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High-dimensional sampling problems are ubiquitous in statistics, operations research, machine learning, etc. In this talk, I will introduce quantum algorithms for two important problems in high-dimens...
Graphs, a potentially extensive web of nodes connected by edges, can be used to express and interrogate relationships between data, like social connections, financial transactions, traffic, energy gri...
Physics-informed neural networks (PINNs) have emerged as an effective technique for solving PDEs in a wide range of domains. Recent research has demonstrated, however, that the performance of PINNs ca...
We propose a low-overhead sampling infrastructure for gathering information from the executions experienced by a program’s user community. Several example applications illustrate ways to use sampled i...
Many computer scientists think of a program as either correct (i.e. it meets some specification) or incorrect (i.e. it does not meet some specification). But industrial software development is as much...
Multipath potentially introduces a significant bias error into GPS code phase positioning solutions. That error is dependent on the amplitude, delay, phase, and phase rate of the multipath with respec...
In low bit rate video coding, the frame rate of input sequence can be reduced to the half or even smaller portion by skipping or deleting frames before compression, and then the temporal resolution is...
This paper deals with Bayesian inference and prediction problems of the Burr type XII distribution based on progressive first failure censored data. We consider the Bayesian inference under a squared ...
AbstractRay casting is a widely recognized method for high quality volume rendering. It traverses and samples the volume data ray by ray in image space. Traditionally, the algorithm is implemented in ...
In Sign Language recognition, one of the problems is to collect enough data. Data collection for both training and testing is a laborious but necessary step. Almost all of the statistical methods used...
A new approach to software reliability estimation is presented that combines operational testing with stratified sampling in order to reduce the number of program executions that must be checked man...

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