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In my thesis, I reveal several already-existing and emerging challenges in multi-objective management of multiprocessor systems, and address them through novel solutions, from heuristics to RL, depending on the complexity of the problem. Conventional multi ...
The applicability of two Reduced-Basis techniques to parametric laminar and turbulent incompressible fluid flow problems in nuclear engineering is studied in this work. The Reduced-Basis methods are used to generate Reduced-Order Models (ROMs) that can acc ...
Deep neural networks often have millions of parameters. This can hinder their deployment to low-end devices, not only due to high memory requirements but also because of increased latency at inference. We propose a novel model compression method that gener ...
Standard analysis pipelines for measurements of Baryon Acoustic Oscillations (BAO) in galaxy surveys make use of a fiducial cosmological model to guide the data compression required to transform from observed redshifts and angles to the measured angular an ...
Second-order information, in the form of Hessian- or Inverse-Hessian-vector products, is a fundamental tool for solving optimization problems. Recently, there has been a tremendous amount of work on utilizing this information for the current compute and me ...
Recent advances in signal processing, machine learning and deep learning with sparse intrinsic structure of data have paved the path for solving inverse problems in acoustics and audio. The main task of this thesis was to bridge the gap between the powerfu ...
We present and analyze a novel wavelet-Fourier technique for the numerical treatment of multidimensional advection–diffusion–reaction equations based on the COmpRessed SolvING (CORSING) paradigm. Combining the Petrov–Galerkin technique with the compressed ...
In distributed optimization and machine learning, multiple nodes coordinate to solve large problems. To do this, the nodes need to compress important algorithm information to bits so that it can be communicated over a digital channel. The communication tim ...
JPEG image coding standard has been a dominant format in a wide range of applications in soon three decades since it has been released as an international standard. The landscape of applications and services based on pictures has evolved since the original ...
A major line of work in graph signal processing [2] during the past 10 years has been to design new transform methods that account for the underlying graph structure to identify and exploit structure in data residing on a connected, weighted, undirected gr ...
