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On the influence of stochastic rounding bias in implementing gradient descent with applications in low-precision training – Lu Xia (Eindhoven University of Technology)

In the context of low-precision computation for the training of neural networks with thegradient descent method (GD), the occurrence of deterministic rounding errors often leadsto stagnation or adversely affects the convergence of the optimizers.…

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Stochastic probing methods for estimating the trace of functions of sparse symmetric matrices – Michele Rinelli (Scuola Normale Superiore)

We consider the combination of two approaches for the trace estimation of a symmetric matrix function f(A) when the only feasible operations are matrix-vector products and quadratic forms with f(A): stochastic estimators, such as the Hutchinson…

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Grassmann extrapolation of density matrices as a tool to accelerate Born-Oppenheimer molecular dynamics – Federica Pes (Università di Pisa)

Born-Oppenheimer molecular dynamics (BOMD) is a powerful but expensive technique. The main bottleneck in a density functional theory (DFT) BOMD calculation is the solution to the DFT nonlinear equations that requires an iterative procedure that…

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Model order reduction of parametric Hamiltonian systems on matrix manifolds – Cecilia Pagliantini (University of Pisa)

Model order reduction of parametric differential equations aims at constructing low-complexity high-fidelity surrogate models that allow rapid and accurate solutions under parameter variation. The development of reduced order models for Hamiltonian…

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COLLOQUIO DE GIORGI – Dirac and Lagrange structures in energy-based mathematical modeling – Volker Mehrmann (Technische Universität Berlin)

Most real world dynamical systems consist of subsystems from different physical domains, modelled by partial-differential equations, ordinary differential equations, and algebraic equations, combined with input and output connections.…

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