<?xml version="1.0" encoding="UTF-8"?>
 <rdf:RDF xmlns="http://purl.org/rss/1.0/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:cc="http://web.resource.org/cc/" xmlns:syn="http://purl.org/rss/1.0/modules/syndication/" xmlns:admin="http://webns.net/mvcb/">
  <channel rdf:about="http://pinboard.in">
    <title>Pinboard (Vaguery)</title>
    <link>https://pinboard.in/u:Vaguery/public/</link>
    <description>recent bookmarks from Vaguery</description>
    <items>
      <rdf:Seq>	<rdf:li rdf:resource="https://arxiv.org/abs/1706.06083"/>
	<rdf:li rdf:resource="http://www.space.com/11907-mars-history-martian-illusions-human-delusions.html"/>
	<rdf:li rdf:resource="http://illusioncontest.neuralcorrelate.com/"/>
      </rdf:Seq>
    </items>
  </channel><item rdf:about="https://arxiv.org/abs/1706.06083">
    <title>[1706.06083] Towards Deep Learning Models Resistant to Adversarial Attacks</title>
    <dc:date>2019-03-02T13:02:30+00:00</dc:date>
    <link>https://arxiv.org/abs/1706.06083</link>
    <dc:creator>Vaguery</dc:creator><description><![CDATA[Recent work has demonstrated that neural networks are vulnerable to adversarial examples, i.e., inputs that are almost indistinguishable from natural data and yet classified incorrectly by the network. In fact, some of the latest findings suggest that the existence of adversarial attacks may be an inherent weakness of deep learning models. To address this problem, we study the adversarial robustness of neural networks through the lens of robust optimization. This approach provides us with a broad and unifying view on much of the prior work on this topic. Its principled nature also enables us to identify methods for both training and attacking neural networks that are reliable and, in a certain sense, universal. In particular, they specify a concrete security guarantee that would protect against any adversary. These methods let us train networks with significantly improved resistance to a wide range of adversarial attacks. They also suggest the notion of security against a first-order adversary as a natural and broad security guarantee. We believe that robustness against such well-defined classes of adversaries is an important stepping stone towards fully resistant deep learning models.
]]></description>
<dc:subject>machine-learning adversarial-learning coevolution generalization optical-illusions feature-extraction feature-construction neural-networks rather-interesting to-write-about</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:Vaguery/b:467cab18cde9/</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:adversarial-learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:coevolution"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:generalization"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:optical-illusions"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:feature-extraction"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:feature-construction"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:neural-networks"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:rather-interesting"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:to-write-about"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.space.com/11907-mars-history-martian-illusions-human-delusions.html">
    <title>Seeing Things On Mars: A Long History of Martian Illusions and Human Delusions |Pareidolia &amp; Optical Illusions | Space.com</title>
    <dc:date>2011-06-10T12:44:49+00:00</dc:date>
    <link>http://www.space.com/11907-mars-history-martian-illusions-human-delusions.html</link>
    <dc:creator>Vaguery</dc:creator><description><![CDATA["Humans have been seeing strange things on the surface of Mars for centuries. From the 1700s up through the present day, widespread fame has been available to anyone able to produce even the slightest bit of flimsy evidence that there's Martian life."]]></description>
<dc:subject>nanohistory Mars psychoceramics astronomy belief optical-illusions</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:Vaguery/b:f1b64f5b229b/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:nanohistory"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:Mars"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:psychoceramics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:astronomy"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:belief"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:optical-illusions"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://illusioncontest.neuralcorrelate.com/">
    <title>Best Illusion of the Year Contest</title>
    <dc:date>2011-05-26T13:47:20+00:00</dc:date>
    <link>http://illusioncontest.neuralcorrelate.com/</link>
    <dc:creator>Vaguery</dc:creator><description><![CDATA["The Best Visual illusion of the Year Contest is a celebration of the ingenuity and creativity of the world’s premier visual illusion research community. Contestants from all around the world submitted novel visual illusions (unpublished, or published no earlier than 2009), and an international panel of judges rated them and narrowed them to the TOP TEN. At the Contest Gala in the Naples Philharmonic Center for the Arts, the top ten illusionists presented their creations and the attendees of the event voted to pick the TOP THREE WINNERS!"]]></description>
<dc:subject>via:Jason-H-Moore optical-illusions contest psychology cognition nudge-targets</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:Vaguery/b:1c6cfb772d3d/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:via:Jason-H-Moore"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:optical-illusions"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:contest"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:psychology"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:cognition"/>
	<rdf:li rdf:resource="https://pinboard.in/u:Vaguery/t:nudge-targets"/>
</rdf:Bag></taxo:topics>
</item>
</rdf:RDF>