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View our offer Mathematics
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Gödel, Escher, Bach
This groundbreaking Pulitzer Prize-winning book sets the standard for interdisciplinary writing, exploring the patterns and symbols in the thinking of mathematician Kurt Godel, artist M.C. Escher, and composer Johann Sebastian Bach.
€ 24,50 -
Data Science, Classification, and Artificial Intelligence for Modeling Decision Making
Javier Trejos is a Full Professor and Researcher at the School of Mathematics and the Center for Research in Pure and Applied Mathematics (CIMPA), University of Costa Rica. His research focuses on the relations between data analysis and combinatorial optimization. He was the chief editor of the Journal of Mathematics: Theory and Applications and is the former president of the Central American and Caribbean Society for Classification and Data Analysis (SoCCCAD). In 1996 he was awarded the Simon Régnier Prize of the Francophone Classification Society. Theodore Chadjipandelis is Professor of Applied Statistics and the Director of the Laboratory of Applied Political Research, Aristotle University, Thessaloniki, Greece. His research interests are in the field of applied statistics and mainly focus on issues of experiment design, statistical research training, public opinion, political and electoral behavior, electoral geography, election systems as well as urban and regional programming and development. He coordinated the Greek section of the program C.C.S. (Comparative Candidates Survey) – a co-operation between 30 research teams – and of C.S.E.S. (Comparative Study of Electoral Systems). Currently he coordinates the Greek section of the program MeDem (Measuring Electoral Democracy) - a co-operation between 30 research teams - and of the Horizon project AI4GOV (Artificial Intelligence for Governance). Aurea Grané is Full Professor of Statistics and Operations Research at Universidad Carlos III de Madrid, Spain. Her work involves several lines of research whose common link is the development of non-parametric techniques based on distances with application to data of a certain complexity. She has important contributions in the development of goodness-of-fit statistics for uniformity, exponentiality and normality tests, in statistical methods based on distances for data visualization, in predictive methods for functional data and in the development of tools for outlier detection in long financial series and mixed data sets. Mario Villalobos is a Professor and Researcher at the University of Costa Rica, School of Mathematics, and the Center for Research in Pure and Applied Mathematics (CIMPA), of which he was its director until 2020, and a lecturer at the Costa Rica Institute of Technology. His research deals mainly with multi-objective optimization and its relationships with statistical and data analysis methods, the study of functions, teaching innovations in mathematics, and currently curve-fitting to see trends in epidemics. He was the recipient of the Chikio Hayashi Award from the International Federation of Classification Societies in 2006.
€ 180,50 -
Advanced Portfolio Optimization
A Cutting-edge Quantitative ApproachDany Cajas is the creator and sole maintainer of the Riskfolio-Lib portfolio optimization Python library, one of the most popular finance libraries worldwide with more than 3,100 stars on Github and more than 600k downloads. He has experience in financial planning, management control, quantitative financial risk management, pricing of financial derivative instruments and portfolio construction. He has teaching experience in Python programming for quantitative finance courses for students in North America, South America, Asia, and Europe through his company Orenji EIRL.
€ 124,95 -
Graph Neural Network for Hyperspectral Image Clustering
Multiple graph neural network-based clustering methods for hyperspectral images are proposed, effectively improving the clustering accuracy of hyperspectral images and taking an important step towards the practical application of hyperspectral images.
€ 180,50 -
Statistical Optimal Transport
École d'Été de Probabilités de Saint-Flour XLIX – 2019This monograph aims to offer a concise introduction to optimal transport, quickly transitioning to its applications in statistics and machine learning. As such, this monograph is suitable for a graduate course on the topic of statistical optimal transport.
€ 82,95 -
The Complete Beginner’s Guide to Using ChatGPT
Getting the Most Out of Generative AI as a Non-Techiemso-padding-alt: 31.0pt 31.0pt 31.0pt 31.0pt; margin: 0in 0in 0in .5in;">
€ 45,95 -
Exploring Nanostatistics
The Emerging Science of NanoscaleDr Fernando Gomes de Souza Junior is a distinguished scholar in materials science, renowned for his groundbreaking contributions to polymer nanocomposites, machine learning, and sustainable solutions. He earned his undergraduate degree in Chemistry from the Federal University of Espírito Santo, Brazil, in 1999, followed by a Master's in Materials Engineering and Science from the State University of Northern Rio de Janeiro, Brazil, in 2002. Motivated by a passion for interdisciplinary innovation, he completed his Ph.D. in Polymer Science and Technology at the Federal University of Rio de Janeiro (UFRJ), Brazil in 2006, and later a postdoctoral fellowship in Chemical Engineering with a focus on Data Analysis and Design of Experiments (DoE) at COPPE/UFRJ in 2008. Now a Full Professor at UFRJ, Fernando has been teaching Data Analysis and DoE since 2008 in UFRJ's postgraduate programs. He has published 236 peer-reviewed articles, authored 13 books, and received numerous accolades. Fernando's research bridges statistical methodologies and nanotechnology, aiming to unlock sustainable and transformative solutions across industries.
€ 105,50 -
Machine Learning Techniques to Predict Terrorist Attacks
Exemplified by Jama'at Nasr al-Islam wal MusliminLaura Mostert is an officer in the Royal Netherlands Air Force with a background in war studies and cyber security governance. Roy Lindelauf is the Chair Data Science in Military Operations at Faculty of Military Sciences at Netherlands Defence Academy and an Endowed Chair Data Science for Safety, Security at the Department of Cognitive Science & Artificial Intelligence at Tilburg School of Humanities and Digital Sciences. He is also Head of Data Science Center of Excellence at Netherlands Ministry of Defence. Chiara Pulice is a Senior Research Associate in computer science with Northwestern University, Evanston, IL, USA. Her research interests include counter-terrorism and machine learning. She received the Ph.D. degree in computer and systems engineering from the University of Calabria, Cosenza, Italy, in 2015. Marnix Provoost is an active duty officer in the Royal Netherlands Army. He holds a Master’s degree in Military Strategic Studies and is currently positioned at the Netherlands Defence Academy as a fulltime PhD student. His research is focused on insurgencies and their analogies with state formation. Priyanka Amin has recently finished her undergraduate degree in computer science and global history at Northwestern University. V.S. Subrahmanian is the Walter P. Murphy Professor of Computer Science and Buffett Faculty Fellow in the Buffett Institute for Global Affairs at Northwestern University where he also heads the Northwestern Security & AI Lab. He is one of the world’s foremost experts at the intersection of AI and Security matters ranging from counterterrorism to cybersecurity to border issues and warfare. An elected Fellow of AAAI and AAAS, he has previously served as Director of the Institute for Security, Technology, and Society at Dartmouth College and as Director of the University of Maryland Institute for Advanced Computer Studies.
€ 62,50 -
A Tutorial on Meta-Reinforcement Learning
€ 108,95 -
Computational Methods for Blade Icing Detection of Wind Turbines
This book thoroughly explores the realm of data-driven blade-icing detection for wind turbines, focusing on multivariate time series classification to enhance the reliability and efficiency of wind energy utilization.
€ 180,50 -
New Trends in Functional Statistics and Related Fields
A variety of features of statistics for functional data are addressed, such as estimation of functional features, exploration and pre-processing of functional data, methodologies for functional regression and forecasting problems, unsupervised and supervised classification, and testing procedures.
€ 221,95 -
Mean Field Guided Machine Learning
This book explores the integration of Mean Field Game (MFG) theory with machine learning (ML), presenting both theoretical foundations and practical applications.
€ 193,95