الصفحة 1
الصفحة 1
Nonblocking Supervisory Control of State Tree Structures
This monograph proposes how to manage complexity by organizing the system as a State Tree Structure (STS). an efficient recursive symbolic algorithm is presented that can perform nonblocking supervisory control design in reasonable time and memory for complex systems.
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.
Modern deep learning for tabular data : Novel approaches to common modeling problems
Synthesizes and presents novel deep learning approaches to a seemingly unlikely domain - tabular data. Whether for finance, business, security, medicine, or countless other domain, deep learning can help mine and model complex patterns in tabular data - an incredibly ubiquitous form of structured data. Part I of the book offers a rigorous overview of machine learning principles, algorithms, and implementation skills relevant to holistically modeling and manipulating tabular data. Part II studies five dominant deep learning model designs - Artificial Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Attention and Transformers, and Tree-Rooted Networks - through both their 'default' usage and their application to tabular data. Part III compounds the power of the previously covered methods by surveying strategies and techniques to supercharge deep learning systems: autoencoders, deep data generation, meta-optimization, multi-model arrangement, and neural network interpretability.
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2005 ; 8th International Conference, Palm Springs, CA, USA, October 26-29, 2005, Proceedings, Part I
This paper presents a method for classification of medical images, using machine learning and deformation-based morphometry. A morphological representation of the anatomy of interest is first obtained using highdimensional template warping, from which regions that display strong correlations between morphological measurements and the classification (clinical) variable are extracted using a watershed segmentation, taking into account the regional smoothness of the correlation map which is estimated by a crossvalidation strategy in order to achieve robustness to outliers. A Support Vector Machine-Recursive Feature Elimination (SVM-RFE) technique is then used to rank computed features from the extracted regions, according to their effect on the leave-one-out error bound. Finally, SVM classification is applied using the best set of features, and it is tested using leave-one-out. The results from a group of 61 brain images of female normal controls and schizophrenia patients demonstrate not only high classification accuracy (91.8%) and steep ROC curves, but also exceptional stability with respect to the number of selected features and the SVM kernel size
Introduction to Machine Learning with Applications in Information Security
Provides a classroom-tested introduction to a wide variety of machine learning and deep learning algorithms and techniques, reinforced via realistic applications. The book is accessible and doesn't prove theorems, or dwell on mathematical theory. The goal is to present topics at an intuitive level, with just enough detail to clarify the underlying concepts. The book covers core classic machine learning topics in depth, including Hidden Markov Models (HMM), Support Vector Machines (SVM), and clustering. Additional machine learning topics include k-Nearest Neighbor (k-NN), boosting, Random Forests, and Linear Discriminant Analysis (LDA). The fundamental deep learning topics of backpropagation, Convolutional Neural Networks (CNN), Multilayer Perceptrons (MLP), and Recurrent Neural Networks (RNN) are covered in depth. A broad range of advanced deep learning architectures are also presented, including Long Short-Term Memory (LSTM), Generative Adversarial Networks (GAN), Extreme Learning Machines (ELM), Residual Networks (ResNet), Deep Belief Networks (DBN), Bidirectional Encoder Representations from Transformers (BERT), and Word2Vec.
Information theory and machine learning
The recent successes of machine learning, especially regarding systems based on deep neural networks, have encouraged further research activities and raised a new set of challenges in understanding and designing complex machine learning algorithms. New applications require learning algorithms to be distributed, have transferable learning results, use computation resources efficiently, convergence quickly on online settings, have performance guarantees, satisfy fairness or privacy constraints, incorporate domain knowledge on model structures, etc. A new wave of developments in statistical learning theory and information theory has set out to address these challenges.
Inductive logic programming ; 15th International Conference, ILP 2005, Bonn, Germany, August 10-13, 2005, Proceedings
“Change is inevitable.” Embracing this quote we have tried to carefully exp- iment with the format of this conference, the 15th International Conference on Inductive Logic Programming, hopefully making it even better than it already was. But it will be up to you, the inquisitive reader of this book, to judge our success. The major changes comprised broadening the scope of the conference to include more diverse forms of non-propositional learning, to once again have tutorials on exciting new areas, and, for the ?rst time, to also have a discovery challenge as a platform for collaborative work. This year the conference was co-located with ICML 2005, the 22nd Inter- tional Conference on Machine Learning, and also in close proximity to IJCAI 2005, the 19th International Joint Conference on Arti?cial Intelligence. - location can be tricky, but we greatly bene?ted from the local support provided by Codrina Lauth, Michael May, and others. We were also able to invite all ILP and ICML participants to shared events including a poster session, an invited talk, and a tutorial about the exciting new area of “statistical relational lea- ing”. Two more invited talks were exclusively given to ILP participants and were presented as a kind of stock-taking—?ttingly so for the 15th event in a series—but also tried to provide a recipe for future endeavours.
Implementation and Applications of Automata ; 13th International Conference, CIAA 2008, San Francisco, California, USA, July 21-24, 2008. Proceedings
This book constitutes the thoroughly refereed post-proceedings of the 13th International Conference on Implementation and Application of Automata, CIAA 2008, held in San Francisco, USA, in July 2008.The 26 revised full papers togehter with 4 invited papers were carefully reviewed and selected from 40 submissions and have gone through two rounds of reviewing and improvement. The papers cover various topics in the theory, implementation, and applications of automata and related structures.
Hypercomputation : Computing Beyond the Church-Turing Barrier
Hypercomputation is a relatively new theory of computation which treats computing methods and devices that transcend the Church-Turing thesis. This book will provide a thorough description of the field of hypercomputation, covering all attempts at devising conceptual hypermachines and all new promising computational paradigms that may eventually lead to the construction of a hypermachine.Readers will reach a deeper understanding of what computability is and why the Church-Turing thesis poses an arbitrary limit to what actually can be computed. Hypercomputing is quite a novel idea, and therefore the book is interesting to the reader in its own right.
Hands-on question answering systems with BERT : Applications in neural networks and natural language processing
Begins with an overview of the technology landscape behind BERT. It takes you through the basics of NLP, including natural language understanding with tokenization, stemming, and lemmatization, and bag of words. Next, you’ll look at neural networks for NLP starting with its variants such as recurrent neural networks, encoders and decoders, bi-directional encoders and decoders, and transformer models. Along the way, you’ll cover word embedding and their types along with the basics of BERT. After this solid foundation, you’ll be ready to take a deep dive into BERT algorithms such as masked language models and next sentence prediction. You’ll see different BERT variations followed by a hands-on example of a question answering system. You will: Examine the fundamentals of word embeddings / Apply neural networks and BERT for various NLP tasks / Develop a question-answering system from scratch / Train question-answering systems for your own data
Event-Based Programming : Taking Events to the Limit
This book teaches you how to develop software based on parts that interact primarily through an event mechanism. You'll learn how to use events in many different situations, to solve recurring development problems without coupling. The book introduces Signal Wiring Diagram, a novel form of software diagram similar to the circuit diagrams used by hardware designers. The book concludes with a series of case studies, incorporating all featured concepts.
Discrete Mathematics Using a Computer
Discrete Mathematics Using a Computer offers a new, "hands-on" approach to teaching Discrete Mathematics. Using software that is freely available on Mac, PC and Unix platforms, the functional language Haskell allows students to experiment with mathematical notations and concepts -- a practical approach that provides students with instant feedback and allows lecturers to monitor progress easily.
Digital self-tuning controllers : Algorithms, implementation and applications
Digital Self-tuning Controllers presents you with a complete course in self-tuning control, beginning with a survey of adaptive control and the formulation of adaptive control problems. Modelling and identification are dealt with before passing on to algebraic design methods and particular PID and linear-quadratic forms of self-tuning control. Finally, laboratory verification and experimentation will show you how to ground your theoretical knowledge in real plant control.
Deep learning methods for converting speech to text = تقنيات التعلم العميق في تحويل الصوت إلى نص
Aims to design and develop a system capable of extracting audio content from films and audio recordings and converting it into text using deep learning techniques. This is done by analyzing audio patterns, extracting sounds and words from the video, and then converting them into written text. Deep learning, a branch of artificial intelligence, is used to accomplish this task. The study also includes comparing different deep learning techniques to determine their effectiveness in this context.
