Machine Learning Safety
Machine learning algorithms allow computers to learn without being explicitly programmed. Their application is now spreading to highly sophisticated tasks across multiple domains, such as medical diagnostics or fully autonomous vehicles. While this development holds great potential, it also raises n...
I tiakina i:
| Ngā kaituhi matua: | Huang, Xiaowei (Author), Jin, Gaojie (Author), Ruan, Wenjie (Author) |
|---|---|
| Kaituhi rangatōpū: | SpringerLink (Online service) |
| Hōputu: | Tāhiko īPukapuka |
| Reo: | Ingarihi |
| I whakaputaina: |
Singapore :
Springer Nature Singapore : Imprint: Springer,
2023.
|
| Putanga: | 1st ed. 2023. |
| Rangatū: | Artificial Intelligence: Foundations, Theory, and Algorithms,
|
| Ngā marau: | |
| Urunga tuihono: | https://doi.org/10.1007/978-981-19-6814-3 |
| Ngā Tūtohu: |
Tāpirihia he Tūtohu
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
|
Ngā tūemi rite
Representation in Machine Learning
mā: Murty, M. N., me ētahi atu.
I whakaputaina: (2023)
mā: Murty, M. N., me ētahi atu.
I whakaputaina: (2023)
Machine Learning for Real World Applications
I whakaputaina: (2024)
I whakaputaina: (2024)
Practical Machine Learning Illustrated with KNIME
mā: Geng, Yu, me ētahi atu.
I whakaputaina: (2024)
mā: Geng, Yu, me ētahi atu.
I whakaputaina: (2024)
From Unimodal to Multimodal Machine Learning An Overview /
mā: Škrlj, Blaž
I whakaputaina: (2024)
mā: Škrlj, Blaž
I whakaputaina: (2024)
Reinforcement Learning Theory and Python Implementation /
mā: Xiao, Zhiqing
I whakaputaina: (2024)
mā: Xiao, Zhiqing
I whakaputaina: (2024)
Mean Field Guided Machine Learning
mā: Kang, Yuhan, me ētahi atu.
I whakaputaina: (2025)
mā: Kang, Yuhan, me ētahi atu.
I whakaputaina: (2025)
Machine Learning, Deep Learning and AI for Cybersecurity
I whakaputaina: (2025)
I whakaputaina: (2025)
Thinking Data Science A Data Science Practitioner’s Guide /
mā: Sarang, Poornachandra
I whakaputaina: (2023)
mā: Sarang, Poornachandra
I whakaputaina: (2023)
Causal Inference 6th Pacific Causal Inference Conference, PCIC 2024, Shanghai, China, July 5–6, 2024, Revised Selected Papers /
I whakaputaina: (2025)
I whakaputaina: (2025)
Online Machine Learning A Practical Guide with Examples in Python /
I whakaputaina: (2024)
I whakaputaina: (2024)
Metaheuristics for Machine Learning New Advances and Tools /
I whakaputaina: (2023)
I whakaputaina: (2023)
Machine Learning and Deep Learning in Computational Toxicology
I whakaputaina: (2023)
I whakaputaina: (2023)
Machine Learning for Data Science Handbook Data Mining and Knowledge Discovery Handbook /
I whakaputaina: (2023)
I whakaputaina: (2023)
Fundamentals of Reinforcement Learning
mā: Ris-Ala, Rafael
I whakaputaina: (2023)
mā: Ris-Ala, Rafael
I whakaputaina: (2023)
Domain-informed Machine Learning for Smart Manufacturing
mā: Huang, Qiang
I whakaputaina: (2025)
mā: Huang, Qiang
I whakaputaina: (2025)
Machine Learning with Python Theory and Implementation /
mā: Zollanvari, Amin
I whakaputaina: (2023)
mā: Zollanvari, Amin
I whakaputaina: (2023)
Estimating Ore Grade Using Evolutionary Machine Learning Models
mā: Ehteram, Mohammad, me ētahi atu.
I whakaputaina: (2023)
mā: Ehteram, Mohammad, me ētahi atu.
I whakaputaina: (2023)
Deep Learning Foundations and Concepts /
mā: Bishop, Christopher M., me ētahi atu.
I whakaputaina: (2024)
mā: Bishop, Christopher M., me ētahi atu.
I whakaputaina: (2024)
Applications of Game Theory in Deep Learning
mā: Hazra, Tanmoy, me ētahi atu.
I whakaputaina: (2024)
mā: Hazra, Tanmoy, me ētahi atu.
I whakaputaina: (2024)
Emerging ICT Technologies and Cybersecurity From AI and ML to Other Futuristic Technologies /
mā: Thakur, Kutub, me ētahi atu.
