4,319 research outputs found
Ascending auctions and Walrasian equilibrium
We present a family of submodular valuation classes that generalizes gross
substitute. We show that Walrasian equilibrium always exist for one class in
this family, and there is a natural ascending auction which finds it. We prove
some new structural properties on gross-substitute auctions which, in turn,
show that the known ascending auctions for this class (Gul-Stacchetti and
Ausbel) are, in fact, identical. We generalize these two auctions, and provide
a simple proof that they terminate in a Walrasian equilibrium
Sum Tzu and the Mathematics of War: A Predictive Assistant for Warhammer 40,000
The purpose of this project is to classify simple strategies for the tabletop miniature war game Warhammer 40,000. The paper enumerates a series of strategies that are straightforward to automate. Further analysis on these simulations identify collection of proposed best and worst auto-strategies
Testing formula satisfaction
We study the query complexity of testing for properties defined by read once formulae, as instances of massively parametrized properties, and prove several testability and non-testability results. First we prove the testability of any property accepted by a Boolean read-once formula involving any bounded arity gates, with a number of queries exponential in \epsilon and independent of all other parameters. When the gates are limited to being monotone, we prove that there is an estimation algorithm, that outputs an approximation of the distance of the input from
satisfying the property. For formulae only involving And/Or gates, we provide a more efficient test whose query complexity is only quasi-polynomial in \epsilon. On the other hand we show that such testability results do not hold in general for formulae over non-Boolean alphabets; specifically we construct a property defined by a read-once arity 2 (non-Boolean) formula over alphabets of size 4, such that any 1/4-test for it requires a number of queries depending on the formula size
No Ascending Auction can find Equilibrium for SubModular valuations
We show that no efficient ascending auction can guarantee to find even a
minimal envy-free price vector if all valuations are submodular, assuming a
basic complexity theory's assumption.Comment: arXiv admin note: text overlap with arXiv:1301.115
During the election, Donald Trump's racist rhetoric activated the fears of people in areas with growing Latino populations
In the opening salvo of his presidential election campaign in June 2015, Donald Trump referred to Mexican immigrants as "racists" and "criminals". In new research Ben Newman, Sono Shah, and Loren Collingwood look at how Trump's racist rhetoric drew support during the election. Using data from survey polls taken during the campaign, they find that Trump's inflammatory comments activated the latent anti-immigrant sentiments of those who lived in areas which had experienced large increases in their Latino populations
Scene signatures: localised and point-less features for localisation
This paper is about localising across extreme lighting and weather conditions. We depart from the traditional point-feature-based approach as matching under dramatic appearance changes is a brittle and hard thing. Point feature detectors are fixed and rigid procedures which pass over an image examining small, low-level structure such as corners or blobs. They apply the same criteria applied all images of all places. This paper takes a contrary view and asks what is possible if instead we learn a bespoke detector for every place. Our localisation task then turns into curating a large bank of spatially indexed detectors and we show that this yields vastly superior performance in terms of robustness in exchange for a reduced but tolerable metric precision. We present an unsupervised system that produces broad-region detectors for distinctive visual elements, called scene signatures, which can be associated across almost all appearance changes. We show, using 21km of data collected over a period of 3 months, that our system is capable of producing metric localisation estimates from night-to-day or summer-to-winter conditions
Growth and structure of Slovenia's scientific collaboration network
We study the evolution of Slovenia's scientific collaboration network from
1960 till present with a yearly resolution. For each year the network was
constructed from publication records of Slovene scientists, whereby two were
connected if, up to the given year inclusive, they have coauthored at least one
paper together. Starting with no more than 30 scientists with an average of 1.5
collaborators in the year 1960, the network to date consists of 7380
individuals that, on average, have 10.7 collaborators. We show that, in spite
of the broad myriad of research fields covered, the networks form "small
worlds" and that indeed the average path between any pair of scientists scales
logarithmically with size after the largest component becomes large enough.
Moreover, we show that the network growth is governed by near-liner
preferential attachment, giving rise to a log-normal distribution of
collaborators per author, and that the average starting year is roughly
inversely proportional to the number of collaborators eventually acquired.
Understandably, not all that became active early have till now gathered many
collaborators. We also give results for the clustering coefficient and the
diameter of the network over time, and compare our conclusions with those
reported previously.Comment: 10 pages, 3 figures; accepted for publication in Journal of
Informetrics [related work available at http://arxiv.org/abs/1003.1018 and
http://www.matjazperc.com/sicris/stats.html
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