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In this paper, we propose a novel selective search method to speed up the object detection via category-based attention scheme. The proposed attentional searching strategy is designed to focus on a small set of selected regions where the object category is ...
Compressed sensing is a new trend in signal processing for efficient sampling and signal acquisition. The idea is that most real-world signals have a sparse representation in an appropriate basis and this can be exploited to capture the sparse signal by ta ...
We study the steady-state probability distribution of diffusion and consensus strategies that employ constant step-sizes to enable continuous adaptation and learning. We show that, in the small step-size regime, the estimation error at each agent approache ...
In recent years we are experiencing a dramatic increase in the amount of available time-series data. Primary sources of time-series data are sensor networks, medical monitoring, financial applications, news feeds and social networking applications. Availab ...
This paper presents a novel probabilistic framework for localizing multiple speakers with a microphone array. In this framework, the generalized cross correlation function (GCC) of each microphone pair is interpreted as a probability distribution of the ti ...
In this work we apply the Continuation Multi-Level Monte Carlo (C-MLMC) algorithm proposed by [Collier et al, BIT 2014] to efficiently propagate operational and geometrical uncertainties in compressible aerodynamics numerical simulations. The key idea of M ...
We extend the classical empirical interpolation method to a weighted empirical interpolation method in order to approximate nonlinear parametric functions with weighted parameters, e.g. random variables obeying various probability distributions. A priori c ...
Distributionally robust optimization is a paradigm for decision-making under uncertainty where the uncertain problem data is governed by a probability distribution that is itself subject to uncertainty. The distribution is then assumed to belong to an ambi ...
A novel methodology consisting of three hierarchical levels is proposed for the detection phase of contact mechanics simulations. The top level of the hierarchy uses kinematic information from the objects involved in the simulation to determine approximate ...
The max-product algorithm, a local message-passing scheme that attempts to compute the most probable assignment (MAP) of a given probability distribution, has been successfully employed as a method of approximate inference for applications arising in codin ...
