Welcome to our book review site go-pdf.online!
You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
Decision Making Under Uncertainty and Reinforcement Learning
This book presents recent research in decision making under uncertainty, in particular reinforcement learning and learning with expert advice. The core elements of decision theory, Markov decision processes and reinforcement learning have not been previously collected in a concise volume. Our aim with this book was to provide a solid theoretical foundation with elementary proofs of the most important theorems in the field, all collected in one place, and not typically found in introductory textbooks. This book is addressed to graduate students that are interested in statistical decision making under uncertainty and the foundations of reinforcement learning.
Privacy and Security Issues in Data Mining and Machine Learning
This book constitutes the refereed proceedings of the International ECML/PKDD Workshop on Privacy and Security Issues in Data Mining and Machine Learning, PSDML 2010, held in Barcelona, Spain, in September 2010. The 11 revised full papers presented were carefully reviewed and selected from 21 submissions. The papers range from data privacy to security applications, focusing on detecting malicious behavior in computer systems.
Interactive Collaborative Information Systems
The increasing complexity of our world demands new perspectives on the role of technology in human decision making. We need new technology to cope with the increasingly complex and information-rich nature of our modern society. This is particularly true for critical environments such as crisis management and traffic management, where humans need to engage in close collaborations with artificial systems to observe and understand the situation and respond in a sensible way. The book Interactive Collaborative Information Systems addresses techniques that support humans in situations in which complex information handling is required and that facilitate distributed decision-making. The theme inte...
Foundations of Information and Knowledge Systems
An ideal text for researchers and professionals alike, this book constitutes the refereed proceedings of the 5th International Symposium on Foundations of Information and Knowledge Systems, FoIKS 2008 held in Pisa, Italy, in February 2008. The 13 revised full papers are presented together with nine revised short papers and three invited lectures. All of these were carefully selected during two rounds of reviewing and improvement from a total of 79 submissions.
Recent Advances in Reinforcement Learning
This book constitutes revised and selected papers of the 9th European Workshop on Reinforcement Learning, EWRL 2011, which took place in Athens, Greece in September 2011. The papers presented were carefully reviewed and selected from 40 submissions. The papers are organized in topical sections online reinforcement learning, learning and exploring MDPs, function approximation methods for reinforcement learning, macro-actions in reinforcement learning, policy search and bounds, multi-task and transfer reinforcement learning, multi-agent reinforcement learning, apprenticeship and inverse reinforcement learning and real-world reinforcement learning.
Artificial Neural Networks - ICANN 2006
The two-volume set LNCS 4131 and LNCS 4132 constitutes the refereed proceedings of the 16th International Conference on Artificial Neural Networks, ICANN 2006. The set presents 208 revised full papers, carefully reviewed and selected from 475 submissions. This first volume presents 103 papers, organized in topical sections on feature selection and dimension reduction for regression, learning algorithms, advances in neural network learning methods, ensemble learning, hybrid architectures, and more.
Computational and Robotic Models of the Hierarchical Organization of Behavior
Current robots and other artificial systems are typically able to accomplish only one single task. Overcoming this limitation requires the development of control architectures and learning algorithms that can support the acquisition and deployment of several different skills, which in turn seems to require a modular and hierarchical organization. In this way, different modules can acquire different skills without catastrophic interference, and higher-level components of the system can solve complex tasks by exploiting the skills encapsulated in the lower-level modules. While machine learning and robotics recognize the fundamental importance of the hierarchical organization of behavior for bu...
Security in Computing and Communications
This book constitutes the refereed proceedings of the International Symposium on Security in Computing and Communications, SSCC 2013, held in Mysore, India, in August 2013. The 24 revised full papers presented together with 15 poster papers were carefully reviewed and selected from 111 submissions. The papers cover all aspects of secure computing and communication in networking and distributed systems such as cloud-based data centers.
Proceedings of the 3rd European Conference on Computer Network Defense
The European Conference on Computer and Network Defense draws contributions and participation both from academia and industry, and addresses security from multiple perspectives, including state-of-the-art research in computer network security, intrusion detection, denial-of-service, privacy protection, security policies, and incident response & management. The conference is organized jointly by the Institute of Computer Science of the Foundation for Research and Technology – Hellas (FORTH) and the European Network and Information Security Agency (ENISA).
Machine Learning and Knowledge Discovery in Databases, Part III
This three-volume set LNAI 6911, LNAI 6912, and LNAI 6913 constitutes the refereed proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2011, held in Athens, Greece, in September 2011. The 121 revised full papers presented together with 10 invited talks and 11 demos in the three volumes, were carefully reviewed and selected from about 600 paper submissions. The papers address all areas related to machine learning and knowledge discovery in databases as well as other innovative application domains such as supervised and unsupervised learning with some innovative contributions in fundamental issues; dimensionality reduction, distance and similarity learning, model learning and matrix/tensor analysis; graph mining, graphical models, hidden markov models, kernel methods, active and ensemble learning, semi-supervised and transductive learning, mining sparse representations, model learning, inductive logic programming, and statistical learning. a significant part of the papers covers novel and timely applications of data mining and machine learning in industrial domains.
