Human and Machine Learning by Jianlong Zhou
With an evolutionary advancement of Machine Learning (ML) algorithms, a rapid increase of data volumes and a significant improvement of computation powers, machine learning becomes hot in different applications. However, because of the nature of “black-box” in ML methods, ML still needs to be interpreted to link human and machine learning for transparency and user acceptance of delivered solutions. This edited book addresses such links from the perspectives of visualisation, explanation, trustworthiness and transparency. The book establishes the link between human and machine learning by exploring transparency in machine learning, visual explanation of ML processes, algorithmic explanation of ML models, human cognitive responses in ML-based decision making, human evaluation of machine learning and domain knowledge in transparent ML applications.
This is the first book of its kind to systematically understand the current active research activities and outcomes related to human and machine learning. The book will not only inspire researchers to passionately develop new algorithms incorporating human for human-centred ML algorithms, resulting in the overall advancement of ML, but also help ML practitioners proactively use ML outputs for informative and trustworthy decision making.
This book is intended for researchers and practitioners involved with machine learning and its applications. The book will especially benefit researchers in areas like artificial intelligence, decision support systems and human-computer interaction.
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Sonic Interactions in Virtual Environments
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Funology
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Whole Body Interaction
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The Technology Acceptance Model
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Design for Flexibility
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Artificial Intelligence for Human Computer Interaction: A Modern Approach
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Web Accessibility
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Visualization of Time-Oriented Data
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Universal Design in Video Games
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Human-Centered Software Engineering
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Global Usability
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A Human-Centered Perspective of Intelligent Personalized Environments and Systems
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Artificial Intelligence for Customer Relationship Management
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Modern Statistical Methods for HCI
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Communication Skills for Generative AI
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Radar-Based Human-Computer Interaction
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Cognitive Modeling for Automated Human Performance Evaluation at Scale
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Smart Automotive Mobility
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Macrotask Crowdsourcing
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Advances in Physiological Computing
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Social Robots: Technological, Societal and Ethical Aspects of Human-Robot Interaction
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HCI and Design in the Context of Dementia
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Doing Design Ethnography
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Social Interaction, Globalization and Computer-Aided Analysis
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Virtual Taste and Smell Technologies for Multisensory Internet and Virtual Reality
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Online Worlds: Convergence of the Real and the Virtual
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Pen-and-Paper User Interfaces
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Primitive Interaction Design
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Researching Learning in Virtual Worlds
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HCI and User-Experience Design
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User-Centered Interaction Design Patterns for Interactive Digital Television Applications
Dr. Zhou is a leading senior researcher in trustworthy and transparent machine learning, and has done pioneering research in the area of linking human and machine learning. He also works with industries in advanced data analytics for transforming data into actionable operations particularly by incorporating human user aspects into machine learning and translate machine learning into impacts in real world applications.
| SKU | Unavailable |
| ISBN 13 | 9783319904023 |
| ISBN 10 | 3319904027 |
| Title | Human and Machine Learning |
| Author | Jianlong Zhou |
| Series | Human-Computer Interaction Ser |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Springer International Publishing AG |
| Year published | 2018-06-20 |
| Number of pages | 482 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |