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We consider robust optimization problems, where the goal is to optimize an unknown objective function against the worst-case realization of an uncertain parameter. For this setting, we design a novel sample-efficient algorithm GP-MRO, which sequentially le ...
The state-of-the-art RF and millimeterwave circuits design requires accurate prediction of the nonquasi-static (NQS) effects at high frequency for all levels of channel inversion. This paper provides a practical insight to help high-frequency performance a ...
Engineered fibrous tissues consisting of cells encapsulated within collagen gels are widely used three-dimensional (3D) in vitro models of morphogenesis and wound healing. While cell-mediated matrix remodeling that occurs within these scaffolds has been ex ...
The abatement of organic micropollutants during oxidation processes has become an emerging issue for various urban water systems such as drinking water, wastewater, and water reuse. Reaction kinetics and mechanisms play an important role in terms of effici ...
We consider multiagent decision making where each agent optimizes its convex cost function subject to individual and coupling constraints. The constraint sets are compact convex subsets of a Euclidean space. To learn Nash equilibria, we propose a novel dis ...
We present an end-to-end deep Convolutional Neural Network called Convolutional Relational Machine (CRM) for recognizing group activities that utilizes the information in spatial relationsbetween individualpersons in image or video. It learns to produce an ...
Structural testing is probably the best and only way to reveal the actual performance of composite laminates, structural components, and complete composite structures under fatigue loading. Nevertheless, the high cost, and the multitude of loading cases a ...
A fluid droplet suspended in an extensional flow of moderate intensity may break into pieces, depending on the amplitude of the initial droplet deformation. In subcritical uniaxial extensional flow the nonbreaking base state is linearly stable, implying th ...
This paper examines a stochastic formulation of the generalized Nash equilibrium problem where agents are subject to randomness in the environment of unknown statistical distribution. We focus on fully distributed online learning by agents and employ penal ...
In the past few years quantification of fluorescently labeled (bio-) molecules has become of increasing importance and several approaches have been developed to address this task. Counting by photon statistics measures the distribution of multiple photon d ...