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comparing models with entirely different structures and parameter counts, whether comparing linear regression against mixture models or decision trees. MML is strictly Bayesian, requiring prior distributions
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, which brings together several teams from different laboratories across France. It will take place within the Computer Science and Systems Laboratory (LIS), in the DALGO team for algorithms and distributed
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Fund. Subject description The subject includes signal processing with emphasis on development and optimization of algorithms for processing single and multi-dimensional signals that are closely related
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advanced algorithms that efficiently utilize UWB signal features (RSSI, channel impulse response, phase and amplitude data, Doppler maps,..) to support both high-precision localization and radar-based
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, especially in the case of fast charging. · Integrate electrochemical, thermal, and even mechanical effects into models. · Analyze the differences between homogeneous and heterogeneous models
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in mathematical theory. Unlike standard deep networks, each connection in a KAN learns a continuous function, allowing a richer and more flexible representation of computation. This perspective aligns
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machine learning algorithms for anomaly detection, pattern recognition, and efficient data compression. To ensure practical usability, these models will also be optimized to run efficiently on edge hardware
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data donation. To analyze how different types of people cope with algorithmic persuasion on TikTok and how this relates to how they are affected you will make use of a survey. To formulate guidelines
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to research on language and speech development across different populations and contexts, including children acquiring language in different cultural settings outside of the United States to children with
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réseaux neuronaux) et les décompositions tensorielles (multicouches) de rang faible [5,6,7], qui fournissent un cadre mathématique rigoureux pour développer des nouveaux algorithmes et architectures et pour