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Conformal Prediction for Reliable Machine Learning
The conformal predictions framework is a recent development in machine learning that can associate a reliable measure of confidence with a prediction in any real-world pattern recognition application, including risk-sensitive applications such as medical diagnosis, face recognition, and financial risk prediction. Conformal Predictions for Reliable Machine Learning: Theory, Adaptations and Applications captures the basic theory of the framework, demonstrates how to apply it to real-world problems, and presents several adaptations, including active learning, change detection, and anomaly detection. As practitioners and researchers around the world apply and adapt the framework, this edited vol...
Social, Cultural, and Behavioral Modeling
This book constitutes the refereed proceedings of the 10th International Conference on Social, Cultural, and Behavioral Modeling & Prediction and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2017, held in Washington, DC, USA, in July 2017. The 16 full papers and 27 short papers presented were carefully reviewed and selected from 79 submissions. Owing to its strong multi-disciplinary heritage, the papers represent a large range of disciplines including computer science, psychology, sociology, communication science, public health, bioinformatics, political science, and organizational science and use numerous types of computational methods such as machine learning, language technology, social network analysis and visualization, agent-based simulation, and statistics. They are organized in the following topical sections: behavioral and social sciences; cyber and intelligence applications; information, systems, and network sciences; and methodology.
Social Computing, Behavioral-Cultural Modeling and Prediction
This book constitutes the refereed proceedings of the 7th International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction, SBP 2014, held in Washington, DC, USA, in April 2014. The 51 full papers presented were carefully reviewed and selected from 101 submissions. The SBP conference provides a forum for researchers and practitioners from academia, industry, and government agencies to exchange ideas on current challenges in social computing, behavioral-cultural modeling and prediction, and on state-of-the-art methods and best practices being adopted to tackle these challenges. The topical areas addressed by the papers are social and behavioral sciences, health sciences, military science, and information science.
Database Systems for Advanced Applications
The three-volume set LNCS 13245, 13246 and 13247 constitutes the proceedings of the 26th International Conference on Database Systems for Advanced Applications, DASFAA 2022, held online, in April 2021. The total of 72 full papers, along with 76 short papers, are presented in this three-volume set was carefully reviewed and selected from 543 submissions. Additionally, 13 industrial papers, 9 demo papers and 2 PhD consortium papers are included. The conference was planned to take place in Hyderabad, India, but it was held virtually due to the COVID-19 pandemic.
Social, Cultural, and Behavioral Modeling
This book constitutes the proceedings of the 12th International Conference on Social, Cultural, and Behavioral Modeling, SBP-BRiMS 2019, held in Washington, DC, USA, in July 2019. The total of 28 papers presented in this volume was carefully reviewed and selected from 72 submissions. The papers in this volume show, people, theories, methods and data from a wide number of disciplines including computer science, psychology, sociology, communication science, public health, bioinformatics, political science, and organizational science. Numerous types of computational methods are used include, but not limited to, machine learning, language technology, social network analysis and visualization, agent-based simulation, and statistics.
Social, Cultural, and Behavioral Modeling
This book constitutes the refereed proceedings of the 9th International Conference on Social, Cultural, and Behavioral Modeling & Prediction and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2016, held in Washington, DC, USA, in June/July 2016. The 38 full papers presented were carefully reviewed and selected from 78 submissions. The goal of this conference was to build a new community of social cyber scholars by bringing together and fostering interaction between members of the scientific, corporate, government and military communities interested in understanding, forecasting and impacting human socio-cultural behavior. For this three challenges have to be met: deep understanding, socio-cognitive reasoning, and re-usable computational technology. Thus papers come from a wide number of disciplines: computer science, psychology, sociology, communication science, public health, bioinformatics, political science, and organizational science.
Introduction to Semi-Supervised Learning
Semi-supervised learning is a learning paradigm concerned with the study of how computers and natural systems such as humans learn in the presence of both labeled and unlabeled data. Traditionally, learning has been studied either in the unsupervised paradigm (e.g., clustering, outlier detection) where all the data are unlabeled, or in the supervised paradigm (e.g., classification, regression) where all the data are labeled. The goal of semi-supervised learning is to understand how combining labeled and unlabeled data may change the learning behavior, and design algorithms that take advantage of such a combination. Semi-supervised learning is of great interest in machine learning and data mi...
Machine Intelligence and Signal Analysis
The book covers the most recent developments in machine learning, signal analysis, and their applications. It covers the topics of machine intelligence such as: deep learning, soft computing approaches, support vector machines (SVMs), least square SVMs (LSSVMs) and their variants; and covers the topics of signal analysis such as: biomedical signals including electroencephalogram (EEG), magnetoencephalography (MEG), electrocardiogram (ECG) and electromyogram (EMG) as well as other signals such as speech signals, communication signals, vibration signals, image, and video. Further, it analyzes normal and abnormal categories of real-world signals, for example normal and epileptic EEG signals using numerous classification techniques. The book is envisioned for researchers and graduate students in Computer Science and Engineering, Electrical Engineering, Applied Mathematics, and Biomedical Signal Processing.
Social Computing, Behavioral-Cultural Modeling, and Prediction
This book constitutes the refereed proceedings of the 8th International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction, SBP 2015, held in Washington, DC, USA, in March/April 2015. The 24 full papers presented together with 36 poster papers were carefully reviewed and selected from 118 submissions. The goal of the conference was to advance our understanding of human behavior through the development and application of mathematical, computational, statistical, simulation, predictive and other models that provide fundamental insights into factors contributing to human socio-cultural dynamics. The topical areas addressed by the papers are social and behavioral sciences, health sciences, engineering, computer and information science.
Advances in Knowledge Discovery and Data Mining
This book constitutes the refereed proceedings of the 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2009, held in Bangkok, Thailand, in April 2009. The 39 revised full papers and 73 revised short papers presented together with 3 keynote talks were carefully reviewed and selected from 338 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD-related areas including data mining, data warehousing, machine learning, databases, statistics, knowledge acquisition, automatic scientific discovery, data visualization, causal induction, and knowledge-based systems.
