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We consider in this paper the information retrieval problem over a collection of time-evolving documents such that the search has to be carried out based on a query text and a temporal specification. A solution to this ...

The sparse grid stochastic collocation method is a new method for solving partial differential equations with random coefficients. However, when the probability space has high dimensionality, the number of points required ...

Humans confront the unexpected every day, deal with it, and often learn from it. AI agents, on the other hand, are typically brittle—they tend to break down as soon as something happens for which their creators did not ...

An important way to learn new actions and behaviors is by observing others, and several evolutionary games have been developed to investigate what learning strategies work best and how they might have evolved. In this paper ...

Vortex-element methods are often used to efficiently simulate incompressible flows using Lagrangian techniques. Use of the FMM (Fast Multipole Method) allows considerable speed up of both velocity evaluation and vorticity ...

In linear stability analysis of a large-scale dynamical system, we need to compute the rightmost eigenvalue(s) for a series of large generalized eigenvalue problems. Existing iterative eigenvalue solvers are not robust ...

Understanding multicore memory behavior is crucial, but can be challenging due to the cache hierarchies employed in modern CPUs. In today's hierarchies, performance is determined by complex thread interactions, such as ...

We propose a learning-based method for detecting carried objects that generates candidate image regions from protrusion, color contrast and occlusion boundary cues, and uses a classifier to filter out the regions unlikely ...

Current high-throughput algorithms for constructing inverted files all follow the MapReduce framework, which presents a high-level programming model that hides the complexities of parallel programming. In this paper, ...