1 option
Math optimization for artificial intelligence : heuristic and metaheuristic methods for robotics and machine learning / edited by Umesh Kumar Lilhore [and four others].
- Format:
- Book
- Series:
- Mathematical Methods in the Digital Age Series ; v. 2.
- Mathematical Methods in the Digital Age Series ; Volume 2
- Language:
- English
- Subjects (All):
- Machine learning.
- Robotics.
- Physical Description:
- 1 online resource (434 pages)
- Edition:
- First edition.
- Place of Publication:
- Berlin, Germany : Walter de Gruyter, [2025]
- Summary:
- The book presents powerful optimization approaches for integrating AI into daily life.This book explores how heuristic and metaheuristic methodologies have revolutionized the fields of robotics and machine learning.
- Contents:
- Intro
- Foreword
- Contents
- List of Authors
- 1 The Role of Mathematical Optimization in Advanced AI Applications
- 2 An Overview of Mathematical Optimization in Artificial Intelligence
- 3 Robust Optimization Methods for Ensuring AI System Reliability
- 4 Swarm Intelligence and Optimization in AI
- 5 Privacy and Security for 6G's IoT-Connected Future in the Age of Quantum Computing
- 6 Optimization in Natural Language Processing Models for Enhanced Performance and Efficiency
- 7 Unveiling the Intriguing Applications of Mathematical Optimization in Artificial Intelligence
- 8 Unleashing the Power of Evolutionary Algorithms: Advanced Optimization Techniques in Artificial Intelligence
- 9 Introduction to Mathematical Optimization Techniques in AI
- 10 Hybrid Mathematical Optimization Techniques in AI
- 11 Mathematical Optimization for Enhanced AI-Enabled Geospatial Intelligence
- 12 Deep Learning-Based Ultrasound Analysis Using Explainable Artificial Intelligence (XAI) Methods for Breast Cancer
- 13 Explainable Artificial Intelligence Techniques in Deep Learning-Based Liver Tumor Analysis
- 14 A Novel African Wild Dog Optimization (AWDO) Algorithm for Applications of Artificial Intelligence
- 15 Artificial Intelligence-Based Control Strategies for COVID-19 That Target Different Age Groups
- 16 Model Optimization in Deep Learning: Theory and Application
- 17 Quantitative Analysis for LMS Using Mathematical Modeling by Artificial Intelligence
- 18 Optimizing Neural Network Training by Addressing Key Challenges and Advanced Techniques
- 19 Principles and Applications of Bayesian Optimization in AI
- Index.
- Notes:
- Description based on publisher supplied metadata and other sources.
- Description based on print version record.
- ISBN:
- 9783111436180
- 3111436187
- OCLC:
- 1511106114
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.