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On matrix estimation under monotonicity constraints
We consider the problem of estimating an unknown $n_1 \times n_2$ matrix $\mathbf{\theta^*}$ from noisy observations under the constraint that $\mathbf{\theta}^*$ is nondecreasing in both rows andExpand
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MULTIWAVELENGTH CONSTRAINTS ON PULSAR POPULATIONS IN THE GALACTIC CENTER
The detection of radio pulsars within the central few parsecs of the Galaxy would provide a unique probe of the gravitational and magneto-ionic environments in the Galactic center (GC) and, if closeExpand
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Isotonic regression in general dimensions
We study the least squares regression function estimator over the class of real-valued functions on $[0,1]^d$ that are increasing in each coordinate. For uniformly bounded signals and with a fixed,Expand
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Adaptive Risk Bounds in Univariate Total Variation Denoising and Trend Filtering
We study trend filtering, a relatively recent method for univariate nonparametric regression. For a given positive integer $r$, the $r$-th order trend filtering estimator is defined as the minimizerExpand
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Estimation in Tournaments and Graphs Under Monotonicity Constraints
TLDR
We propose a natural estimator which bypasses the need to search over all possible latent permutations and hence is computationally tractable. Expand
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Spatial Adaptation in Trend Filtering
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Adaptive Risk Bounds in Unimodal Regression
We study the statistical properties of the least squares estimator in unimodal sequence estimation. Although closely related to isotonic regression, unimodal regression has not been as extensivelyExpand
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Optimal Frequency Ranges for Submicrosecond Precision Pulsar Timing
Precision pulsar timing requires optimization against measurement errors and astrophysical variance from the neutron stars themselves and the interstellar medium. We investigate optimization ofExpand
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Opto-thermal analysis of a lightweighted mirror for solar telescope.
In this paper, an opto-thermal analysis of a moderately heated lightweighted solar telescope mirror is carried out using 3D finite element analysis (FEA). A physically realistic heat transfer modelExpand
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An Improved Global Risk Bound in Concave Regression
A new risk bound is presented for the problem of convex/concave function estimation, using the least squares estimator. The best known risk bound, as had appeared in \citet{GSvex}, scaled likeExpand
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