112,693 research outputs found
Consistency in Models for Distributed Learning under Communication Constraints
Motivated by sensor networks and other distributed settings, several models
for distributed learning are presented. The models differ from classical works
in statistical pattern recognition by allocating observations of an independent
and identically distributed (i.i.d.) sampling process amongst members of a
network of simple learning agents. The agents are limited in their ability to
communicate to a central fusion center and thus, the amount of information
available for use in classification or regression is constrained. For several
basic communication models in both the binary classification and regression
frameworks, we question the existence of agent decision rules and fusion rules
that result in a universally consistent ensemble. The answers to this question
present new issues to consider with regard to universal consistency. Insofar as
these models present a useful picture of distributed scenarios, this paper
addresses the issue of whether or not the guarantees provided by Stone's
Theorem in centralized environments hold in distributed settings.Comment: To appear in the IEEE Transactions on Information Theor
(WP 2010-08) Neuroeconomics: Constructing Identity
This paper asks whether neuroeconomics will make instrumental use of neuroscience to adjudicate existing disputes in economics or be more seriously informed by neuroscience in ways that might transform economics. The paper pursues the question by asking how neuroscience constructs an understanding of individuals as whole persons. The body of the paper is devoted to examining two approaches: Don Ross’s neurocellular approach to neuroeconomics and Joseph Dumit’s cultural anthropological science organization approach. The accounts are used to identify boundaries on single individual explanations. With that space Andy Clark’s external scaffolding view and Nathaniel Wilcox’s socially distributed cognition view are employed
Collaborative signal and information processing for target detection with heterogeneous sensor networks
In this paper, an approach for target detection and acquisition with heterogeneous sensor networks through strategic resource allocation and coordination is presented. Based on sensor management and collaborative signal and information processing, low-capacity low-cost sensors are strategically deployed to guide and cue scarce high performance sensors in the network to improve the data quality, with which the mission is eventually completed more efficiently with lower cost. We focus on the problem of designing such a network system in which issues of resource selection and allocation, system behaviour and capacity, target behaviour and patterns, the environment, and multiple constraints such as the cost must be addressed simultaneously. Simulation results offer significant insight into sensor selection and network operation, and demonstrate the great benefits introduced by guided search in an application of hunting down and capturing hostile vehicles on the battlefield
Post processing of multimedia information - concepts, problems, and techniques
Currently, most research work on multimedia information processing is focused on multimedia information storage and retrieval, especially indexing and content-based access of multimedia information. We consider multimedia information processing should include one more level-post-processing. Here "post-processing" means further processing of retrieved multimedia information, which includes fusion of multimedia information and reasoning with multimedia information to reach new conclusions. In this paper, the three levels of multimedia information processing storage, retrieval, and post-processing- are discussed. The concepts and problems of multimedia information post-processing are identified. Potential techniques that can be used in post-processing are suggested, By highlighting the problems in multimedia information post-processing, hopefully this paper will stimulate further research on this important but ignored topic.<br /
Editorial Special Issue on Enhancement Algorithms, Methodologies and Technology for Spectral Sensing
The paper is an editorial issue on enhancement algorithms, methodologies and technology for spectral sensing and serves as a valuable and useful reference for researchers and technologists interested in the evolving state-of-the-art and/or the emerging science and technology base associated with spectral-based sensing and monitoring problem. This issue is particularly relevant to those seeking new and improved solutions for detecting chemical, biological, radiological and explosive threats on the land, sea, and in the air
Digital Peacekeepers, Drone Surveillance and Information Fusion: A Philosophical Analysis of New Peacekeeping
In June 2014 an Expert Panel on Technology and Innovation in UN Peacekeeping was commissioned to examine how technology and innovation could strengthen peacekeeping missions. The panel\u27s report argues for wider deployment of advanced technologies, including greater use of ground and airborne sensors and other technical sources of data, advanced data analytics and information fusion to assist in data integration. This article explores the emerging intelligence-led, informationist conception of UN peacekeeping against the backdrop of increasingly complex peacekeeping mandates and precarious security conditions. New peacekeeping with its heightened commitment to information as a political resource and the endorsement of offensive military action within robust mandates reflects the multiple and conflicting trajectories generated by asymmetric conflicts, the responsibility to protect and a technology-driven information revolution. We argue that the idea of peacekeeping is being revised (and has been revised) by realities beyond peacekeeping itself that require rethinking the morality of peacekeeping in light of the emergence of \u27digital peacekeeping\u27 and the knowledge revolution engendered by new technologies
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