Novel Compact Three-Way Filtering Power Divider Using Net-Type Resonators

In this paper, we present a novel compact three-way power divider with bandpass responses. The proposed power divider utilizes folded net-type resonators to realize dual functions of filtering and power splitting as well as compact size. Equal power ratio with low magnitude imbalance is achieved due to the highly symmetric structure. For demonstration, an experimental three way filtering power divider is implemented. Good filtering and power division characteristics are observed in the measured results of the circuit. The area of the circuits is 14.5 mm x 21.9 mm or 0.16 λg x 0.24 λg, where the λg is the guide wavelength of the center frequency at 2.1 GHz

Field-aware Calibration: A Simple and Empirically Strong Method for Reliable Probabilistic Predictions

It is often observed that the probabilistic predictions given by a machine learning model can disagree with averaged actual outcomes on specific subsets of data, which is also known as the issue of miscalibration. It is responsible for the unreliability of practical machine learning systems. For example, in online advertising, an ad can receive a click-through rate prediction of 0.1 over some population of users where its actual click rate is 0.15. In such cases, the probabilistic predictions have to be fixed before the system can be deployed. In this paper, we first introduce a new evaluation metric named field-level calibration error that measures the bias in predictions over the sensitive input field that the decision-maker concerns. We show that existing post-hoc calibration methods have limited improvements in the new field-level metric and other non-calibration metrics such as the AUC score. To this end, we propose Neural Calibration, a simple yet powerful post-hoc calibration method that learns to calibrate by making full use of the field-aware information over the validation set. We present extensive experiments on five large-scale datasets. The results showed that Neural Calibration significantly improves against uncalibrated predictions in common metrics such as the negative log-likelihood, Brier score and AUC, as well as the proposed field-level calibration error.Comment: WWW 202

An inexact linearized proximal algorithm for a class of DC composite optimization problems and applications

This paper is concerned with a class of DC composite optimization problems which, as an extension of the convex composite optimization problem and the DC program with nonsmooth components, often arises from robust factorization models of low-rank matrix recovery. For this class of nonconvex and nonsmooth problems, we propose an inexact linearized proximal algorithm (iLPA) which in each step computes an inexact minimizer of a strongly convex majorization constructed by the partial linearization of their objective functions. The generated iterate sequence is shown to be convergent under the Kurdyka-{\L}ojasiewicz (KL) property of a potential function, and the convergence admits a local R-linear rate if the potential function has the KL property of exponent $1/2$ at the limit point. For the latter assumption, we provide a verifiable condition by leveraging the composite structure, and clarify its relation with the regularity used for the convex composite optimization. Finally, the proposed iLPA is applied to a robust factorization model for matrix completions with outliers, DC programs with nonsmooth components, and $\ell_1$-norm exact penalty of DC constrained programs, and numerical comparison with the existing algorithms confirms the superiority of our iLPA in computing time and quality of solutions

Searching for lepton portal dark matter with colliders and gravitational waves

We study the lepton portal dark matter (DM) model in which the relic abundance is determined by the portal coupling among the Majorana fermion DM candidate $\chi$, the singlet charged scalar mediator $S^\pm$ and the Standard Model (SM) right-handed lepton. The direct and indirect searches are not sensitive to this model. This article studies the lepton portal coupling as well as the scalar portal coupling (between $S^\pm$ and SM Higgs boson), as the latter is generally allowed in the Lagrangian. The inclusion of scalar portal coupling not only significantly enhances the LHC reach via the $gg\to h^*\to S^+S^-$ process, but also provides a few novel signal channels, such as the exotic decays and coupling deviations of the Higgs boson, offering new opportunities to probe the model. In addition, we also study the Drell-Yan production of $S^+S^-$ at future lepton colliders, and find out that the scenario where one $S^\pm$ is off-shell can be used to measure the lepton portal coupling directly. In particular, we are interested in the possibility that the scalar potential triggers a first-order phase transition and hence provides the stochastic gravitational wave (GW) signals. In this case, the terrestrial collider experiments and space-based GW detectors serve as complementary approaches to probe the model.Comment: 23 pages+references, 15 figures. To appear on JHE