344 research outputs found
Trees with an On-Line Degree Ramsey Number of Four
On-line Ramsey theory studies a graph-building game between two players. The player called Builder builds edges one at a time, and the player called Painter paints each new edge red or blue after it is built. The graph constructed is called the background graph. Builder's goal is to cause the background graph to contain a monochromatic copy of a given goal graph, and Painter's goal is to prevent this. In the S[subscript k]-game variant of the typical game, the background graph is constrained to have maximum degree no greater than k. The on-line degree Ramsey number [˚over R][subscript Δ](G) of a graph G is the minimum k such that Builder wins an S[subscript k]-game in which G is the goal graph. Butterfield et al. previously determined all graphs G satisfying [˚ over R][subscript Δ](G)≤3. We provide a complete classification of trees T satisfying [˚ over R][subscript Δ](T)=4.National Science Foundation (U.S.) (Grant DMS-0754106)United States. National Security Agency (Grant H98230-06-1-0013
Towards an integrated understanding of neural networks
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mathematics, 2018.Cataloged from PDF version of thesis.Includes bibliographical references (pages 123-136).Neural networks underpin both biological intelligence and modern Al systems, yet there is relatively little theory for how the observed behavior of these networks arises. Even the connectivity of neurons within the brain remains largely unknown, and popular deep learning algorithms lack theoretical justification or reliability guarantees. This thesis aims towards a more rigorous understanding of neural networks. We characterize and, where possible, prove essential properties of neural algorithms: expressivity, learning, and robustness. We show how observed emergent behavior can arise from network dynamics, and we develop algorithms for learning more about the network structure of the brain.by David Rolnick.Ph. D
Looking for evidence of noncompetitive behavior in Minnesota's banking industry
Banks and banking - Minnesota
Neural Networks as Paths through the Space of Representations
Deep neural networks implement a sequence of layer-by-layer operations that
are each relatively easy to understand, but the resulting overall computation
is generally difficult to understand. We consider a simple hypothesis for
interpreting the layer-by-layer construction of useful representations: perhaps
the role of each layer is to reformat information to reduce the "distance" to
the desired outputs. With this framework, the layer-wise computation
implemented by a deep neural network can be viewed as a path through a
high-dimensional representation space. We formalize this intuitive idea of a
"path" by leveraging recent advances in *metric* representational similarity.
We extend existing representational distance methods by computing geodesics,
angles, and projections of representations, going beyond mere layer distances.
We then demonstrate these tools by visualizing and comparing the paths taken by
ResNet and VGG architectures on CIFAR-10. We conclude by sketching additional
ways that this kind of representational geometry can be used to understand and
interpret network training, and to describe novel kinds of similarities between
different models.Comment: 10 pages, submitted to ICLR 202
Nuclear dependence of the transverse single-spin asymmetry in the production of charged hadrons at forward rapidity in polarized , Al, and Au collisions at GeV
We report on the nuclear dependence of transverse single-spin asymmetries
(TSSAs) in the production of positively-charged hadrons in polarized
, Al and Au collisions at
GeV. The measurements have been performed at forward
rapidity () over the range of GeV and
. We observed a positive asymmetry for
positively-charged hadrons in \polpp collisions, and a significantly reduced
asymmetry in + collisions. These results reveal a nuclear
dependence of charged hadron in a regime where perturbative techniques
are relevant. These results provide new opportunities to use \polpA collisions
as a tool to investigate the rich phenomena behind TSSAs in hadronic collisions
and to use TSSA as a new handle in studying small-system collisions.Comment: 303 authors from 66 institutions, 9 pages, 2 figures, 1 table. v1 is
version accepted for publication in Physical Review Letters. Plain text data
tables for the points plotted in figures for this and previous PHENIX
publications are (or will be) publicly available at
http://www.phenix.bnl.gov/papers.htm
Measurements of double-helicity asymmetries in inclusive production in longitudinally polarized collisions at GeV
We report the double helicity asymmetry, , in inclusive
production at forward rapidity as a function of transverse momentum
and rapidity . The data analyzed were taken during
GeV longitudinally polarized collisions at the Relativistic Heavy Ion
Collider (RHIC) in the 2013 run using the PHENIX detector. At this collision
energy, particles are predominantly produced through gluon-gluon
scatterings, thus is sensitive to the gluon polarization
inside the proton. We measured by detecting the decay
daughter muon pairs within the PHENIX muon spectrometers in the
rapidity range . In this kinematic range, we measured the
to be ~(stat)~~(syst). The
can be expressed to be proportional to the product of the
gluon polarization distributions at two distinct ranges of Bjorken : one at
moderate range where recent RHIC data of jet and
double helicity spin asymmetries have shown evidence for significant gluon
polarization, and the other one covering the poorly known small- region . Thus our new results could be used to further
constrain the gluon polarization for .Comment: 335 authors, 10 pages, 4 figures, 3 tables, 2013 data. Version
accepted for publication by Phys. Rev. D. Plain text data tables for the
points plotted in figures for this and previous PHENIX publications are (or
will be) publicly available at http://www.phenix.bnl.gov/papers.htm
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