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    <title>Pinboard (Vaguery)</title>
    <link>https://pinboard.in/u:Vaguery/public/</link>
    <description>recent bookmarks from Vaguery</description>
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      <rdf:Seq>	<rdf:li rdf:resource="https://jlsc-pub.org/articles/abstract/10.7710/2162-3309.2333/"/>
	<rdf:li rdf:resource="https://arxiv.org/abs/1908.00868"/>
	<rdf:li rdf:resource="http://arxiv.org/abs/1408.3841"/>
	<rdf:li rdf:resource="http://arxiv.org/abs/0912.5193"/>
	<rdf:li rdf:resource="http://arxiv.org/abs/1303.4303"/>
	<rdf:li rdf:resource="http://arxiv.org/abs/1006.3582"/>
	<rdf:li rdf:resource="http://blog.objectmentor.com/articles/2008/11/27/the-truth-about-bdd"/>
	<rdf:li rdf:resource="http://www.idlewords.com/2005/04/dabblers_and_blowhards.htm"/>
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  </channel><item rdf:about="https://jlsc-pub.org/articles/abstract/10.7710/2162-3309.2333/">
    <title>Is Scholarly Publishing Like Rock and Roll?</title>
    <dc:date>2020-11-14T11:40:42+00:00</dc:date>
    <link>https://jlsc-pub.org/articles/abstract/10.7710/2162-3309.2333/</link>
    <dc:creator>Vaguery</dc:creator><description><![CDATA[This article uses Alan B. Krueger’s analysis of the music industry in his book Rockonomics: A Backstage Tour of What the Music Industry Can Teach Us About Economics and Life as a lens to consider the structure of scholarly publishing and what could happen to scholarly publishing going forward. Both the music industry and scholarly publishing are facing disruption as their products become digital. Digital content provides opportunities to a create a better product at lower prices and in the music industry this has happened. Scholarly publishing has not yet done so. Similarities and differences between the music industry and scholarly publishing will be considered. Like music, scholarly publishing appears to be a superstar industry. Both music and scholarly publishing are subject to piracy, which threatens revenue, though Napster was a greater disrupter than Sci-Hub seems to be. It also appears that for a variety of reasons market forces are not effective in driving changes in business models and practices in scholarly publishing, at least not at the rate we would expect given the changes in technology. After reviewing similarities and differences, the prospects for the future of scholarly publishing will be considered.
]]></description>
<dc:subject>via:several academic-culture publishing citation-networks analogies long-tails economics</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:Vaguery/b:cf48f8c5f1c8/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:via:several"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:academic-culture"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:publishing"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:citation-networks"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:analogies"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:long-tails"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:economics"/>
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<item rdf:about="https://arxiv.org/abs/1908.00868">
    <title>[1908.00868] Machine Learning as Ecology</title>
    <dc:date>2019-08-05T14:21:59+00:00</dc:date>
    <link>https://arxiv.org/abs/1908.00868</link>
    <dc:creator>Vaguery</dc:creator><description><![CDATA[Machine learning methods have had spectacular success on numerous problems. Here we show that a prominent class of learning algorithms - including Support Vector Machines (SVMs) -- have a natural interpretation in terms of ecological dynamics. We use these ideas to design new online SVM algorithms that exploit ecological invasions, and benchmark performance using the MNIST dataset. Our work provides a new ecological lens through which we can view statistical learning and opens the possibility of designing ecosystems for machine learning. 
