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<\/div>\n Call for Contributions<\/span><\/strong>\n <\/span>\n <\/h1>\n We are excited to invite you to submit proposals for contributed talks and posters for ML in PL Conference 2022 that will be organized 4-6 November 2022.<\/span><\/p>\n We believe that anyone can make a valuable contribution to the field of machine learning and in our eyes, an important contribution is not necessarily the most novel research. Therefore we wish to bring together a broad array of researchers, specialists, practitioners, educators, students, and others of diverse backgrounds, locations, and genders to present their works at the conference.<\/span><\/p>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n \n <\/div>\n \n <\/section>\n \n \n \n \n <\/i>\n \n General Machine Learning<\/span><\/strong>\n \n <\/span>\n <\/p>\n Active Learning, Classification, Clustering, Learning Theory, Online Learning, Ranking, Regression, Semi-supervised and Unsupervised learning, Optimization, Sparsity, etc.<\/span>\n \n <\/p>\n <\/div>\n <\/div>\n \n <\/div>\n \n <\/i>\n \n Reinforcement Learning<\/span><\/strong>\n <\/span>\n <\/p>\n Bandits, Decision and Control, Exploration, Hierarchical RL, Markov Decision Processes, Multi-Agent RL, Navigation, Planning, etc.<\/span><\/p>\n <\/div>\n <\/div>\n \n <\/div>\n \n <\/i>\n \n Applications of Machine Learning<\/span><\/strong>\n <\/span>\n <\/p>\n Audio and Speech Processing, Computational Biology, Computer Vision, Natural Language Processing, Robotics, Neuroscience, Physics, Social Good, etc.<\/span><\/p>\n <\/div>\n <\/div>\n \n <\/div>\n \n <\/i>\n \n Probabilistic Methods<\/span><\/strong>\n <\/span>\n <\/p>\n Bayesian methods, Causal Inference, Gaussian Processes, Graphical Models, etc.<\/span><\/p>\n <\/div>\n <\/div>\n \n <\/div>\n \n <\/i>\n \n Deep Learning<\/span><\/strong>\n <\/span>\n <\/p>\n Architectures, Generative Models, Optimization for Deep Networks, Recurrent Networks, etc.<\/span><\/p>\n <\/div>\n <\/div>\n \n <\/div>\n \n <\/i>\n \n Explainable Machine Learning<\/span>
<\/span><\/strong><\/p>\n Explainability, Causality, Biased Data, Fairness, Robustness, etc.<\/span><\/p>\n <\/div>\n <\/div>\n \n <\/div>\n \n <\/i>\n \n Social Aspects of Machine Learning<\/span><\/strong>\n <\/span>\n <\/p>\n AI\/ML Ethics, AI\/ML Safety, Causality, eXplainable AI, Responsible AI\/ML, Biased Data, Fairness, Privacy, Robustness, and Safety, etc.<\/span><\/p>\n <\/div>\n <\/div>\n \n <\/div>\n \n <\/i>\n \n Technical Solutions and Machine Learning Resources<\/span><\/strong>\n <\/span>\n <\/p>\n Architectures, Competitions, Data Sets, and Repositories, Distributed Machine Learning, Implementations, Software Toolkits, etc.<\/span><\/p>\n <\/div>\n <\/div>\n \n <\/div>\n \n <\/i>\n \n Machine Learning Stories<\/span><\/strong>\n <\/span>\n <\/p>\n Interesting and insightful competitions, projects and start-up stories!<\/span><\/p>\n <\/div>\n <\/div>\n \n <\/div>\n <\/div>\n \n <\/div>\n \n <\/section>\n \n \n \n \n We aim at providing a forum for discussing recent advances from the possible broadest range of topics and perspectives, we especially encourage (but not limit) submissions related to the following topics of interest:<\/span><\/p>\n <\/div>\n <\/div>\n \n <\/div>\n \n <\/section>\n \n \n \n \n \n Registration<\/span><\/strong>\n <\/span>\n <\/h1>\n Registration is currently closed.<\/span><\/p>\n The talks will have a length of 20 minutes + 5 minutes for questions. To participate in Call for Contributions, we ask you to provide the title of your talk\/poster proposal, abstract up to 300 words, preference towards talk or poster, short bio and list of your previous talks. Talks and posters should be in English. The submission deadline is 21 <\/strong>September 2022<\/strong>. With the help of the Contributions Committee, we will select the best proposals.<\/span><\/p>\n This year the factors that will be considered the most when evaluating submissions include:<\/span><\/p>\n 1. The relevance of the proposed topic in the current machine learning landscape.<\/span>
2. Novelty and uniqueness of the proposed topic. Even if your topic does not fall into any listed areas, do not feel discouraged to submit it! Also interdisciplinary topics are especially highly encouraged!<\/span>
3. Enjoyable by our audience: a good balance between accessibility and scientific excellence.<\/span>
4. For talks proposals we will take into account the author\u2019s speaking experience, however, it does not mean that we will reject all inexperienced speakers.<\/span>
