The access to very large databases, combined with ever-increasing computation speed, has paved the way for the development of new artificial intelligence (AI) tools, which have sparked a revolution in industry and services. Machine learning, boosted by the Internet of Things, is at the heart of AI and can now be applied to practically all industrial processes, including the design of a product, how it is used and associated services.
To be used in decision-making in critical areas (defense, health, transportation…) or simply to permit the necessary trust that technology requires to be adopted, AI systems must offer guarantees on their correctness, their robustness, the traceability of learning and the interpretability of their decisions. Moreover, embedded in a non-stationary environment, they are supposed to interact with their environment, be aware of their potential weaknesses and continue to improve themselves through relevant interactions. For research groups, this represents a set of stimulating challenges whose solutions will be the key to the long-lasting use of Data Science and AI tools.
This second edition of the International Workshop on Machine Learning and AI aims at presenting recent approaches developed to cope with these stimulating challenges of AI, with illustrations in the fields of robotics and natural language processing, in particular. It will serve as a forum for academics and practitioners working on both theoretical and practical aspects of learning systems for AI.
It will be funded by the new teaching and research chair, Data Science & Artificial Intelligence for Digitalized Industry & Services (DSAIDIS) led by Florence d’Alché-Buc, Full Professor in Computer Science and Applied Mathematics at Télécom Paris.
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