Data science for economics and finance : Methodologies and applications
The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis.
Logic and Theory of Algorithms ; 4th Conference on Computability in Europe, CiE 2008, Athens, Greece, June 15-20, 2008 Proceedings
Constitutes the refereed proceedings of the 4th International Conference on Computability in Europe, CiE 2008, held in Athens, Greece, in June 2008.The 36 revised full papers presented together with 25 invited tutorials and lectures were carefully reviewed and selected from 108 submissions. Among them are papers of 6 special sessions entitled algorithms in the history of mathematics, formalising mathematics and extracting algorithms from proofs, higher-type recursion and applications, algorithmic game theory, quantum algorithms and complexity, and biology and computation.
Java Challenges 100+ : Proven Tasks that Will Prepare You for Anything
Expand your knowledge of Java with this entertaining learning guide, which features 100+ exercises and programming challenges. Java Challenges will prepare you for your next exam or job interview, and covers many practical topics, such as strings, arrays, data structures, recursion, and date and time. The APIs and other material included in this book are Java 17 compatible. You will: Improve your Java knowledge by solving enjoyable but challenging programming puzzles / Solve mathematical problems, recursions, strings, arrays and more / Manage data processing and data structures like lists, sets, maps / Handle advanced recursion as well as binary trees, sorting and searching / Gamify key fundamentals for fun and easier reinforcement
Java : how to program. Late objects : Introducing Jshell
Introduction to Computers, the Internet and Java / Introduction to Java Applications; Input/Output and Operators / Control Statements: Part 1; Assignment, ++ and Operators / Control Statements: Part 2; Logical Operators / Methods / Arrays and ArrayLists / Introduction to Classes and Objects / Classes and Objects: A Deeper Look / Object-Oriented Programming: Inheritance / Object-Oriented Programming: Polymorphism and Interfaces / Exception Handling: A Deeper Look / JavaFX Graphical User Interfaces / JavaFX GUI / Strings, Characters and Regular Expressions / Files, Input/Output Streams, NIO and XML Serialization / Generic Collections / Lambdas and Streams / Recursion / Searching, Sorting and Big O / Generic Classes and Methods: A Deeper Look / Custom Generic Data Structures / JavaFX Graphics and Multimedia / Concurrency / Accessing Databases with JDBC / Introduction to JShell: Java 9's REPL for Interactive Java
Comprehensive mathematics for computer scientists 2 : Calculus and ODEs, splines, probability, fourier and wavelet theory, fractals and neural networks, categories and lambda calculus
This second volume of a comprehensive tour through mathematical core subjects for computer scientists completes the first volume in two - gards: Part III first adds topology, di?erential, and integral calculus to the t- ics of sets, graphs, algebra, formal logic, machines, and linear geometry, of volume 1. With this spectrum of fundamentals in mathematical e- cation, young professionals should be able to successfully attack more involved subjects, which may be relevant to the computational sciences. In a second regard, the end of part III and part IV add a selection of more advanced topics. In view of the overwhelming variety of mathematical approaches in the computational sciences, any selection, even the most empirical, requires a methodological justi?cation. Our primary criterion has been the search for harmonization and optimization of thematic - versity and logical coherence. This is why we have, for instance, bundled such seemingly distant subjects as recursive constructions, ordinary d- ferential equations, and fractals under the unifying perspective of c- traction theory.
Communications and Multimedia Security ; Vol.4237 ; 10th IFIP TC-6 TC 11 International Conference, CMS 2006, Heraklion Crete, Greece, October 19-21, 2006, Proceedings
Scientists, managers, and politicians all over the world havedesignedandarecurrently implementing systematicapproachesto network and information security, most of which are underlined by the principle: there is much more room for improvement and research. Along the lines of encouraging and catalyzing research in the area of c- munications and multimedia security, it is our great pleasure to present the proceedings of the 10th IFIP TC-6 TC-11 Conference on Communications and MultimediaSecurity(CMS2006), we sought a balanced program containing presentations on various aspects of secure c- munication and multimedia systems.
