Related papers: Expected Limits on R-symmetric $\mu \to e $ Proces…
We take a new look at parameter estimation for Gaussian Mixture Models (GMMs). In particular, we propose using \emph{Riemannian manifold optimization} as a powerful counterpart to Expectation Maximization (EM). An out-of-the-box invocation…
Contaminated mixture of experts (MoE) is motivated by transfer learning methods where a pre-trained model, acting as a frozen expert, is integrated with an adapter model, functioning as a trainable expert, in order to learn a new task.…
We calculate the region of the MSSM parameter space (i.e. $M_{1/2}$, $m_{0}$, $\mu$, \ldots) compatible with a correct electroweak breaking and a realistic top-quark mass. To do so we have included {\em all} the one-loop corrections to the…
New results of a search for the ultra-rare decay $\mu \to e \gamma$ by the MEG collaboration are reported in this contribution. The data were taken during 2009 and correspond to approximately 6.5 10$^{13}$ muon stopped on target. A maximum…
We study Radiative Electroweak Symmetry Breaking in the Minimal Supersymmetric Standard Model (MSSM). We employ the 2-loop Renormalization Group equations for running masses and couplings taking into account sparticle threshold effects. The…
Detailed derivations of two bounds of the minimum mean-square error (MMSE) of complex-valued multiple-input multiple-output (MIMO) systems are proposed for performance evaluation. Particularly, the lower bound is derived based on a…
We consider maximum likelihood estimation for Gaussian Mixture Models (Gmms). This task is almost invariably solved (in theory and practice) via the Expectation Maximization (EM) algorithm. EM owes its success to various factors, of which…
Machine learning models have traditionally been developed under the assumption that the training and test distributions match exactly. However, recent success in few-shot learning and related problems are encouraging signs that these models…
Starting from the new sources of $LL$- and $LR$- scalar (slepton) mixings due to R-parity violation, we discuss the structure of lepton-flavor violation focusing on the radiative decay of muon into electron. Using an optimal…
This paper investigates a general class of problems in which a lower bounded smooth convex function incorporating $\ell_{0}$ and $\ell_{2,0}$ regularization is minimized over a box constraint. Although such problems arise frequently in…
In this paper, tight upper and lower bounds are derived on the weighted sum of minimum mean-squared errors for additive Gaussian noise channels. The bounds are obtained by constraining the input distribution to be close to a Gaussian…
We present the results of a complete analysis of the one loop electroweak corrections to $e^-e^+\to\gamma\gamma, ~Z\gamma, ~ZZ$ in the Standard (SM) and the Minimal Supersymmetric Standard Model (MSSM). A special emphasis is put on the high…
We develop a unified statistical framework for softmax-gated Gaussian mixture of experts (SGMoE) that addresses three long-standing obstacles in parameter estimation and model selection: (i) non-identifiability of gating parameters up to…
When designing a preemptive online algorithm for the maximum matching problem, we wish to maintain a valid matching M while edges of the underlying graph are presented one after the other. When presented with an edge e, the algorithm should…
Physical quantities in QCD are independent of renormalization scheme (RS), but that exact invariance is spoiled by truncations of the perturbation series. "Optimization" corresponds to making the perturbative approximant, at any given…
New data on the lepton mixing angle $\theta_{13}$ imply that the $e\mu$ element of the matrix $m_\nu m_\nu^\dagger$, where $m_\nu$ is the neutrino Majorana mass matrix, cannot vanish. This implies a lower limit on lepton flavor violating…
It is now a firmly established fact that all family lepton numbers are violated in Nature. In this paper we discuss the implications of this observation for future searches for rare tau decays in the supersymmetric see-saw model. Using the…
We study the problem of selecting between different mechanisms of supersymmetry breaking in the Minimal Supersymmetric Standard Model using current data. We evaluate the Bayesian evidence of four supersymmetry breaking scenarios: mSUGRA,…
Mixture models, such as Gaussian mixture models, are widely used in machine learning to represent complex data distributions. A key challenge, especially in high-dimensional settings, is to determine the mixture order and estimate the…
We analyze the experimental data from the search for new particles at LEP 100 and obtain mass bounds for the neutralinos of the Next--To--Minimal Supersymmetric Standard Model (NMSSM). We find that for $\tan\beta \gsim 5.5$ a massless…