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Finding the K largest metrics in a noisy broadcast network

Chengzhi Li, Huaiyu Dai, Husheng Li
2008 2008 46th Annual Allerton Conference on Communication, Control, and Computing  
Distributed computing in an N -node noisy broadcast network is considered. Each node holds an n-bit integer as an input instead of a binary input assumed by most work in literature.  ...  The goal is for all the nodes to find out the K largest values with fault tolerance Q.  ...  In this paper, we will focus on a noisy broadcast network.  ... 
doi:10.1109/allerton.2008.4797694 fatcat:4s2feooaknf6da7oyrbiyg6tb4

Optimal TDMA Frame Scheduling in Broadcasting Packet Radio Networks Using a Gradual Noisy Chaotic Neural Network [chapter]

Haixiang Shi, Lipo Wang
2005 Lecture Notes in Computer Science  
In this paper, we propose a novel approach called the gradual noisy chaotic neural network (G-NCNN) to find a collision-free time slot schedule in a time division multiple access (TDMA) frame in packet  ...  In order to find a minimal average time delay of the network, we aim to find an optimal schedule which has the minimum frame length and provides the maximum channel utilization.  ...  Conclusion In this paper, we propose a gradual noisy chaotic neural network for solving the broadcast scheduling problem in packet radio networks.  ... 
doi:10.1007/11539087_145 fatcat:etozmt3hujex7hfzprrx4iwwry

A Gradual Noisy Chaotic Neural Network for Solving the Broadcast Scheduling Problem in Packet Radio Networks

L. Wang, H. Shi
2006 IEEE Transactions on Neural Networks  
In this paper, we propose a gradual noisy chaotic neural network (G-NCNN) to solve the NP-complete broadcast scheduling problem (BSP) in packet radio networks.  ...  In the first phase, we propose a G-NCNN which combines the noisy chaotic neural network (NCNN) and the gradual expansion scheme to find a minimal TDMA frame length.  ...  In the next section, we will introduce a novel noisy chaotic neural network and then apply this model to solve the BSP in the subsequent sections. III. THE NOISY CHAOTIC NEURAL NETWORK A.  ... 
doi:10.1109/tnn.2006.875976 pmid:16856661 fatcat:kazuigsi5vbgznv2zz7ttdoyva

FINDING THE AUDIENCE IN EARLY AMERICAN RADIO

Amanda R. Keeler
2012 Cultural Studies  
Together, her analysis of these materials recreate a sense of a vibrant time in radio's past in which the audience held significant sway over the radio networks, and the possibilities for radio's future  ...  These matches fell on one side of what Razlogova describes as a "distinctive" mode of listening-"emotional, public, noisy, and populist," designed a "shared" listening experience between listeners and  ... 
doi:10.1080/09502386.2012.707223 fatcat:qzeihrsih5bpteev4o7x53zyhi

Finding parity in a simple broadcast network

R.G. Gallager
1988 IEEE Transactions on Information Theory  
Consider a broadcast network of N nodes in which each binary digit transmitted by each node is received by each other node via a binary symmetric channel of given transition probability.  ...  Each node has a binary state and the problem is to construct a distributed algorithm to find the parity of the set of states with some given reliability.  ...  FINDING PARITY IN A SIMPLE BROADCAST NETWORK by Robert G.  ... 
doi:10.1109/18.2626 fatcat:wpx7ghvt3zemjhxumfvkef75ji

Secondary Vertex Finding in Jets with Neural Networks [article]

Jonathan Shlomi, Sanmay Ganguly, Eilam Gross, Kyle Cranmer, Yaron Lipman, Hadar Serviansky, Haggai Maron, Nimrod Segol
2021 arXiv   pre-print
We use a neural network to perform vertex finding inside jets in order to improve the classification performance, with a focus on separation of bottom vs. charm flavor tagging.  ...  We also find that improved vertex finding leads to a significant improvement in jet classification performance.  ...  Vertex reconstruction is in essence an inverse problem of a complicated noisy (forward) function: Particle Decay → Particle Measurement in Detector (1) Neural networks can find a model for this inverse  ... 
arXiv:2008.02831v3 fatcat:s6k5p6tgqzed7iqe6e6lrsj5c4

Dynamic Query Modeling for Related Content Finding

Daan Odijk, Edgar Meij, Isaac Sijaranamual, Maarten de Rijke
2015 Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval - SIGIR '15  
[18] propose an approach to find relevant news articles during broadcast news.  ...  The MediaEval Search and Hyperlinking task considers two related tasks: finding a known item in broadcast video and providing video hyperlinks for specific anchors.  ... 
doi:10.1145/2766462.2767715 dblp:conf/sigir/OdijkMSR15 fatcat:mnc5wctzcnbxrczgcvxf2hyhbe

Finding consensus in speech recognition: word error minimization and other applications of confusion networks [article]

L. Mangu, E. Brill, A. Stolcke
2000 arXiv   pre-print
In addition to improving the accuracy of the recognizer, our method produces a new representation of the set of candidate hypotheses that specifies the sequence of word-level confusions in a compact lattice  ...  In the standard MAP decoding approach the recognizer outputs the string of words corresponding to the path with the highest posterior probability given the acoustics and a language model.  ...  Dimitra Vergyri kindly provided the lattices used in the experiments. The work reported here was supported in part by NSF and DARPA under NSF grant IRI-9618874 (STIMULATE).  ... 
arXiv:cs/0010012v1 fatcat:limmi3xkmveixoe7rp33txes6e

