Results 201 to 210 of about 606,212 (231)
Some of the next articles are maybe not open access.
On Network Topology Inference of Social Networks
2019 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2019This paper studies topology inference, from agent states, of a directed cyber-social network with opinion spreading dynamics model that explicitly takes confirmation bias into account. The cyber-social network comprises a set of partially connected directed network of agents at the social level, and a set of information sources at the cyber layer.
Yanbing Mao, Emrah Akyol
openaire +1 more source
Nonmonotonic Inferences and Neural Networks
Synthese, 2004zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +4 more sources
Fuzzy inference neural network
Neurocomputing, 1997Abstract A new model for the design of Fuzzy Inference Neural Network (FINN) is proposed in this paper. It can automatically partition an input-output pattern space and can extract fuzzy if-then rules from numerical data. The proposed FINN is a two-layer network which utilizes Kohonen's algorithm.
Takatoshi Nishima, Masafumi Hagiwara
openaire +1 more source
Robust network topology inference
2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017We address the problem of identifying a graph structure from the observation of signals defined on its nodes. Fundamentally, the unknown graph encodes direct relationships between signal elements, which we aim to recover from observable indirect relationships generated by a diffusion process on the graph. We put forth a novel network topology inference
Santiago Segarra +3 more
openaire +1 more source
Bayesian network loss inference
2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)., 2004In large-scale dynamic communication networks, endsystems can not rely on the network itself to cooperate in characterizing its own behavior. This has prompted research activities on methods for inferring internal network behavior based on the external end-to-end network measurements.
Dong Guo 0003, Xiaodong Wang 0001
openaire +1 more source
Topology inference of multilayer networks
2017 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), 2017Linear structural equation models (SEMs) have been very successful in identifying the topology of complex graphs, such as those representing tactical, social and brain networks. The rising popularity of multilayer networks, presents the need for tools that are tailored to leverage the layered structure of the underlying network.
Panagiotis A. Traganitis +2 more
openaire +1 more source
Bayesian Inference in Trust Networks
ACM Transactions on Management Information Systems, 2013Trust has emerged as a major impediment to the success of electronic markets and communities where interaction with the strangers is the norm. Social Networks and Online Communities enable interaction with complete strangers, and open up new commercial, political, and social possibilities.
openaire +1 more source
Probabilistic Inference for Network Management
2004As networks grow in size, heterogeneity, and complexity of applications and network services, an efficient network management system needs to work effectively even in face of incomplete management information, uncertain situations and dynamic changes.
Jianguo Ding +3 more
openaire +1 more source
Abductive Inference of Genetic Networks
2001GenePath is an automated system for reasoning on genetic networks, wherein a set of genes have various influences on one another and on a biological outcome. It acts on a set of experiments in which genes are knocked out or overexpressed, and the outcome of interest is evaluated.
Blaz Zupan +5 more
openaire +1 more source
On Semantics of Inference in Bayesian Networks
2013An algorithm, called Semantics in Inference (SI) has been proposed recently for determining semantics of the intermediate factors constructed during exact inference in discrete Bayesian networks. In this paper, we establish the soundness and completeness of SI.
Cory J. Butz, Wen Yan, Anders L. Madsen
openaire +2 more sources