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Kernel Methods and Machine Learning

S. Y. Kung

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簡介

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關於本書

語言：English
ISBN：9781139861892
發行日期：2014年4月2日
出版商：Cambridge University Press

出版單位：Cambridge University Press
檔案格式：EPUB2
檔案大小：17.00 MB
下載選項：EPUB2 (Adobe DRM)

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Kernel Methods and Machine Learning

為什麼要和我們一起閱讀？

簡介

關於本書

書籍詳細資料

如何閱讀

延伸閱讀

Pattern Recognition

Performance Modeling and Design of Computer Systems

System Identification

Statistical and Machine Learning Approaches for Network Analysis

Neural Networks and Statistical Learning

Guide to Intelligent Data Analysis

Kernel Methods for Pattern Analysis

Statistical Analysis Techniques in Particle Physics

An Introduction to Machine Learning

Bayesian Networks in R

Bayesian Networks

Computational Intelligence

Probabilistic Reliability Models

Modeling and Reasoning with Bayesian Networks

Simulation-Based Algorithms for Markov Decision Processes

Algorithms for Sparsity-Constrained Optimization

Core Concepts in Data Analysis: Summarization, Correlation and Visualization

Graphical Models with R

Fundamentals of Computational Intelligence

An Introduction to Support Vector Machines and Other Kernel-based Learning Methods

Optimization in Engineering Sciences

Linear Models

Data Analysis

Rough-Fuzzy Pattern Recognition

Kernel-based Approximation Methods Using Matlab

Handbook of Blind Source Separation

Pattern Recognition and Machine Learning

Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods

Stochastic Local Search

Mathematical Perspectives on Neural Networks

Optimization

Matrix Information Geometry

Clustering High--Dimensional Data

Support Vector Machines for Pattern Classification

Type-2 Fuzzy Graphical Models for Pattern Recognition

Handbook of Computational Statistics

Principal Component Analysis Networks and Algorithms

Computational Intelligence

Low Rank Approximation

Probability and Statistics with Reliability, Queuing, and Computer Science Applications

Optimization and Optimal Control

Advances in K-means Clustering

Similarity-Based Pattern Analysis and Recognition

Type-2 Fuzzy Neural Networks and Their Applications

Analog Electronics

Stochastic Processes

Digital Signal Processing

Introduction to Medical Imaging

Applied Matrix and Tensor Variate Data Analysis

Statistical Signal Processing for Neuroscience and Neurotechnology

Random-Like Multiple Objective Decision Making

Advanced Signal Processing On Brain Event-related Potentials: Filtering Erps In Time, Frequency And Space Domains Sequentially And Simultaneously

Ensemble Machine Learning

Carrier Grade Voice Over IP, Third Edition

Research Methods for Engineers

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Academic Press Library in Signal Processing

Signals and Systems for Bioengineers

Clusters, Orders, and Trees: Methods and Applications

Weighted Network Analysis

Multivariate Statistical Process Control

Performance Analysis of Complex Networks and Systems

Non-negative Matrix Factorization Techniques

Multidimensional Systems Signal Processing Algorithms and Application Techniques

System Parameter Identification

Model Calibration and Parameter Estimation

Computing and Visualization for Intravascular Imaging and Computer-Assisted Stenting

Visible Light Communication

Learning in Non-Stationary Environments

Developments in Medical Image Processing and Computational Vision

Semi-Supervised and Unsupervised Machine Learning

Modeling and Optimization: Theory and Applications