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Moment Machine: Opportunities and Challenges of Posting Situated Snapshots onto Networked Public Displays [chapter]

Nemanja Memarovic, Ava Fatah gen Schieck, Efstathia Kostopoulou, Moritz Behrens, Martin Traunmueller
2013 Lecture Notes in Computer Science  
In order to understand the potential of posting situated snapshots on networked public displays in the context of place-based communities we designed and developed the Moment Machine -a networked public  ...  Interconnected over the Internet these hitherto isolated "ad displays" could become a novel and powerful communication medium -networked public displays.  ...  networked urban screens for communities and culture" under the grant agreement no.  ... 
doi:10.1007/978-3-642-40498-6_50 fatcat:o5rp27sb5berbhuy7si2f36j6a

Hermeneutic of performing data

Karamjit S. Gill
2017 AI & Society: The Journal of Human-Centred Systems and Machine Intelligence  
Moreover, anonymity and secrecy in which personal data are manipulated leaves little opportunity to anchor this new capacity of the digital driver in public interest or public debate.  ...  Inhabitants of a public space respond to a series of questions using their mobile phones, and interact with each other in real time using a media facade or similar display infrastructure.  ... 
doi:10.1007/s00146-017-0727-2 fatcat:p6iguowznvbcxk7iv3kktl4lhm

On closures for reduced order models - A spectrum of first-principle to machine-learned avenues [article]

Shady E. Ahmed, Suraj Pawar, Omer San, Adil Rasheed, Traian Iliescu, Bernd R. Noack
2021 arXiv   pre-print
, and machine learning have changed the standard ROM methodology over the last two decades.  ...  Early examples include Galerkin models inspired by the Orr-Sommerfeld stability equation and numerous vortex models, of which the von K\'arm\'an vortex street is one of the most prominent.  ...  visualization tool of the network analysis 443 , physics-guided machine learning 444, 445 , and hybrid modeling 20, 240, 410, 446 .  ... 
arXiv:2106.14954v2 fatcat:q6jzbxfjabc3vg3nsn24z4lbyy

A Survey of Statistical Network Models

Anna Goldenberg
2009 Foundations and Trends® in Machine Learning  
We thank Joseph Blitzstein and Pavel Krivitsky for a careful reading and the correction of a number of infelicities.  ...  Airoldi was a postdoctoral fellow in the Department of Computer Science and the Lewis-Sigler Institute for Integrative Genomics at Princeton University when a large portion of this work was carried out  ...  Several network data repositories are available on public websites and as part of packages.  ... 
doi:10.1561/2200000005 fatcat:psbbsr4hgbdfhjx5wr6hky7mc4

Brain–Machine Interface Engineering

Justin C. Sanchez, José C. Principe
2007 Synthesis Lectures on Biomedical Engineering  
Karl Gugel helped develop the DSP hardware and firmware to create the new generation of portable systems. We were fortunate to count with the intelligence, dedication, and hard work of many students.  ...  Rizwan Bashirullah open up the scope of the work with electrodes and wireless systems.  ...  BRaIN-MaChINE INTERFaCE ENgINEERINg BRaIN-MaChINE INTERFaCE ENgINEERINg BRaIN-MaChINE INTERFaCE ENgINEERINg A property of some stationary random processes in which the statistical moments  ... 
doi:10.2200/s00053ed1v01y200710bme017 fatcat:jm6kaqyjurgddmssiru2fy435i

A survey of migration mechanisms of virtual machines

Violeta Medina, Juan Manuel García
2014 ACM Computing Surveys  
Rosemblum and Garfinkel [2005] present an overview of VMMs.  ...  This migration should be transparent to the guest operating system, applications running on the operating system, and remote clients of the virtual machine.  ...  In LLM, the machine that provides regular services is called the primary machine, and the replica machine is called the backup machine. One challenge of live migration is to minimize the downtime.  ... 
doi:10.1145/2492705 fatcat:7nix6qbtozhcxnzx7admfwfeei

Robust Intelligence (RI) under uncertainty: Mathematical foundations of autonomous hybrid (human-machine-robot) teams, organizations and systems

William F. Lawless
2013 Structure and Dynamics : e-Journal of Anthropological and Related Sciences  
Army Research Laboratory and the U. S. Army Research Office under contract/grant number W911NF-10-1-0252.  ...  Introduction Our challenge is to devise a valid theory for hybrid teams composed interchangeably of humans, machines and robots.  ...  and autonomous machines as part of hybrid teams that they and the public can trust (Lee & See, 2004) , even under uncertainty.  ... 
doi:10.5070/sd962015715 fatcat:5g3uf5ddyfertc4vwd4bc6bvrq

Neural Interfacing: Forging the Human-Machine Connection

Susanne D. Coates
2008 Synthesis Lectures on Biomedical Engineering  
The physical, chemical, molecular, and perhaps even quantum [3, 4] structure of the brain alters itself from moment to moment to store and/or process information.  ...  Amplification ( Fig. 1.7 , right) refers to the opposite situation where the post-synaptic response is greater than the pre-synaptic stimuli.  ...  Last, but not least, a special thanks to all of those who contributed graphics material. ABOUT THE AUTHOR  ... 
doi:10.2200/s00148ed1v01y200809bme022 fatcat:sj2w7ygpyfah7bof3lhre5wc2a

