Commercial detection in news broadcast videos involves judicious selection of meaningful audio-visual feature combinations and efficient classifiers. And, this problem becomes much simpler if these combinations can be learned from the data. To this end, we propose an Multiple Kernel Learning based method for boosting successful kernel functions while ignoring the irrelevant ones. We adopt a int...

In this paper we study the estimation of a quantile function based on left truncated and right censored data by the kernel smoothing method. Asymptotic normality and a Berry-Esseen type bound for the kernel quantile estimator are derived. Monte Carlo studies are conducted to compare the proposed estimator with the PL-quantile estimator.

We derive an elementary formula for Janossy densities for determinantal point processes with a finite rank projection-type kernel. In particular, for β = 2 polynomial ensembles of random matrices we show that the Janossy densities on an interval I ⊂ R can be expressed in terms of the Christoffel-Darboux kernel for the orthogonal polynomials on the complement of I.

We derive an elementary formula for Janossy densities for determinantal point processes with a finite rank projection-type kernel. In particular, for β = 2 polynomial ensembles of random matrices we show that the Janossy densities on an interval I ⊂ R can be expressed in terms of the Christoffel-Darboux kernel for the orthogonal polynomials on the complement of I.

Modern monolithic OSes leverage the loadable kernel module paradigm to add functionality to the kernel and allow a system to communicate with an increasing number of I/O devices. This paradigm is convenient as OS designers can outsource extra functionality to third parties and keep the original kernel from growing too large. On the other hand, this paradigm represents an avenue for exploitation...

In this paper we study a question related to the continuity of maximal operators convolution type acting on W1,1(ℝ). We prove that map u ↦ (u*)′ is continuous from W1,1(ℝ) L1(ℝ), where u* function associated Poisson kernel, Heat kernel or family kernels fractional Laplacian. This first result for centered operator.

A common type of memory error in the Linux kernel is using uninitialized variables (uninitialized use). Uninitialized uses not only cause undefined behaviors but also impose a severe security risk if an attacker takes control of the uninitialized variables. However, reliably exploiting uninitialized uses on the kernel stack has been considered infeasible until now since the code executed prior ...

By means of real analysis and weight functions, we obtain a few equivalent conditions of two kinds of Hardy-type integral inequalities with the non-homogeneous kernel and parameters. The constant factors related to the gamma function are proved to be the best possible. We also consider the operator expressions and some cases of homogeneous kernel.