now publishers Inc Learning with Submodular Functions: A Convex Optimization Perspective (Foundations and Trends® in Machine Learning)

Non-convex Optimization for Machine Learning (Foundations and Trends in Machine Learning)

Now Publishers

Convex Optimization for Machine Learning (NowOpen)

Introduction to Online Convex Optimization (Foundations and Trends (R) in Optimization)

Now Publishers Inc

Optimization for Machine Learning (Neural Information Processing series)

MIT Press

Submodular Functions and Optimization (Annals of Discrete Mathematics): Volume 58

Elsevier

Chordal Graphs and Semidefinite Optimization (Foundations and Trends (R) in Optimization)

now publishers Inc

Tensor Networks for Dimensionality Reduction and Large-scale Optimization: Part 1 Low-Rank Tensor Decompositions (Foundations and Trends (R) in Machine Learning)

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Convex Optimization with Computational Errors: 155 (Springer Optimization and Its Applications, 155)

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Machine Learning from Weak Supervision: An Empirical Risk Minimization Approach (Adaptive Computation and Machine Learning series)

MIT Press

Machine Learning: A Constraint-Based Approach

Morgan Kaufmann

Regularization, Optimization, Kernels, and Support Vector Machines (Chapman & Hall/CRC Machine Learning & Pattern Recognition)

CRC Press

Optimization for Learning and Control

Wiley

Elements of Dimensionality Reduction and Manifold Learning

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Machine Learning: A Bayesian and Optimization Perspective

Academic Press

Optimization on Solution Sets of Common Fixed Point Problems: 178 (Springer Optimization and Its Applications, 178)

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An Introduction to Approaches and Modern Applications with Ensemble Learning (Computer Science, Technology and Applications)

Linear Algebra and Optimization for Machine Learning: A Textbook

Machine Learning Methods

Springer

Tensor Networks for Dimensionality Reduction and Large-scale Optimization: Part 2 Applications and Future Perspectives (Foundations and Trends in Machine Learning)

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Lectures on Convex Optimization: 137 (Springer Optimization and Its Applications, 137)

Springer

Discrete Graphical Models: An Optimization Perspective (Foundations and Trends® in Computer Graphics and Vision)

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Machine Learning in Complex Networks

Springer

Kernel Mean Embedding of Distributions: A Review and Beyond (Foundations and Trends in Machine Learning)

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Applied Machine Learning

Springer