Springer Unsupervised Domain Adaptation: Recent Advances and Future Perspectives (Machine Learning: Foundations, Methodologies, and Applications)

Unsupervised Domain Adaptation: Recent Advances and Future Perspectives (Machine Learning: Foundations, Methodologies, and Applications)

Springer - Federated Learning: Fundamentals and Advances Book

Springer

Machine Learning for Computer Scientists and Data Analysts: From an Applied Perspective

Springer

Topic Modeling: Advanced Techniques and Applications (Machine Learning: Foundations, Methodologies, and Applications)

Machine Learning in Educational Sciences: Approaches, Applications and Advances

Derivative-Free Optimization: Theoretical Foundations, Algorithms, and Applications (Machine Learning: Foundations, Methodologies, and Applications)

Springer

Springer - Applications of Machine Learning Book

Springer

Data Driven Model Learning for Engineers: With Applications to Univariate Time Series

Springer

Machine Learning for Advanced Functional Materials

Springer

Alternating Direction Method of Multipliers for Machine Learning

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Machine Learning in Biological Sciences: Updates and Future Prospects

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Cross-device Federated Recommendation: Privacy-Preserving Personalization (Machine Learning: Foundations, Methodologies, and Applications)

Springer - Hidden Markov Models and Applications Book

Springer

Springer - Trustworthy Machine Learning under Imperfect Data

Springer

Feature and Dimensionality Reduction for Clustering with Deep Learning (Unsupervised and Semi-Supervised Learning)

Uncertainty, Optimization and Machine Learning with Applications (Mathematics for Sustainable Developments)

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Machine Learning Applications in Electronic Design Automation

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Springer - Metaheuristics for Machine Learning Book

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Robust Machine Learning: Distributed Methods for Safe AI (Machine Learning: Foundations, Methodologies, and Applications)

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Robust Machine Learning: Distributed Methods for Safe AI (Machine Learning: Foundations, Methodologies, and Applications)

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Multi-faceted Deep Learning: Models and Data

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Recent Trends and Future Challenges in Learning from Data (Studies in Classification, Data Analysis, and Knowledge Organization)

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Advanced Machine Learning with Evolutionary and Metaheuristic Techniques (Computational Intelligence Methods and Applications)

Advanced Automation for Comprehensible Causal Explanations of Reinforcement Learning Agents

Springer