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SPARSE CODING AND ITS APPLICATIONS IN COMPUTER VISION

SPARSE CODING AND ITS APPLICATIONS IN COMPUTER VISION

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Sparse Estimation with Math and Python: 100 Exercises for Building Logic

Sparse Estimation with Math and Python: 100 Exercises for Building Logic

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Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more

Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more

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Sparse Representation, Modeling and Learning in Visual Recognition: Theory, Algorithms and Applications (Advances in Computer Vision and Pattern Recognition)

Sparse Representation, Modeling and Learning in Visual Recognition: Theory, Algorithms and Applications (Advances in Computer Vision and Pattern Recognition)

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SIMULTANEOUS LOCALIZATION AND MAPPING: EXACTLY SPARSE INFORMATION FILTERS (New Frontiers in Robotics)

SIMULTANEOUS LOCALIZATION AND MAPPING: EXACTLY SPARSE INFORMATION FILTERS (New Frontiers in Robotics)

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Foundations of Real World Intelligence (Volume 125) (Lecture Notes)

Foundations of Real World Intelligence (Volume 125) (Lecture Notes)

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Robotic Tactile Perception and Understanding: A Sparse Coding Method

Robotic Tactile Perception and Understanding: A Sparse Coding Method

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DeepSeek in Action

DeepSeek in Action

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Cohesive Subgraph Computation over Large Sparse Graphs: Algorithms, Data Structures, and Programming Techniques (Springer Series in the Data Sciences)

Cohesive Subgraph Computation over Large Sparse Graphs: Algorithms, Data Structures, and Programming Techniques (Springer Series in the Data Sciences)

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Machine Learning for Biomedical Applications: With Scikit-Learn and PyTorch

Machine Learning for Biomedical Applications: With Scikit-Learn and PyTorch

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Hyperspectral Image Analysis: Advances in Machine Learning and Signal Processing (Advances in Computer Vision and Pattern Recognition)

Hyperspectral Image Analysis: Advances in Machine Learning and Signal Processing (Advances in Computer Vision and Pattern Recognition)

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Nonlinear Blind Source Separation and Blind Mixture Identification: Methods for Bilinear, Linear-quadratic and Polynomial Mixtures (SpringerBriefs in Electrical and Computer Engineering)

Nonlinear Blind Source Separation and Blind Mixture Identification: Methods for Bilinear, Linear-quadratic and Polynomial Mixtures (SpringerBriefs in Electrical and Computer Engineering)

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Minimizing Data Movement and Parameter Count Across the Machine Learning Stack: Everything is a Matrix (Synthesis Lectures on Computer Science)

Minimizing Data Movement and Parameter Count Across the Machine Learning Stack: Everything is a Matrix (Synthesis Lectures on Computer Science)

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Topic Detection and Classification in Social Networks: The Twitter Case

Topic Detection and Classification in Social Networks: The Twitter Case

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Feature Learning and Understanding: Algorithms and Applications (Information Fusion and Data Science)

Feature Learning and Understanding: Algorithms and Applications (Information Fusion and Data Science)

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Sparsity-Constrained Linear Dynamical Systems: From Compressed Sensing to Control Theory (Springer Tracts in Electrical and Electronics Engineering)

Sparsity-Constrained Linear Dynamical Systems: From Compressed Sensing to Control Theory (Springer Tracts in Electrical and Electronics Engineering)

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Advances in Principal Component Analysis: Research and Development

Advances in Principal Component Analysis: Research and Development

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