Applications such as image processing, fluid mechanics, and weather forecasting require high computer performance. Researchers and designers in those areas are looking for solutions to multi-dimensional problems through the use of parallel computers and/or specialized hardware. It is known that in highly parallel computers communication is often the limiting execution speed bottleneck. While th...

This thesis describes some of the recent developments in multi-way analysis in the field of chemometrics. Originally, the primary purpose of this work was to test the adequacy of multi-way models in areas related to the food industry. However, during the course of this work, it became obvious that basic research is still called for. Hence, a fair part of the thesis describes methodological deve...

In the paper we derive and discuss a wide class of algorithms for 3D Super-symmetric nonnegative Tensor Factorization (SNTF) or nonnegative symmetric PARAFAC, and as a special case: Symmetric Nonnegative Matrix Factorization (SNMF) that have many potential applications, including multi-way clustering, feature extraction, multisensory or multi-dimensional data analysis, and nonnegative neural sp...

We should not have to look at the entire corpus (e.g., the Web) to know if two (or more) words are associated or not. A powerful sampling technique called Sketches was originally introduced to remove duplicate Web pages. We generalize sketches to estimate contingency tables and associations, using a maximum likelihood estimator to find the most likely contingency table given the sample, the mar...

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The amount of resources consumed for a complete and exhaustive testing becomes unreasonable and unaffordable. While it is vital to assure the quality and the reliability of any system, it is impossible to do an exhaustive testing due to the huge number of possible combinations. To bring a balance between exhaustive testing and lack of testing combinatorial interactions testing has been adopted....

We consider nonlinear filtering applications to target tracking based on a vector of multi-scaled models where some of the processes are rapidly mean reverting to their local equilibria. We focus attention on target tracking problems because multiple scaled models with fast mean-reversion (FMR) are a simple way to model latency in the response of tracking systems. The main results of this paper...

Sequential multi-constraint graph partitioners have been developed to address the static load balancing requirements of multi-phase simulations. These work well when (i) the graph that models the computation fits into the memory of a single processor, and (ii) the simulation does not require dynamic load balancing. The efficient execution of very large or dynamically adapting multi-phase simula...

Multi-agent learning refers to settings in which multiple agents learn simultaneously. Usually defined in a game theoretic setting, specifically in repeated games or stochastic games, the key feature that distinguishes multi-agent learning from single-agent learning is that in the former the learning of one agent impacts he learning of others. As a result neither the problem definition for mutl...