Pattern Recognition : 45th DAGM German Conference, DAGM GCPR 2023, Heidelberg, Germany, September 19–22, 2023, Proceedings
Ullrich Kothe
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Pattern Recognition : 45th DAGM German Conference, DAGM GCPR 2023, Heidelberg, Germany, September 19-22, 2023, Proceedings
Ullrich Kothe
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Healthcare Big Data Analytics : Computational Optimization and Cohesive Approaches
Akash Kumar Bhoi
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Strong Gravitational Lensing in the Era of Big Data (IAU S381)
Hannah (Max Planck Institute for Astrophysics, Germany) Stacey
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Machine Learning with Noisy Labels : Definitions, Theory, Techniques and Solutions
Gustavo (Professor of AI and Machine Learning, Centre for Vi Carneiro
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Machine Learning with Noisy Labels : Definitions, Theory, Techniques and Solutions
Gustavo Carneiro
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Intelligent Fractal-Based Image Analysis : Applications in Pattern Recognition and Machine Vision
Soumya Ranjan (Assistant Professor, Amity School of Engineering Nayak
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Fuzzy Rule-Based Inference : Advances and Applications in Reasoning with Approximate Knowledge Interpolation
Fangyi Li
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Neural Networks for Pattern Recognition
Christopher M. (, Microsoft Research) Bishop
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High-Dimensional Statistics : A Non-Asymptotic Viewpoint
Martin J. (University of California, Berkeley) Wainwright
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Pattern Recognition
Konstantinos (Institute for Space Applications & Remote S Koutroumbas
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Data Mining and Machine Learning : Fundamental Concepts and Algorithms
Mohammed J. (Rensselaer Polytechnic Institute, New York) Zaki
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Mining of Massive Datasets
Jure (Stanford University, California) Leskovec
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Mathematics for Machine Learning
Marc Peter (University College London) Deisenroth
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Inference and Learning from Data: Volume 2 : Inference
Ali H. (Ecole Polytechnique Federale de Lausanne) Sayed
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Plan, Activity, and Intent Recognition : Theory and Practice
Gita Sukthankar
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Introduction to Clustering Large and High-Dimensional Data
Jacob (University of Maryland, Baltimore) Kogan
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Introduction to Computational Genomics : A Case Studies Approach
Nello (University of Bristol) Cristianini
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Algorithms on Strings, Trees, and Sequences : Computer Science and Computational Biology
Dan Gusfield
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