We report non-zero weak lensing convergence correlation signal of Type-Ia supernovae from 5-year Supernovae Legacy Survey data. For our analysis we utilize 296 supernovae magnification data from 5-year SNLS in the weak lensing limit. The data we use consists of measurements from four different...

In this paper, we present a method to estimate the signal subspace at all the frequencies in a given band, which is computed from the usual set of frequency-bin sample covariance matrices in wideband subspace estimation. Fundamentally, the method exploits the similarity between the signal...

We develop a procedure to identify latent group structures in linear panel data models that exploits a grouping in the error variances of cross-sectional units. To accommodate such grouping, we introduce an objective function that avoids a singularity that arises in a pseudo-likelihood approach....

This paper proposes a recursive interval-valued estimation framework for identifying the parameters of linearly parameterized systems which may be slowly time-varying. It is assumed that the model error (which may consist in measurement noise or model mismatch or both) is unknown but lies at...

In this paper, we propose an efficient approach based on linear programming to study constrained stabilization problem of linear positive differential-difference equations with unbounded delay. We first propose new characterizations of the positivity of the equations, then delaydependent...

First-order convex optimization algorithms are popular due to their computational attractiveness and applicability to a wide range of domains such as machine learning and control. Despite the substantial progress being made over the last few decades, some open questions related to their...

In this paper, we propose a novel learning-based robust adaptive trajectory tracking controller for wheeled mobile robots (WMR) subject to velocity input uncertainties. Gaussian process regression (GPR) is employed in view of its powerful estimation ability and wide scope of applications as a...

Embrittlement of the reactor pressure vessel is one of the most crucial factors that limit the lifetime of a nuclear reactor, and it is traditionally determined using destructive methods. We demonstrate that machine learning algorithms can build models that estimate the embrittlement, which is...

In a recent article, George Pickering (2019) has taken issue with my work regarding the two potential ways one might deal with the regression theorem in light of bitcoin. Specifically, he argues that I misinterpret 'the purpose and requirements of the regression theorem' (p. 608). His critical...

Essential features of the multigrid Ensemble Kalman Filter (G. Moldovan , G. Lehnasch , L. Cordier , M. Meldi , A multigrid /ensemble Kalman filter strategy for assimilation of unsteady flows , Journal of Computational Physics 443-110481 ) recently proposed for Data Assimilation of fluid flows...