This book constitutes the refereed proceedings of the 38th Conference on Current Trends in Theory and Practice of computerscience, SOFSEM 2012, held in Špindlerův Mlýn, Czech Republic, in January 2012. The 43 re...
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ISBN:
(数字)9783642276606
ISBN:
(纸本)9783642276590
This book constitutes the refereed proceedings of the 38th Conference on Current Trends in Theory and Practice of computerscience, SOFSEM 2012, held in Špindlerův Mlýn, Czech Republic, in January 2012.
The 43 revised papers presented in this volume were carefully reviewed and selected from 121 submissions. The book also contains 11 invited talks, 10 of which are in full-paper length. The contributions are organized in topical sections named: foundations of computerscience; software and Web engineering; cryptography, security, and verification; and artificial intelligence.
This Festschrift volume is published in honor of Dexter Kozen on the occasion of his 60th birthday. Dexter Kozen has been a leader in the development of Kleene Algebras (KAs). The contributions in this volume reflect ...
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ISBN:
(数字)9783642294853
ISBN:
(纸本)9783642294846
This Festschrift volume is published in honor of Dexter Kozen on the occasion of his 60th birthday. Dexter Kozen has been a leader in the development of Kleene Algebras (KAs). The contributions in this volume reflect the breadth of his work and influence.
The volume includes 19 full papers related to Dexter Kozen's research. They deal with coalgebraic methods, congruence closure; the completeness of various programming logics; decision procedure for logics; alternation; algorithms and complexity; and programming languages and program analysis.
The second part of this volume includes laudatios from several collaborators, students and friends, including the members of his current band.
Although neural networks (especially deep neural networks) have achieved better-than-human performance in many fields, their real-world deployment is still questionable due to the lack of awareness about the limitatio...
Although neural networks (especially deep neural networks) have achieved better-than-human performance in many fields, their real-world deployment is still questionable due to the lack of awareness about the limitations in their knowledge. To incorporate such awareness in the machine learning model, prediction with reject option (also known as selective classification or classification with abstention) has been proposed in the literature. In this paper, we present a systematic review of the prediction with the reject option in the context of various neural networks. To the best of our knowledge, this is the first study focusing on this aspect of neural networks. Moreover, we discuss different novel loss functions related to the reject option and post-training processing (if any) of network output for generating suitable measurements for knowledge awareness of the model. Finally, we address the application of the rejection option in reducing the prediction time for real-time problems and present a comprehensive summary of the techniques related to the reject option in the context of a wide variety of neural networks. Our code is available on GitHub: https://***/MehediHasanTutul/Reject_option.
This book constitutes the refereed proceedings of the 15th Pacific Rim Conference on Multimedia, PCM 2014, held in Kuching, Malaysia, in December 2014. The 35 revised full papers and 6 short papers presented were care...
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ISBN:
(数字)9783319131689
ISBN:
(纸本)9783319131672
This book constitutes the refereed proceedings of the 15th Pacific Rim Conference on Multimedia, PCM 2014, held in Kuching, Malaysia, in December 2014. The 35 revised full papers and 6 short papers presented were carefully reviewed and selected from 84 submissions. The papers cover a wide range of topics in the area of multimedia content analysis, multimedia signal processing and communications, and multimedia applications and services. They have been organized into topical sections on video coding, annotation, image and photo, applications, people, image analysis and processing under extra help, nearest neighbor, neural networks, and audio. Also included are sections with best papers and posters and demonstrations.
This book focuses on a critical issue in the study of physical agents, whether natural or artificial: the quantitative modelling of sensory–motor coordination.;Adopting a novel approach, it defines a common scientifi...
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ISBN:
(数字)9783030141264
ISBN:
(纸本)9783030141240
This book focuses on a critical issue in the study of physical agents, whether natural or artificial: the quantitative modelling of sensory–motor coordination.;Adopting a novel approach, it defines a common scientific framework for both the intelligentsystems designed by engineers and those that have evolved naturally. As such it contributes to the widespread adoption of a rigorous quantitative and refutable approach in the scientific study of ‘embodied’ intelligence and cognition.;More than 70 years after Norbert Wiener’s famous book Cybernetics: or Control and Communication in the Animal and the Machine (1948), robotics, AI and life sciences seem to be converging towards a common model of what we can call the ‘science of embodied intelligent/cognitive agents’.;This book is interesting for an interdisciplinary community of researchers, technologists and entrepreneurs working at the frontiers of robotics and AI, neuroscience and general life and brain sciences.
This volume constitutes the proceedings of the 10th International Conference on Simulated Evolution and Learning, SEAL 2012, held in Dunedin, New Zealand, in December 2014. The 42 full papers and 29 short papers prese...
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ISBN:
(数字)9783319135632
ISBN:
(纸本)9783319135625
This volume constitutes the proceedings of the 10th International Conference on Simulated Evolution and Learning, SEAL 2012, held in Dunedin, New Zealand, in December 2014. The 42 full papers and 29 short papers presented were carefully reviewed and selected from 109 submissions. The papers are organized in topical sections on evolutionary optimization; evolutionary multi-objective optimization; evolutionary machine learning; theoretical developments; evolutionary feature reduction; evolutionary scheduling and combinatorial optimization; real world applications and evolutionary image analysis.
Advanced Aerial Mobility encompasses many outstanding applications that promise to revolutionize modern logistics and pave the way for various public services and industry uses. However, throughout its history, the de...
Advanced Aerial Mobility encompasses many outstanding applications that promise to revolutionize modern logistics and pave the way for various public services and industry uses. However, throughout its history, the development of such systems has been impeded by the complexity of legal restrictions and physical constraints. While airspaces are often tightly shaped by various legal requirements, Unmanned Aerial Vehicles (UAV) must simultaneously consider, among others, energy demands, signal quality, and noise pollution. In this work, we address this challenge by presenting a novel architecture that integrates methods of Probabilistic Mission Design (ProMis) [1, 2] and Many-Objective Optimization [3] for UAV routing. Hereby, our framework facilitates compliance with legal requirements under uncertainty while producing effective paths that minimize various physical costs a UAV needs to consider when traversing human-inhabited spaces. To this end, we combine hybrid probabilistic first-order logic for spatial reasoning with mixed deterministic-stochastic route optimization, incorporating physical objectives such as energy consumption and radio interference with a logical, probabilistic model of legal requirements. We demonstrate the versatility and advantages of our system in a large-scale empirical evaluation over real-world, crowd-sourced data from a map extract from the city of Paris, France, showing how a network of effective and compliant paths can be formed.
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