]]></description>
<dc:subject>machine-learning analogies via:cshalizi but-I-am-less-skeptical a-good-analogy-is-a-blessing-to-the-mind to-read</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:Vaguery/b:ac3f5bce6e2a/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:machine-learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:analogies"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:via:cshalizi"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:but-I-am-less-skeptical"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:a-good-analogy-is-a-blessing-to-the-mind"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:to-read"/>
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<item rdf:about="http://arxiv.org/abs/1408.3841">
    <title>[1408.3841] Extraction of Force-Chain Network Architecture in Granular Materials Using Community Detection</title>
    <dc:date>2015-11-12T13:40:15+00:00</dc:date>
    <link>http://arxiv.org/abs/1408.3841</link>
    <dc:creator>Vaguery</dc:creator><description><![CDATA[Force chains form heterogeneous physical structures that can constrain the mechanical stability and acoustic transmission of granular media. However, despite their relevance for predicting bulk properties of materials, there is no agreement on a quantitative description of force chains. Consequently, it is difficult to compare the force-chain structures in different materials or experimental conditions. To address this challenge, we treat granular materials as spatially-embedded networks in which the nodes (particles) are connected by weighted edges that represent contact forces. We use techniques from community detection, which is a type of clustering, to find sets of closely connected particles. By using a geographical null model that is constrained by the particles' contact network, we extract chain-like structures that are reminiscent of force chains. We propose three diagnostics to measure these chain-like structures, and we demonstrate the utility of these diagnostics for identifying and characterizing classes of force-chain network architectures in various materials. To illustrate our methods, we describe how force-chain architecture depends on pressure for two very different types of packings: (1) ones derived from laboratory experiments and (2) ones derived from idealized, numerically-generated frictionless packings. By resolving individual force chains, we quantify statistical properties of force-chain shape and strength, which are potentially crucial diagnostics of bulk properties (including material stability). These methods facilitate quantitative comparisons between different particulate systems, regardless of whether they are measured experimentally or numerically.
]]></description>
<dc:subject>physics! granular-materials community-detection rather-interesting analogies one-of-these-things-is-something-like-the-others nudge-targets consider:feature-discovery</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:Vaguery/b:4aa1728e940b/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:physics!"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:granular-materials"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:community-detection"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:rather-interesting"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:analogies"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:one-of-these-things-is-something-like-the-others"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:nudge-targets"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:consider:feature-discovery"/>
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</item>
<item rdf:about="http://arxiv.org/abs/0912.5193">
    <title>[0912.5193] Ranking relations using analogies in biological and information networks</title>
    <dc:date>2013-09-03T18:08:54+00:00</dc:date>
    <link>http://arxiv.org/abs/0912.5193</link>
    <dc:creator>Vaguery</dc:creator><description><![CDATA[Analogical reasoning depends fundamentally on the ability to learn and generalize about relations between objects. We develop an approach to relational learning which, given a set of pairs of objects $\mathbf{S}=\{A^{(1)}:B^{(1)},A^{(2)}:B^{(2)},\ldots,A^{(N)}:B ^{(N)}\}$, measures how well other pairs A:B fit in with the set $\mathbf{S}$. Our work addresses the following question: is the relation between objects A and B analogous to those relations found in $\mathbf{S}$? Such questions are particularly relevant in information retrieval, where an investigator might want to search for analogous pairs of objects that match the query set of interest. There are many ways in which objects can be related, making the task of measuring analogies very challenging. Our approach combines a similarity measure on function spaces with Bayesian analysis to produce a ranking. It requires data containing features of the objects of interest and a link matrix specifying which relationships exist; no further attributes of such relationships are necessary. We illustrate the potential of our method on text analysis and information networks. An application on discovering functional interactions between pairs of proteins is discussed in detail, where we show that our approach can work in practice even if a small set of protein pairs is provided.
