Diagnosis-related groups (DRGs) are used in hospitals for the reimbursement of inpatient services. The assignment of a patient to a DRG can be distinguished into billing- and operations-driven DRG cla
This book constitutes the refereed proceedings of the First International Conference on Advanced Machine Learning Technologies and Applications, AMLTA 2012, held in Cairo, Egypt, in December 2012.The
Rubinstein is the pioneer of the well-known score function and cross-entropy methods.Accessible to a broad audience of engineers, computer scientists, mathematicians, statisticians and in general anyo
This book develops two key machine learning principles: the semi-supervised paradigm and learning with interdependent data. It reveals new applications, primarily web related, that transgress the clas
This three-volume set LNAI 8724, 8725 and 8726 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2014, held in Nancy,
This three-volume set LNAI 8724, 8725 and 8726 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2014, held in Nancy,
This three-volume set LNAI 8724, 8725 and 8726 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2014, held in Nancy,
This Springer Brief examines the combination of computer vision techniques and machine learning algorithms necessary for humanoid robots to develop “true consciousness.” It illustrates the critical fi
This three-volume set LNAI 8188, 8189 and 8190 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2013, held in Prague,
This three-volume set LNAI 8188, 8189 and 8190 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2013, held in Prague,
This three-volume set LNAI 8188, 8189 and 8190 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2013, held in Prague,
This book constitutes the refereed proceedings of the 11th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2013, held in Vienna, Austria, in
This book constitutes the refereed proceedings of the Third International Workshop on Machine Learning in Medical Imaging, MLMI 2012, held in conjunction with MICCAI 2012, in Nice, France, in October
This two-volume set LNAI 7523 and LNAI 7524 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2012, held in Bristol, U
This book constitutes the refereed proceedings of the 4th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2005, held in Leipzig, Germany, in July 2005.The 68
This carefully edited book brings together a fascinating selection of applications of Learning Classifier Systems (LCS). The book demonstrates the utility of this machine learning technique in recent
Efficient Learning Machines explores all the major topics of machine learning, including big data, knowledge discovery, classifications, genetic algorithms, neural networking, kernel methods, and gami
Accurate fluid level measurement in dynamic environments can be assessed using a Support Vector Machine (SVM) approach. SVM is a supervised learning model that analyzes and recognizes patterns. It is
Remarkable advances in computation and data storage and the ready availability of huge data sets have been the keys to the growth of the new disciplines of data mining and machine learning, while the
A detailed examination of learning classifier systems (LCS), a form of machine learning system, which incorporates both Evolutionary Algorithms and Reinforcement Learning Algorithms.
Accelerated Path to Cures provides a transformative perspective on the power of combining advanced computational technologies, modeling, bioinformatics and machine learning approaches with nonclinical
This book is intended for use in advanced graduate courses in statistics / machine learning, as well as for all experimental neuroscientists seeking to understand statistical methods at a deeper level
Learn the fundamental aspects of the business statistics, data mining, and machine learning techniques required to understand the huge amount of data generated by your organization. This book explains
This book covers aspects of human re-identification problems related to computer vision and machine learning. Working from a practical perspective, it introduces novel algorithms and designs for human
This book lays out a path leading from the linguistic and cognitive basics, to classical rule-based and machine learning algorithms, to today’s state-of-the-art approaches, which use advanced empirica
This textbook provides concise coverage of the basics of linear and integer programming which, with megatrends toward optimization, machine learning, big data, etc., are becoming fundamental toolkits
This text presents a wide-ranging and rigorous overview of nearest neighbor methods, one of the most important paradigms in machine learning. Now in one self-contained volume, this book systematically
The ideas introduced in this book explore the relationships among rule based systems, machine learning and big data. Rule based systems are seen as a special type of expert systems, which can be built
This successful textbook on predictive text mining offers a unified perspective on a rapidly evolving field, integrating topics spanning the varied disciplines of data science, machine learning, datab
Practical Graph Analytics with Apache Giraph helps you build data mining and machine learning applications using the Apache Foundation’s Giraph framework for graph processing. This is the same framewo
This book proposes a novel approach for time-series prediction using machine learning techniques with automatic feature generation. Application of machine learning techniques to predict time-series co
This book explores multimedia applications that emerged from computer vision and machine learning technologies. These state-of-the-art applications include MPEG-7, interactive multimedia retrieval, mu
This book describes the basic principles underlying the generation, coding, transmission and enhancement of speech and audio signals, including advanced statistical and machine learning techniques for
This work combines interdisciplinary knowledge and experience from research fields of psychology, linguistics, audio-processing, machine learning, and computer science. The work systematically explore
This SpringerBrief reveals the latest techniques in computer vision and machine learning on robots that are designed as accurate and efficient military snipers. Militaries around the world are investi
Graph Embedding for Pattern Recognition covers theory methods, computation, and applications widely used in statistics, machine learning, image processing, and computer vision. This book presents the
Data mining, an interdisciplinary field combining methods from artificial intelligence, machine learning, statistics and database systems, has grown tremendously over the last 20 years and produced co
Reactive Search integrates sub-symbolic machine learning techniques into search heuristics for solving complex optimization problems. By automatically adjusting the working parameters, a reactive sea
Assembled in this volume is a collection of some of the state-of-the-art methods that are using computer vision and machine learning techniques as applied in robotic applications. Currently there is a
When it comes to robotics and bioinformatics, the Holy Grail everyone is seeking is how to dovetail logic-based inference and statistical machine learning. This volume offers some possible solutions t
