Search Results for author:
Found 8 papers, 2 papers with code
A survey of some recent developments in measures of association
This paper surveys some recent developments in measures of association related to a new coefficient of correlation introduced by the author.
Estimating large causal polytrees from small samples
We consider the problem of estimating a large causal polytree from a relatively small i. i. d.
MOSPAT: AutoML based Model Selection and Parameter Tuning for Time Series Anomaly Detection
Organizations leverage anomaly and changepoint detection algorithms to detect changes in user behavior or service availability and performance.
Convergence of gradient descent for deep neural networks
This article presents a criterion for convergence of gradient descent to a global minimum, which is then used to show that gradient descent with proper initialization converges to a global minimum when training any feedforward neural network with smooth and strictly increasing activation functions, provided that the input dimension is greater than or equal to the number of data points.
Micro-Estimates of Wealth for all Low- and Middle-Income Countries
Many critical policy decisions, from strategic investments to the allocation of humanitarian aid, rely on data about the geographic distribution of wealth and poverty.
The Observed Rate of Binary Black Hole Mergers can be Entirely Explained by Globular Clusters
Since the first signal in 2015, the gravitational-wave detections of merging binary black holes (BBHs) by the LIGO and Virgo collaborations (LVC) have completely transformed our understanding of the lives and deaths of compact object binaries, and have motivated an enormous amount of theoretical work on the astrophysical origin of these objects.
High Energy Astrophysical Phenomena General Relativity and Quantum Cosmology
A new coefficient of correlation
Is it possible to define a coefficient of correlation which is (a) as simple as the classical coefficients like Pearson's correlation or Spearman's correlation, and yet (b) consistently estimates some simple and interpretable measure of the degree of dependence between the variables, which is 0 if and only if the variables are independent and 1 if and only if one is a measurable function of the other, and (c) has a simple asymptotic theory under the hypothesis of independence, like the classical coefficients?
Statistics Theory Probability Statistics Theory 62H20, 62H15
Matrix estimation by Universal Singular Value Thresholding
Consider the problem of estimating the entries of a large matrix, when the observed entries are noisy versions of a small random fraction of the original entries.
Statistics Theory Probability Statistics Theory