5. Talks\/posters proposals with clear promotion of the commercial products will be rejected.<\/span><\/p>\n <\/div>\n <\/div>\n <\/div>\n \n <\/div>\n \n <\/section>\n \n \n \n \n \n Accepted talks and posters<\/span><\/strong>\n <\/span>\n <\/p>\n Instructions for preparing your talk and poster can be found here<\/a>.<\/span><\/p>\n The list of accepted talks and posters (with slides and poster in pdf format) is available here<\/a>.<\/span><\/p>\n
We believe that anyone can make a valuable contribution to the field of machine learning and in our eyes, an important contribution is not necessarily the most novel research. Therefore we wish to bring together a broad array of researchers, specialists, practitioners, educators, students, and others of diverse backgrounds, locations, and genders to present their works at the conference.<\/span><\/p>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n \n <\/div>\n \n <\/section>\n General Machine Learning<\/span><\/strong>\n \n <\/span>\n <\/p>\n Active Learning, Classification, Clustering, Learning Theory, Online Learning, Ranking, Regression, Semi-supervised and Unsupervised learning, Optimization, Sparsity, etc.<\/span>\n \n <\/p>\n <\/div>\n <\/div>\n \n <\/div>\n Reinforcement Learning<\/span><\/strong>\n <\/span>\n <\/p>\n Bandits, Decision and Control, Exploration, Hierarchical RL, Markov Decision Processes, Multi-Agent RL, Navigation, Planning, etc.<\/span><\/p>\n <\/div>\n <\/div>\n \n <\/div>\n Applications of Machine Learning<\/span><\/strong>\n <\/span>\n <\/p>\n Audio and Speech Processing, Computational Biology, Computer Vision, Natural Language Processing, Robotics, Neuroscience, Physics, Social Good, etc.<\/span><\/p>\n <\/div>\n <\/div>\n \n <\/div>\n Probabilistic Methods<\/span><\/strong>\n <\/span>\n <\/p>\n Bayesian methods, Causal Inference, Gaussian Processes, Graphical Models, etc.<\/span><\/p>\n <\/div>\n <\/div>\n \n <\/div>\n Deep Learning<\/span><\/strong>\n <\/span>\n <\/p>\n Architectures, Generative Models, Optimization for Deep Networks, Recurrent Networks, etc.<\/span><\/p>\n <\/div>\n <\/div>\n \n <\/div>\n Explainable Machine Learning<\/span> Explainability, Causality, Biased Data, Fairness, Robustness, etc.<\/span><\/p>\n <\/div>\n <\/div>\n \n <\/div>\n Social Aspects of Machine Learning<\/span><\/strong>\n <\/span>\n <\/p>\n AI\/ML Ethics, AI\/ML Safety, Causality, eXplainable AI, Responsible AI\/ML, Biased Data, Fairness, Privacy, Robustness, and Safety, etc.<\/span><\/p>\n <\/div>\n <\/div>\n \n <\/div>\n Technical Solutions and Machine Learning Resources<\/span><\/strong>\n <\/span>\n <\/p>\n Architectures, Competitions, Data Sets, and Repositories, Distributed Machine Learning, Implementations, Software Toolkits, etc.<\/span><\/p>\n <\/div>\n <\/div>\n \n <\/div>\n Machine Learning Stories<\/span><\/strong>\n <\/span>\n <\/p>\n Interesting and insightful competitions, projects and start-up stories!<\/span><\/p>\n <\/div>\n <\/div>\n \n <\/div>\n <\/div>\n \n <\/div>\n \n <\/section>\n We aim at providing a forum for discussing recent advances from the possible broadest range of topics and perspectives, we especially encourage (but not limit) submissions related to the following topics of interest:<\/span><\/p>\n <\/div>\n <\/div>\n \n <\/div>\n \n <\/section>\n Registration is currently closed.<\/span><\/p>\n The talks will have a length of 20 minutes + 5 minutes for questions. To participate in Call for Contributions, we ask you to provide the title of your talk\/poster proposal, abstract up to 300 words, preference towards talk or poster, short bio and list of your previous talks. Talks and posters should be in English. The submission deadline is 21 <\/strong>September 2022<\/strong>. With the help of the Contributions Committee, we will select the best proposals.<\/span><\/p>\n This year the factors that will be considered the most when evaluating submissions include:<\/span><\/p>\n 1. The relevance of the proposed topic in the current machine learning landscape.<\/span> Accepted talks and posters<\/span><\/strong>\n <\/span>\n <\/p>\n Instructions for preparing your talk and poster can be found here<\/a>.<\/span><\/p>\n The list of accepted talks and posters (with slides and poster in pdf format) is available here<\/a>.<\/span><\/p>\n
<\/span><\/strong><\/p>\n Registration<\/span><\/strong>\n <\/span>\n <\/h1>\n
2. Novelty and uniqueness of the proposed topic. Even if your topic does not fall into any listed areas, do not feel discouraged to submit it! Also interdisciplinary topics are especially highly encouraged!<\/span>
3. Enjoyable by our audience: a good balance between accessibility and scientific excellence.<\/span>
4. For talks proposals we will take into account the author\u2019s speaking experience, however, it does not mean that we will reject all inexperienced speakers.<\/span>
5. Talks\/posters proposals with clear promotion of the commercial products will be rejected.<\/span><\/p>\n <\/div>\n <\/div>\n <\/div>\n \n <\/div>\n \n <\/section>\n