Event selection criteria were developed using novel Machine Learning techniques to target ttH... Læs mere
This book provides its readers with an introduction to interesting prediction and science dynamics problems in the field of Science of Science.
The discovery in 2012 of the Higgs boson at the Large Hadron Collider (LHC) represents a milestone for the Standard Model (SM) of particle physics.
This book provides tools and algorithms for solving a wide class of optimization tasks by learning from their repetitions. A... Læs mere
This book offers a clear understanding of the concept of context-aware machine learning including an automated rule-based framework within the broad area of data science and analytics, particularly, with the aim of data-driven intelligent decision making.
The comparison and analysis between the three types of methods are given to help readers have a deeper... Læs mere
It covers a wide range of methods and technologies, including deep neural networks, large scale neural models, brain computer interface, signal processing methods, as well as models of perception, studies on emotion recognition, self-organization and many more.
This book constitutes the refereed post-conference proceedings of the... Læs mere
The ubiquitous challenge of learning and decision-making from rank data arises in situations where intelligent systems collect preference and behavior data from humans, learn from the data, and then use the data to help humans make efficient, effective, and timely decisions.
Graphical models (e.g., Bayesian and constraint networks, influence diagrams, and Markov decision processes) have become a central paradigm for knowledge representation and reasoning in both artificial intelligence and computer science in general.