Lowering the barrier to applying machine learning

Kayur Patel
2010 Adjunct proceedings of the 23nd annual ACM symposium on User interface software and technology - UIST '10  
I found that the key barrier to adoption is not a poor understanding of the machine learning algorithms themselves, but rather a poor understanding of the process for applying those algorithms and insufficient  ...  Lowering the Barrier to Applying Machine Learning Data is driving the future of computation: analysis, visualization, and learning algorithms power systems that help us diagnose cancer, live sustainably  ...  Emily Jacobson and Alexis Hope have been a firehose of wonderfully uncomfortable situations and willfully awkward moments.  ... 
doi:10.1145/1866218.1866222 dblp:conf/uist/Patel10 fatcat:7k7ofxfstnayvgdh247ciltcgq

Lowering the barrier to applying machine learning

Kayur Patel
2010 Proceedings of the 28th of the international conference extended abstracts on Human factors in computing systems - CHI EA '10  
I found that the key barrier to adoption is not a poor understanding of the machine learning algorithms themselves, but rather a poor understanding of the process for applying those algorithms and insufficient  ...  Lowering the Barrier to Applying Machine Learning Data is driving the future of computation: analysis, visualization, and learning algorithms power systems that help us diagnose cancer, live sustainably  ...  Emily Jacobson and Alexis Hope have been a firehose of wonderfully uncomfortable situations and willfully awkward moments.  ... 
doi:10.1145/1753846.1753882 dblp:conf/chi/Patel10 fatcat:ctphoo6owzfnpf53ihq7kjix3e

Synthetic Molecular Motors and Mechanical Machines

Euan R. Kay, David A. Leigh, Francesco Zerbetto
2007 Angewandte Chemie International Edition  
[328] The combination of crystalline order with addressable molecular motions, to yield so-called "amphidynamic" crystals, provides a novel and challenging situation for the operation of artificial  ...  Natures motors and machines generally work at interfaces or on surfaces and the transfer of molecular-machine technology onto solid substrates is a key step in the development of many potential applications  ... 
doi:10.1002/anie.200504313 pmid:17133632 fatcat:wf4sk24bejc25jsxrcjxtckmty

Patterns, predictions, and actions: A story about machine learning [article]

Moritz Hardt, Benjamin Recht
2021 arXiv   pre-print
This graduate textbook on machine learning tells a story of how patterns in data support predictions and consequential actions.  ...  Starting with the foundations of decision making, we cover representation, optimization, and generalization as the constituents of supervised learning.  ...  The problem with the window tax foretold a robust limitation of prediction. Datasets display a static snapshot of a population.  ... 
arXiv:2102.05242v2 fatcat:wy47g4fojnfuxngklyewtjtqdi

Decoding Starlight with Big Survey Data, Machine Learning, and Cosmological Simulations [article]

Kirsten Blancato
2020 arXiv   pre-print
Stars, and collections of stars, encode rich signatures of stellar physics and galaxy evolution.  ...  By synthesizing numerical simulations, large observational data sets, and machine learning techniques, this work makes valuable methodological contributions to maximize insights from diverse ensembles  ...  In post-processing, structure is identified in each snapshot first using the FoF (friends-offriends) algorithm (Davis et al. 1985) and then an updated version of the SUBFIND algorithm (Springel et al  ... 
arXiv:2009.10661v1 fatcat:iu6egebr2bfudgqwyfagvbmifa

Cost-to-Go Function Approximation [chapter]

2017 Encyclopedia of Machine Learning and Data Mining  
It maintains a set, S , of most specific hypotheses that are consistent with the training data and a set, G, of most general hypotheses consistent with the training data.  ...  framework, i.e., they assume a set of positive and negative training examples.  ...  Some algorithms, most notably CN2 (Clark and Niblett 1989; Clark and Boswell 1991) , learn multi-class rules directly by optimizing overall possible classes in the head of the rule.  ... 
doi:10.1007/978-1-4899-7687-1_100093 fatcat:vse7ncdqs5atlosjhz7fhlj3im

A Machine that Dreams: An Artistic Enquiry Leading to an Integrative Theory and Computational Artwork

Benjamin David Robert Bogart
2017 Leonardo: Journal of the International Society for the Arts, Sciences and Technology  
artwork and as a computational model of dreaming -the Dreaming Machine.  ...  The Dreaming Machine is an image-making agent that uses clustering and machine learning methods to make sense of live images captured in the context of installation.  ...  Acknowledgements Acknowledgments The authors thank the Social Science and Humanities Research Council of Canada for supporting the research that led to Memory Association Machine and future work on Dreaming  ... 
doi:10.1162/leon_a_01488 fatcat:e4b4pdzfcjc2lpkrwzymdjedci
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