigated and individuals found violating the rules may face sanctions. Further details about CoLLAs code of conduct, ethics and reproducibility can be found on the website.
-----------Vincenzo Lomonaco on behalf of the 2023 CoLLAs Organizing Committee.