I whakaputaina: (2023)
mā: Thakur, Kutub, me ētahi atu.
I whakaputaina: (2023)
Neuro Symbolic Reasoning and Learning
mā: Shakarian, Paulo, me ētahi atu.
I whakaputaina: (2023)
mā: Shakarian, Paulo, me ētahi atu.
I whakaputaina: (2023)
Machine Learning in Single-Cell RNA-seq Data Analysis
mā: Raza, Khalid
I whakaputaina: (2024)
mā: Raza, Khalid
I whakaputaina: (2024)
Machine Learning Assisted Evolutionary Multi- and Many- Objective Optimization
mā: Saxena, Dhish Kumar, me ētahi atu.
I whakaputaina: (2024)
mā: Saxena, Dhish Kumar, me ētahi atu.
I whakaputaina: (2024)
Machine Learning and Mechanics Based Soft Computing Applications
I whakaputaina: (2023)
I whakaputaina: (2023)
Concise Guide to Quantum Machine Learning
mā: Pastorello, Davide
I whakaputaina: (2023)
mā: Pastorello, Davide
I whakaputaina: (2023)
Principles of Machine Learning The Three Perspectives /
mā: Wang, Wenmin
I whakaputaina: (2025)
mā: Wang, Wenmin
I whakaputaina: (2025)
Adversarial Machine Learning Attack Surfaces, Defence Mechanisms, Learning Theories in Artificial Intelligence /
mā: Sreevallabh Chivukula, Aneesh, me ētahi atu.
I whakaputaina: (2023)
mā: Sreevallabh Chivukula, Aneesh, me ētahi atu.
I whakaputaina: (2023)
Machine Learning Methods
mā: Li, Hang
I whakaputaina: (2024)
mā: Li, Hang
I whakaputaina: (2024)
AGC 2023 First Analytics Global Conference, AGC 2023, Kolkata, India, April 28–29, 2023, Proceedings /
I whakaputaina: (2024)
I whakaputaina: (2024)
Machine Learning and Soft Computing 9th International Conference, ICMLSC 2025, Tokyo, Japan, January 24–26, 2025, Revised Selected Papers, Part I /
I whakaputaina: (2025)
I whakaputaina: (2025)
Hybrid Models for Coupling Deductive and Inductive Reasoning Third International Workshop, HYDRA 2024, Santiago de Compostela, Spain, October 20, 2024, Revised Selected Papers /
I whakaputaina: (2025)
I whakaputaina: (2025)
Probability and Statistics for Machine Learning A Textbook /
mā: Aggarwal, Charu C.
I whakaputaina: (2024)
mā: Aggarwal, Charu C.
I whakaputaina: (2024)
Machine Learning and Artificial Intelligence
mā: Joshi, Ameet V.
I whakaputaina: (2023)
mā: Joshi, Ameet V.
I whakaputaina: (2023)
Handbook of Evolutionary Machine Learning
I whakaputaina: (2024)
I whakaputaina: (2024)
Mathematical Foundations of Reinforcement Learning
mā: Zhao, Shiyu
I whakaputaina: (2025)
mā: Zhao, Shiyu
I whakaputaina: (2025)
Machine Learning Techniques to Predict Terrorist Attacks Exemplified by Jama'at Nasr al-Islam wal Muslimin /
mā: Mostert, Laura, me ētahi atu.
I whakaputaina: (2025)
mā: Mostert, Laura, me ētahi atu.
I whakaputaina: (2025)
Machine Learning Governance for Managers
mā: Lazzeri, Francesca, me ētahi atu.
I whakaputaina: (2024)
mā: Lazzeri, Francesca, me ētahi atu.
I whakaputaina: (2024)
Machine Learning in Molecular Sciences
I whakaputaina: (2023)
I whakaputaina: (2023)
Trustworthy Machine Learning for Healthcare First International Workshop, TML4H 2023, Virtual Event, May 4, 2023, Proceedings /
I whakaputaina: (2023)
I whakaputaina: (2023)
Sustainable IoT and Data Analytics Enabled Machine Learning Techniques and Applications
I whakaputaina: (2024)
I whakaputaina: (2024)
Ngā tūemi rite
-
Representation in Machine Learning
mā: Murty, M. N., me ētahi atu.
I whakaputaina: (2023) -
Machine Learning for Real World Applications
I whakaputaina: (2024) -
Practical Machine Learning Illustrated with KNIME
mā: Geng, Yu, me ētahi atu.
I whakaputaina: (2024) -
From Unimodal to Multimodal Machine Learning An Overview /
mā: Škrlj, Blaž
I whakaputaina: (2024) -
Reinforcement Learning Theory and Python Implementation /
mā: Xiao, Zhiqing
I whakaputaina: (2024)