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Block-enhanced precision matrix estimation for large-scale datasets

Eftekhari, Aryan ; Pasadakis, Dimosthenis ; Bollhöfer, Matthias ; Scheidegger, Simon ; Schenk, Olaf

In: Journal of computational science, 2021, vol. 53, p. 13

The ℓ1-regularized Gaussian maximum likelihood method is a common approach for sparse precision matrix estimation, but one that poses a computational challenge for high-dimensional datasets. We present a novel ℓ1- regularized maximum likelihood method for performant large-scale sparse precision matrix estimation utilizing the block structures in the underlying computations. We identify the...

Constraint handling for gradient-based optimization of compositional reservoir flow

Kourounis, Drosos ; Schenk, Olaf

In: Computational Geosciences, 2015, vol. 19, no. 5, p. 1109-1122

Matching-based preprocessing algorithms to the solution of saddle-point problems in large-scale nonconvex interior-point optimization

Schenk, Olaf ; Wächter, Andreas ; Hagemann, Michael

In: Computational Optimization and Applications, 2007, vol. 36, no. 2-3, p. 321-341

Automatic code generation and tuning for stencil kernels on modern shared memory architectures

Christen, Matthias ; Schenk, Olaf ; Burkhart, Helmar

In: Computer Science - Research and Development, 2011, vol. 26, no. 3-4, p. 205-210

Parallel scalable PDE-constrained optimization: antenna identification in hyperthermia cancer treatment planning

Schenk, Olaf ; Manguoglu, Murat ; Sameh, Ahmed ; Christen, Matthias ; Sathe, Madan

In: Computer Science - Research and Development, 2009, vol. 23, no. 3-4, p. 177-183