Related papers: Expected Limits on R-symmetric $\mu \to e $ Proces…
It has recently been shown that by measuring the transverse polarization of the final particles in the LFV processes $\mu \to e\gamma$, $\mu \to eee$ and $\mu N\to e N$, one can derive information on the CP-violating phases of the…
The electroweak (EW) sector of the Minimal Supersymmetric Standard Model (MSSM), with the lightest neutralino as Dark Matter (DM) candidate, can account for a variety of experimental data. This includes the DM content of the universe, DM…
The minimum error entropy (MEE) criterion has been verified as a powerful approach for non-Gaussian signal processing and robust machine learning. However, the implementation of MEE on robust classification is rather a vacancy in the…
Consider a measure $\mu_\lambda = \sum_x \xi_x \delta_x$ where the sum is over points $x$ of a Poisson point process of intensity $\lambda$ on a bounded region in $d$-space, and $\xi_x$ is a functional determined by the Poisson points near…
We study the convergence of the Expectation-Maximization (EM) algorithm for mixtures of linear regressions with an arbitrary number $k$ of components. We show that as long as signal-to-noise ratio (SNR) is $\tilde{\Omega}(k)$,…
Expectation-Maximization (EM) algorithm is a widely used iterative algorithm for computing (local) maximum likelihood estimate (MLE). It can be used in an extensive range of problems, including the clustering of data based on the Gaussian…
We study the Next-to-Minimal Supersymmetric Standard Model (NMSSM) as the simplest candidate solution to the $\mu$-problem in the context of the gauge mediation of supersymmetry breaking (GMSB). We first review various proposals to solve…
Experimental collaborations for the large hadron collider conducted many and various searches for supersymmetry. In the absence of signals, lower limits were put on sparticle masses but usually within frameworks with (over-) simplifications…
The Expectation-Maximization (EM) algorithm has been predominantly used to approximate the maximum likelihood estimation of the location-scale Gaussian mixtures. However, when the models are over-specified, namely, the chosen number of…
Consider the task of estimating a 3-order $n \times n \times n$ tensor from noisy observations of randomly chosen entries in the sparse regime. We introduce a similarity based collaborative filtering algorithm for estimating a tensor from…
In a few years, the COMET experiment at J-PARC and the Mu2e experiment at Fermilab will probe the $\mu-e$ conversion rate in the vicinity of $\mathcal{O}(10^{-17})$ for an Al target with high experimental sensitivity. Within the framework…
Between 1995-2000, the LEP e+e- collider has been operated above the Z0 peak, at centre-of-mass energies sqrt(s) = 130-209 GeV. Searches for supersymmetric particles have been performed using these data samples. The results from the four…
We study the loop-induced process e+e- --> W+H- in the Minimal Supersymmetric Standard Model (MSSM). This process allows the charged Higgs boson to be produced in e+e- collisions when its mass is larger than half the center-of-mass energy,…
We propose a minimum distance estimator (MDE) for parameter identification in misspecified models characterized by a sequence of ergodic stochastic processes that converge weakly to the model of interest. The data is generated by the…
We study the convergence behavior of the Expectation Maximization (EM) algorithm on Gaussian mixture models with an arbitrary number of mixture components and mixing weights. We show that as long as the means of the components are separated…
In the constrained MSSM one is typically able to restrict the supersymmetric mass spectra below roughly 1-2\tev\ {\em without} resorting to the ambiguous fine-tuning constraint.
We analyze the lepton flavor violating process $\mu-e$ conversion in the framework of the minimal R-symmetric supersymmetric standard model. The theoretical predictions are determined by considering the experimental constraint on parameter…
The persistent 3-4$\sigma$ discrepancy between the experimental result from BNL for the anomalous magnetic moment of the muon and its Standard Model (SM) prediction, was confirmed recently by the "MUON G-2" result from Fermilab. The…
This work provides performance guarantees for the greedy solution of experimental design problems. In particular, it focuses on A- and E-optimal designs, for which typical guarantees do not apply since the mean-square error and the maximum…
We consider distributed statistical optimization in one-shot setting, where there are $m$ machines each observing $n$ i.i.d. samples. Based on its observed samples, each machine sends a $B$-bit-long message to a server. The server then…