What needles do sparse neural networks find in nonlinear haystacks [article]

Sylvain Sardy, Nicolas W Hengartner, Nikolai Bonenko, Yen Ting Lin
2020 arXiv   pre-print
Using a sparsity inducing penalty in artificial neural networks (ANNs) avoids over-fitting, especially in situations where noise is high and the training set is small in comparison to the number of features  ...  For linear models, such an approach provably also recovers the important features with high probability in regimes for a well-chosen penalty parameter.  ...  + is the broadcasting operation.  ... 
arXiv:2006.04041v1 fatcat:qjywf3uczjhvfa6rf5xovg7lbm

LlamaFur: Learning Latent Category Matrix to Find Unexpected Relations in Wikipedia [article]

Paolo Boldi, Corrado Monti
2016 arXiv   pre-print
In this work we focus on finding "unexpected links" in hyperlinked document corpora when documents are assigned to categories.  ...  Besides finding trends and unveiling typical patterns, modern information retrieval is increasingly more interested in the discovery of surprising information in textual datasets.  ...  An alternative way to approach the problem of finding unexpected links is by using link prediction [30] : the expectedness of a link e in a network G is the likelihood of the creation of e in G − {e}.  ... 
arXiv:1603.09540v2 fatcat:gcya7kq4mrcllm2z3zej2lf63y

Finding Sparse Solutions for the Index Coding Problem

M. A. R. Chaudhry, Z. Asad, A. Sprintson, M. Langberg
2011 2011 IEEE Global Telecommunications Conference - GLOBECOM 2011  
In this problem, a server needs to deliver data to a set of wireless clients over the broadcast channel.  ...  In this paper, we focus on finding sparse solutions to the Index Coding problem. In a sparse solution each transmitted packet is a linear combination of at most two original packets.  ...  In [12] authors presented a sparse network coding scheme for robust communication in wireless body area networks.  ... 
doi:10.1109/glocom.2011.6134497 dblp:conf/globecom/ChaudhryASL11 fatcat:uic44xdf4re23aeoq7ou7oknva

Finding Constant from Change: Revisiting Network Performance Aware Optimizations on IaaS Clouds

Yifan Gong, Bingsheng He, Dan Li
2014 SC14: International Conference for High Performance Computing, Networking, Storage and Analysis  
To enable existing network performance aware optimizations on IaaS clouds, we propose to decouple constant component from dynamic network performance while minimizing the difference by a mathematical method  ...  Network performance aware optimizations have long been an effective approach to optimizing distributed applications on traditional network environments.  ...  It is a non-trivial task to find the constant component from dynamic network performance.  ... 
doi:10.1109/sc.2014.85 dblp:conf/sc/GongHL14 fatcat:aiud5mfkcjfincxlfg32yni45m

An Accurate Direction Finding Scheme Using Virtual Antenna Array via Smartphones

Xiaopu Wang, Yan Xiong, Wenchao Huang
2016 Sensors  
Our method is derived from a key insight: By moving a smartphone in regular patterns, we can effectively emulate the sensitivity and functionality of a Uniform Antenna Array to estimate the angle of arrival  ...  Therefore, we propose and implement an accurate, efficient and lightweight system for indoor direction finding using common smartphones and loudspeakers.  ...  Introduction Nowadays, localization technology has been widely applied in mobile social networking, augmented reality, etc.  ... 
doi:10.3390/s16111811 pmid:27801866 pmcid:PMC5134470 fatcat:3lygxj3xufappkyzdw44iowoiq

Mapping communities in large virtual social networks: Using Twitter data to find the Indie Mac community

Michiel van Meeteren, Ate Poorthuis, Elenna Dugundji
2010 2010 IEEE International Workshop on: Business Applications of Social Network Analysis (BASNA)  
Triangulation with qualitative data proves that the fast greedy algorithm is able to distill meaningful communities from a large, noisy and illdelineated network.  ...  This paper describes a multi-method approach to delineate a "real world" community of practice from a large N dataset derived from the social networking site Twitter.  ...  However, by triangulating with earlier qualitative findings and with a self-description provided by each node in the network, we have shown that it is possible to find meaningful subcommunities in a large  ... 
doi:10.1109/basna.2010.5730297 fatcat:2a53itghxffkvddtlookeyzpvq

Finding Event-Specific Influencers in Dynamic Social Networks

Christopher B. Schenk, Douglas C. Sicker
2011 2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int'l Conference on Social Computing  
I demonstrate that the HITS algorithm is not effective at finding influential users, and propose a new algorithm and demonstrate its effectiveness for finding influential users during an event.  ...  that may implicitly infer user or data reputation based on metadata, user relationships and user actions in social networks.  ...  Influencers Finding influencers in a network during an event is a first step in determining reputation.  ... 
doi:10.1109/passat/socialcom.2011.100 dblp:conf/socialcom/SchenkS11 fatcat:nlzs32zowvcmbio2txnfuttkiu
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