367 hasil untuk machine learning
Menampilkan 141–160 · 0,23 detik · RSS
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Fuzzy co-clustering with automated variable weighting
We propose two fuzzy co-clustering algorithms based on the double Kmeans algorithm. Fuzzy approaches are known to require more computation time than hard ones but the fuzziness principle allows a description of uncertainties that often appears in real world applications. The first algorithm…
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A next-generation of biomonitoring to detect global ecosystem change
There is growing interest in the potential for combining eDNA and artificial intelligence (machine learning) to detect and evaluate in real time changes in ecosystems at the global scale, in a more sensitive and cost-effective way than current biomonitoring methods. Machine learning might make…
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Information and Knowledge Systems. Digital Technologies, Artificial Intelligence and Decision Making - 5th International Conference, ICIKS 2021
…in topical sections as follows: knowledge systems and decision making; machine learning, recommender systems, and knowledge systems; and security, artificial intelligence, and information systems.
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AI Approaches for Designing and Evaluating Interactive Intelligent Systems
…Intelligence (AI) techniques due to advancements in the fields of Deep Learning (DL) and Natural Language Processing (NLP). This book presents in a structured way several practical use cases of the interplay between IIS and DL/NLP, from cognitive assistants, adaptive navigation systems, virtual…
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Deep Neural Networks Are Congestion Games: From Loss Landscape to Wardrop Equilibrium and Beyond
The theoretical analysis of deep neural networks (DNN) is arguably among the most challenging research directions in machine learning (ML) right now, as it requires from scientists to lay novel statistical learning foundations to explain their behaviour in practice. While some success has been…
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PROCEEDINGS OF THE GRAPH LABELLING WORKSHOP AND WEB SPAM CHALLENGE
International audience
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Data Science
…toute personne curieuse d'avoir une vue d'ensemble de l'état de l'art du machine learning.
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Modèles statistiques pour l'accès à l'information textuelle
Cet ouvrage présente les modèles statistiques récemment développés au sein de diverses communautés pour accéder à l'information contenue dans des collections textuelles. Les problématiques considérées sont liées aux applications visant à faciliter l'accès à l'information : recherche et extraction…
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Textual Information Access: Statistical Models
Statistical models recently developed in several research communities (natural language processing, information retrieval, machine learning) for textual information access pertain to several application domains: Information extraction and retrieval, Text classification and clustering, Opinion…
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Le traitement numérique des images en C++ - Implémentation d’algorithmes avec la bibliothèque CImg
International audience
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Informatique MP2I et MPI - CPGE 1re et 2e années - Nouveaux programmes
…mémoire et des problèmes de synchronisation et de concurrence dans une machine.Pour chacune de ces parties, les notions théoriques sont introduites, les différents algorithmes et méthodes développés et de nombreux exemples viennent illustrer chaque concept. Des exercices corrigés permettent de…
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Advances in Knowledge Discovery and Management. Studies in Computational Intelligence - volume 3 - Vol. 471
The recent and novel research contributions collected in this book are extended and reworked versions of a selection of the best papers that were originally presented in French at the EGC'2011 Conference held in Brest, France, on January 2011. EGC stands for "Extraction et Gestion des…
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Bayesian Programming
…models, general purpose algorithms for Bayesian inference, and learning problems. FAQs Along with a glossary, the fourth part contains answers to frequently asked questions. The authors compare Bayesian programming and possibility theories, discuss the computational complexity of Bayesian…
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Sparse Modeling for Image and Vision Processing
In recent years, a large amount of multi-disciplinary research has been conducted on sparse models and their applications. In statistics and machine learning, the sparsity principle is used to perform model selection---that is, automatically selecting a simple model among a large collection of…
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Deep IV in Law
Do US Circuit Courts' decisions on criminal appeals influence sentence lengths imposed by US District Courts? This Element explores the use of high-dimensional instrumental variables to estimate this causal relationship. Using judge characteristics as instruments, this Element implements two-stage…
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FAIR training handbook
Are you a developer of training material? Do you want to get more community involvement with your training material by making it Findable Accessible Interoperable and Reusable (FAIR)? Look no further, you are at the right (web)address! The ten chapters provide guidance on how you can FAIRify your…