Zobrazeno 1 - 10
of 4 696
pro vyhledávání: '"Hendrickx, P."'
Autor:
Stehouwer, Lucas E. A., Yu, Cécile X., van Straaten, Barnaby, Tosato, Alberto, John, Valentin, Esposti, Davide Degli, Elsayed, Asser, Costa, Davide, Oosterhout, Stefan D., Hendrickx, Nico W., Veldhorst, Menno, Borsoi, Francesco, Scappucci, Giordano
Disorder in the heterogeneous material stack of semiconductor spin qubit systems introduces noise that compromises quantum information processing, posing a challenge to coherently control large-scale quantum devices. Here, we exploit low-disorder epi
Externí odkaz:
http://arxiv.org/abs/2411.11526
Autor:
Vizuete, Renato, Hendrickx, Julien M.
We analyze the identifiability of directed acyclic graphs in the case of partial excitation and measurement. We consider an additive model where the nonlinear functions located in the edges depend only on a past input, and we analyze the identifiabil
Externí odkaz:
http://arxiv.org/abs/2409.03559
Autor:
Rubbens, Anne, Hendrickx, Julien M.
We propose a novel approach to obtain interpolation constraints for a wide range of function classes, i.e. necessary and sufficient constraints that a set of points, functions values and (sub)gradients must satisfy to ensure the existence of a global
Externí odkaz:
http://arxiv.org/abs/2405.08405
Autor:
Vizuete, Renato, Hendrickx, Julien M.
We derive conditions for the identifiability of nonlinear networks characterized by additive dynamics at the level of the edges when all the nodes are excited. In contrast to linear systems, we show that the measurement of all sinks is necessary and
Externí odkaz:
http://arxiv.org/abs/2405.07636
Autor:
Colla, Sebastien, Hendrickx, Julien M.
We show that, in many settings, the worst-case performance of a distributed optimization algorithm is independent of the number of agents in the system, and can thus be computed in the fundamental case with just two agents. This result relies on a no
Externí odkaz:
http://arxiv.org/abs/2403.11724
Selecting the fastest algorithm for a specific signal/image processing task is a challenging question. We propose an approach based on the Performance Estimation Problem framework that numerically and automatically computes the worst-case performance
Externí odkaz:
http://arxiv.org/abs/2403.10209
Consider a sum of convex functions, where the only information known about each individual summand is the location of a minimizer. In this work, we give an exact characterization of the set of possible minimizers of the sum. Our results cover several
Externí odkaz:
http://arxiv.org/abs/2403.05467
Autor:
Wang, Chien-An, John, Valentin, Tidjani, Hanifa, Yu, