الصفحة 2
الصفحة 2
Neural networks and deep learning
Covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts of neural architectures in different applications. Why do neural networks work? When do they work better than off-the-shelf machine-learning models? When is depth useful? Why is training neural networks so hard? What are the pitfalls? The book is also rich in discussing different applications in order to give the practitioner a flavor of how neural architectures are designed for different types of problems.
Neural Nets ; 16th Italian Workshop on Neural Nets, WIRN 2005, International workshop on natural and artificial immune systems, NAIS 2005, Vietri sul Mare, Italy, June 8-11, 2005, Revised Selected Papers
This book constitutes the thoroughly refereed postproceedings of the 16th Italian Workshop on Neural Nets, WIRN 2005, as well as the satellite International Workshop on Natural and Artificial Immune Systems, NAIS 2005, held in Vietri sul Mare, Italy in June 2005. The 41 revised papers presented together with a lecture by the winner of the Premio Caianiello award were carefully reviewed and improved during two rounds of selection and refereeing.
NETWORKING 2008 Ad Hoc and Sensor Networks, Wireless Networks, Next Generation Internet ; 7th International IFIP-TC6 Networking Conference Singapore, May 5-9, 2008 Proceedings
The 82 revised full papers were carefully reviewed and selected from numerous submissions for inclusion in the book. The papers are organized in topical sections on ad hoc and sensor networks: design and optimization, MAC protocol, overlay networking, and routing; next generation internet: authentication, modeling and performance evaluation, multicast, network measurement and testbed, optical networks, peer-to-peer and overlay networking, peer-to-peer services, QoS, routing, security, traffic engineering, and transport protocols; wireless networks: MAC performance, mesh networks, and mixed networks.
Network Classification For Traffic Management : Anomaly detection, feature selection, clustering and classification
Investigates network traffic classification solutions by proposing transport-layer methods to achieve better run and operated enterprise-scale networks. With the massive increase of data and traffic on the Internet within the 5G, IoT and smart cities frameworks, current network classification and analysis techniques are falling short. Novel approaches using machine learning algorithms are needed to cope with and manage real-world network traffic, including supervised, semi-supervised, and unsupervised classification techniques. Accurate and effective classification of network traffic will lead to better quality of service and more secure and manageable networks. Investigates network traffic classification solutions by proposing transport-layer methods to achieve better run and operated enterprise-scale networks. The authors explore novel methods for enhancing network statistics at the transport layer, helping to identify optimal feature selection through a global optimization approach and providing automatic labelling for raw traffic through a SemTra framework to maintain provable privacy on information disclosure properties.
Natural Language Processing and Information Systems ; Vol. 3513 ; 10th International Conference on Applications of Natural Language to Information Systems, NLDB 2005, Alicante, Spain, June 15-17, Proceedings
The development and convergence of computing, telecommunications and information systems has already led to a revolution in the way that we work, communicate with each other, buy goods and use services, and even in the way that we entertain and educate ourselves.The revolution continues, and one of its results is that large volumes of information will increasingly be held in a form which is more natural for users than the data presentation formats typical of computer systems of the past. Natural language processing (NLP) is crucial in solving these problems, and language technologies will make an indispensable contribution to the success of information systems. We hope that NLDB 2005 was a modest contribution to this goal. NLDB 2005 contributed to advancing the goals and the high international standing of these conferences, largely due to its Program Committee, composed of renowned researchers in the field of natural language processing and inf- mation system engineering. Papers were reviewed by three reviewers from the Program Committee. This clearly contributed to the significant number of - pers submitted (95). Twenty-nine were accepted as regular papers, while 18 were accepted as short papers.
Natural language processing and information systems ; 12th International Conference on Applications of Natural Language to Information Systems, NLDB 2007, Paris, France, June 27-29, 2007, Proceedings
NLP techniques may substantially enhance most phases of the information system lifecycle, starting with requirement analysis, specification and validation, and going up to conflict resolution, result processing and presentation.
Natural Language Processing and Chinese Computing ; 9th CCF International Conference, NLPCC 2020, Zhengzhou, China, October 14–18, 2020, Proceedings, Part II
This two-volume set of LNAI 12340 and LNAI 12341 constitutes the refereed proceedings of the 9th CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2020, held in Zhengzhou, China, in October 2020. The 70 full papers, 30 poster papers and 14 workshop papers presented were carefully reviewed and selected from 320 submissions. They are organized in the following areas: Conversational Bot/QA; Fundamentals of NLP; Knowledge Base, Graphs and Semantic Web; Machine Learning for NLP; Machine Translation and Multilinguality; NLP Applications; Social Media and Network; Text Mining; and Trending Topics.
Natural language processing and chinese computing ; 9th CCF International conference, NLPCC 2020, Zhengzhou, China, October 14–18, 2020, Proceedings, Part I
This two-volume set of LNAI 12340 and LNAI 12341 constitutes the refereed proceedings of the 9th CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2020, held in Zhengzhou, China, in October 2020. The 70 full papers, 30 poster papers and 14 workshop papers presented were carefully reviewed and selected from 320 submissions. They are organized in the following areas: Conversational Bot/QA; Fundamentals of NLP; Knowledge Base, Graphs and Semantic Web; Machine Learning for NLP; Machine Translation and Multilinguality; NLP Applications; Social Media and Network; Text Mining; and Trending Topics.
Natural Language Processing – IJCNLP 2005 ; 2nd International Joint Conference, Jeju Island, Korea, October 11-13, 2005, Proceedings
The Theme of IJCNLP 2005: “NLP with Kimchee”, a Conference with a Unique Flavor Welcometo IJCNLP 2005,thesecondannualconferenceof theAsian Federation ofNaturalLanguageProcessing(AFNLP). Followingthesuccessofthe?rstc- ference held in the beautiful cityof Sanya,Hainan Island,China, in March2004, IJCNLP 2005 is held in yet another attractive Asian resort, namely Jeju Island in Korea, on October 11–13, 2005
Natural Language Processing – IJCNLP 2004 ; 1st International Joint Conference, Hainan Island, China, March 22-24, 2004, Revised Selected Papers
This book constitutes the thoroughly refereed post-proceedings of the First International Joint Conference on Natural Language Processing, IJCNLP 2004, held in Hainan Island, China in March 2004. The 84 revised full papers presented in this volume were carefully selected during two rounds of reviewing and improvement from 211 papers submitted. The papers are organized in topical sections on dialogue and discourse; FSA and parsing algorithms; information extractions and question answering; information retrieval; lexical semantics, ontologies, and linguistic resources; machine translation and multilinguality; NLP software and applications, semantic disambiguities; statistical models and machine learning; taggers, chunkers, and shallow parsers; text and sentence generation; text mining; theories and formalisms for morphology, syntax, and semantics; word segmentation; NLP in mobile information retrieval and user interfaces; and text mining in bioinformatics.
Nanoinformatics
Brings out the state of the art on how informatics-based tools are used and expected to be used in nanomaterials research. There has been great progress in the area in which “big-data” generated by experiments or computations are fully utilized to accelerate discovery of new materials, key factors, and design rules. Data-intensive approaches play indispensable roles in advanced materials characterization. "Materials informatics" is the central paradigm in the new trend. "Nanoinformatics" is its essential subset, which focuses on nanostructures of materials such as surfaces, interfaces, dopants, and point defects, playing a critical role in determining materials properties. There have been significant advances in experimental and computational techniques to characterize individual atoms in nanostructures and to gain quantitative information. The collaboration of researchers in materials science and information science is growing actively and is creating a new trend in materials science and engineering.
Multiscaling in molecular and continuum mechanics : Interaction of time and size from macro to nano ; Application to biology, physics, material science, mechanics, structural and processing engineering
The manipulation of molecules and atoms has been regarded as a common base for both material and life science. Quantum and continuum mechanics are being applied side by side for exploring the behavior of small and large objects moving at fast and slow speed.
Multiple-Aspect Analysis of Semantic Trajectories ; First International Workshop, MASTER 2019, Held in Conjunction with ECML-PKDD 2019, Würzburg, Germany, September 16, 2019, Proceedings
This book constitutes the refereed post-conference proceedings of the First International Workshop on Multiple-Aspect Analysis of Semantic Trajectories, MASTER 2019, held in conjunction with the 19th European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2019, in Würzburg, Germany, in September 2019.