]]></description>
<dc:subject>analogies learning-from-data machine-learning algorithms natural-language-processing artificial-intelligence nudge-targets digital-humanities</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:Vaguery/b:a9165c420b21/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:analogies"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:learning-from-data"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:machine-learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:algorithms"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:natural-language-processing"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:artificial-intelligence"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:nudge-targets"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:digital-humanities"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://arxiv.org/abs/1303.4303">
    <title>[1303.4303] Dynamic Ising Model: Reconstruction of Evolutionary Trees</title>
    <dc:date>2013-04-08T20:05:18+00:00</dc:date>
    <link>http://arxiv.org/abs/1303.4303</link>
    <dc:creator>Vaguery</dc:creator><description><![CDATA[An evolutionary tree is a cascade of bifurcations starting from a single common root, generating a growing set of daughter species as time goes by. Species here is a general denomination for biological species, spoken languages or any other entity evolving through heredity. From the N currently alive species within a clade, distances are measured through pairwise comparisons made by geneticists, linguists, etc. The larger is such a distance for a pair of species, the older is their last common ancestor. The aim is to reconstruct the past unknown bifurcations, i.e. the whole clade, from the knowledge of the N(N-1)/2 quoted distances taken for granted. A mechanical method is presented, and its applicability discussed.]]></description>
<dc:subject>ising-models cladistics algorithms physics nudge-targets representation analogies</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:Vaguery/b:205971966e7e/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:ising-models"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:cladistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:algorithms"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:physics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:nudge-targets"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:representation"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:analogies"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://arxiv.org/abs/1006.3582">
    <title>[1006.3582] Sonic Gradient Index Lens for Aqueous Applications</title>
    <dc:date>2010-06-28T22:00:51+00:00</dc:date>
    <link>http://arxiv.org/abs/1006.3582</link>
    <dc:creator>Vaguery</dc:creator><description><![CDATA["We study the acoustic scattering properties of a phononic crystal designed to behave as a gradient index lens in water, both experimentally and theoretically. The gradient index lens is designed using a square lattice of stainless-steel cylinders based on a multiple scattering approach in the homogenization limit. We experimentally demonstrate that the lens follows the graded index equations derived for optics by mapping the pressure intensity generated from a spherical source at 20 kHz. We find good agreement between the experimental result and theoretical modeling based on multiple scattering theory."
]]></description>
<dc:subject>nudge-targets acoustics phononics(?!) engineering-design simulation experimental-design physics analogies</dc:subject>
<dc:identifier>https://pinboard.in/u:Vaguery/b:8e70ea9b2291/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:nudge-targets"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:acoustics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:phononics(?!)"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:engineering-design"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:simulation"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:experimental-design"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:physics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:analogies"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://blog.objectmentor.com/articles/2008/11/27/the-truth-about-bdd">
    <title>The Truth about BDD</title>
    <dc:date>2008-12-31T15:39:12+00:00</dc:date>
    <link>http://blog.objectmentor.com/articles/2008/11/27/the-truth-about-bdd</link>
    <dc:creator>Vaguery</dc:creator><description><![CDATA["But enough of irony. Is this useful? I think it may be. You see, one of the great benefits of describing a problem as a Finite State Machine (FSM) is that you can complete the logic of the problem. That is, if you can enumerate the states and the events, then you know that the number of paths through the system is no larger than S * E. Or, rather, there are no more than S*E transitions from one state to another. More importantly, enumerating them is simply a matter of creating a transition for every combination of state and event.

One of the more persistent problems in BDD (and TDD for that matter) is knowing when you are done. That is, how do you know that you have written enough scenarios (tests). Perhaps there is some condition that you have forgotten to explore, some pathway through the system that you have not described."
]]></description>
<dc:subject>via:arsyed software design BDD programming TDD behavior-driven-design analogies finite-state-machine</dc:subject>
<dc:identifier>https://pinboard.in/u:Vaguery/b:5e33503c3c92/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:via:arsyed"/>
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	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:design"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:BDD"/>
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	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:TDD"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:behavior-driven-design"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:analogies"/>
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</item>
<item rdf:about="http://www.idlewords.com/2005/04/dabblers_and_blowhards.htm">
    <title>[Best not over-generalize]</title>
    <dc:date>2008-03-22T17:33:21+00:00</dc:date>
    <link>http://www.idlewords.com/2005/04/dabblers_and_blowhards.htm</link>
    <dc:creator>Vaguery</dc:creator><description><![CDATA["But you, sir, are no painter. And while you hack away at your terminal, or ride your homemade Segway, we painters and musicians are going to be right over here with all the wine, hash, and hot chicks."
]]></description>
<dc:subject>analogies commentary criticism philosophy books hacking programming art</dc:subject>
<dc:identifier>https://pinboard.in/u:Vaguery/b:ee76321a8528/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:analogies"/>
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	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:criticism"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:philosophy"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:books"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:hacking"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:programming"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:art"/>
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