92,854 research outputs found
Robust Feature Selection by Mutual Information Distributions
Mutual information is widely used in artificial intelligence, in a
descriptive way, to measure the stochastic dependence of discrete random
variables. In order to address questions such as the reliability of the
empirical value, one must consider sample-to-population inferential approaches.
This paper deals with the distribution of mutual information, as obtained in a
Bayesian framework by a second-order Dirichlet prior distribution. The exact
analytical expression for the mean and an analytical approximation of the
variance are reported. Asymptotic approximations of the distribution are
proposed. The results are applied to the problem of selecting features for
incremental learning and classification of the naive Bayes classifier. A fast,
newly defined method is shown to outperform the traditional approach based on
empirical mutual information on a number of real data sets. Finally, a
theoretical development is reported that allows one to efficiently extend the
above methods to incomplete samples in an easy and effective way.Comment: 8 two-column page
Robust Optical Richness Estimation with Reduced Scatter
Reducing the scatter between cluster mass and optical richness is a key goal
for cluster cosmology from photometric catalogs. We consider various
modifications to the red-sequence matched filter richness estimator of Rozo et
al. (2009), and evaluate their impact on the scatter in X-ray luminosity at
fixed richness. Most significantly, we find that deeper luminosity cuts can
reduce the recovered scatter, finding that sigma_lnLX|lambda=0.63+/-0.02 for
clusters with M_500c >~ 1.6e14 h_70^-1 M_sun. The corresponding scatter in mass
at fixed richness is sigma_lnM|lambda ~ 0.2-0.3 depending on the richness,
comparable to that for total X-ray luminosity. We find that including blue
galaxies in the richness estimate increases the scatter, as does weighting
galaxies by their optical luminosity. We further demonstrate that our richness
estimator is very robust. Specifically, the filter employed when estimating
richness can be calibrated directly from the data, without requiring a-priori
calibrations of the red-sequence. We also demonstrate that the recovered
richness is robust to up to 50% uncertainties in the galaxy background, as well
as to the choice of photometric filter employed, so long as the filters span
the 4000 A break of red-sequence galaxies. Consequently, our richness estimator
can be used to compare richness estimates of different clusters, even if they
do not share the same photometric data. Appendix 1 includes "easy-bake"
instructions for implementing our optimal richness estimator, and we are
releasing an implementation of the code that works with SDSS data, as well as
an augmented maxBCG catalog with the lambda richness measured for each cluster.Comment: Submitted to ApJ. 20 pages in emulateapj forma
The Whole is Greater than the Sum of the Parts: Optimizing the Joint Science Return from LSST, Euclid and WFIRST
The focus of this report is on the opportunities enabled by the combination
of LSST, Euclid and WFIRST, the optical surveys that will be an essential part
of the next decade's astronomy. The sum of these surveys has the potential to
be significantly greater than the contributions of the individual parts. As is
detailed in this report, the combination of these surveys should give us
multi-wavelength high-resolution images of galaxies and broadband data covering
much of the stellar energy spectrum. These stellar and galactic data have the
potential of yielding new insights into topics ranging from the formation
history of the Milky Way to the mass of the neutrino. However, enabling the
astronomy community to fully exploit this multi-instrument data set is a
challenging technical task: for much of the science, we will need to combine
the photometry across multiple wavelengths with varying spectral and spatial
resolution. We identify some of the key science enabled by the combined surveys
and the key technical challenges in achieving the synergies.Comment: Whitepaper developed at June 2014 U. Penn Workshop; 28 pages, 3
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Time-Resolved Near-Infrared Photometry of Extreme Kuiper Belt Object Haumea
We present time-resolved near-infrared (J and H) photometry of the extreme
Kuiper belt object (136108) Haumea (formerly 2003 EL61) taken to further
investigate rotational variability of this object. The new data show that the
near-infrared peak-to-peak photometric range is similar to the value at visible
wavelengths, \Delta m_R = 0.30+/-0.02 mag. Detailed analysis of the new and
previous data reveals subtle visible/near-infrared color variations across the
surface of Haumea. The color variations are spatially correlated with a
previously identified surface region, redder in B-R and darker than the mean
surface. Our photometry indicates that the J-H colors of Haumea
(J-H=-0.057+/-0.016 mag) and its brightest satellite Hi'iaka
(J-H=-0.399+/-0.034 mag) are significantly (>9 sigma) different. The satellite
Hi'iaka is unusually blue in J-H, consistent with strong 1.5 micron water-ice
absorption. The phase coefficient of Haumea in the J-band is found to increase
monotonically with wavelength in the range 0.4<lambda<1.3. We compare our
findings with other Solar system objects and discuss implications regarding the
surface of Haumea.Comment: 10 pages, 10 figures, 6 tables. Accepted for publication in The
Astronomical Journal (2008 November 28
Evidence for Supernova-Synthesised Dust from the Rising Afterglow of GRB 071025 at z~5
We present observations and analysis of the broadband afterglow of Swift GRB
071025. Using optical and infrared (RIYJHK) photometry, we derive a photometric
redshift of 4.4 < z < 5.2; at this redshift our simultaneous multicolour
observations begin at ~30 s after the GRB trigger in the host frame and during
the initial rising phase of the afterglow. We associate the light curve peak at
580 s in the observer frame with the formation of the forward shock, giving an
estimate of the initial Lorentz factor Gamma_0 ~ 200. The red spectral energy
distribution (even in regions not affected by the Lyman-alpha break) provides
secure evidence of a large dust column. However, the inferred extinction curve
shows a prominent flat component between 2000-3000 Angstroms in the rest-frame,
inconsistent with any locally observed template but well-fit by models of dust
formed by supernovae. Time-dependent fits to the extinction profile reveal no
evidence of dust destruction and limit the decrease in the extinction column to
Delta A_3000 < 0.54 mag after t = 50 s in the rest frame. Our observations
provide evidence of a transition in dust properties at z~5, in agreement with
studies of high-z quasars, and suggest that SN-formed dust continues to
dominate the opacity of typical galaxies at this redshift.Comment: Resubmitted to MNRAS following referee report. Contains additional
figure and some extra analysis/discussio
Preattentive texture discrimination with early vision mechanisms
We present a model of human preattentive texture perception. This model consists of three stages: (1) convolution of the image with a bank of even-symmetric linear filters followed by half-wave rectification to give a set of responses modeling outputs of V1 simple cells, (2) inhibition, localized in space, within and among the neural-response profiles that results in the suppression of weak responses when there are strong responses at the same or nearby locations, and (3) texture-boundary detection by using wide odd-symmetric mechanisms. Our model can predict the salience of texture boundaries in any arbitrary gray-scale image. A computer implementation of this model has been tested on many of the classic stimuli from psychophysical literature. Quantitative predictions of the degree of discriminability of different texture pairs match well with experimental measurements of discriminability in human observers
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