Multiple Classifier Systems ; 7th International Workshop, MCS 2007, Prague, Czech Republic, May 23-25, 2007, Proceedings
These proceedings are a record of the Multiple Classifier Systems Workshop, MCS 2007, held at the Institute of Information Theory and Automation, Czech Academy of Sciences, Prague in May 2007. the workshop achieved its objective of bringing together researchers from diverse communities (neural networks, pattern rec- nition, machine learning and statistics) concerned with this research topic.
Multiple Classifier Systems ; 6th International Workshop, MCS 2005, Seaside, CA, USA, June 13-15, 2005, Proceedings
Constitutes the refereed proceedings of the 6th International Workshop on Multiple Classifier Systems, MCS 2005. This book contains papers that are organized in topical sections on boosting, combination methods, performance analysis, and applications. They exemplify the advances in the theory and applications of multiple classifier systems
Multiple Classifier Systems ; 2nd International Workshop, MCS 2001 Cambridge, UK, July 2-4, 2001 Proceedings
Driven by the requirements of a large number of practical and commercially - portant applications, the last decade has witnessed considerable advances in p- tern recognition. Better understanding of the design issues and new paradigms, such as the Support Vector Machine, have contributed to the development of - proved methods of pattern classi cation. However, while any performance gains are welcome, and often extremely signi cant from the practical point of view, it is increasingly more challenging to reach the point of perfection as de ned by the theoretical optimality of decision making in a given decision framework. The asymptoticity of gains that can be made for a single classi er is a re?- tion of the fact that any particular design, regardless of how good it is, simply provides just one estimate of the optimal decision rule.
Multiobjective Problem Solving from Nature : From Concepts to Applications
he book focuses on how MOEAs and related techniques can be used to solve problems, particularly in the disciplines of science and engineering. Contributions by leading researchers show how the concepts of multiobjective optimization can be used to reformulate and resolve problems in broad areas such as constrained optimization, coevolution, classification, inverse modelling and design. The book is distinguished from other texts on MOEAs in that it is not primarily about the algorithms, nor specific applications, but about the concepts and processes involved in solving problems using a multiobjective approach. Each chapter contributes to the central, deep concepts and themes of the book: evaluating the utility of the multiobjective approach; discussing alternative problem formulations; showing how problem formulation affects the search process; and examining solution selection and decision making.
Multimedia technology and enhanced learning ; 2nd EAI International conference, ICMTEL 2020, Leicester, UK, April 10-11, 2020, Proceedings, Part II
This two-volume book constitutes the refereed proceedings of the Second International Conference on Multimedia Technology and Enhanced Learning, ICMTEL 2020, held in Leicester, United Kingdom, in April 2020. Due to the COVID-19 pandemic all papers were presented in YouTubeLive. The 83 revised full papers have been selected from 158 submissions. They describe new learning technologies which range from smart school, smart class and smart learning at home and which have been developed from new technologies such as machine learning, multimedia and Internet of Things.
Multimedia Technology and Enhanced Learning ; 2nd EAI International Conference, ICMTEL 2020, Leicester, UK, April 10-11, 2020, Proceedings, Part I
This two-volume book constitutes the refereed proceedings of the Second International Conference on Multimedia Technology and Enhanced Learning, ICMTEL 2020, held in Leicester, United Kingdom, in April 2020. Due to the COVID-19 pandemic all papers were presented in YouTubeLive. The 83 revised full papers have been selected from 158 submissions. They describe new learning technologies which range from smart school, smart class and smart learning at home and which have been developed from new technologies such as machine learning, multimedia and Internet of Things.
Multimedia Forensics
Media forensics has never been more relevant to societal life. Not only media content represents an ever-increasing share of the data traveling on the net and the preferred communications means for most users, it has also become integral part of most innovative applications in the digital information ecosystem that serves various sectors of society, from the entertainment, to journalism, to politics. Undoubtedly, the advances in deep learning and computational imaging contributed significantly to this outcome. The underlying technologies that drive this trend, however, also pose a profound challenge in establishing trust in what we see, hear, and read, and make media content the preferred target of malicious attacks.
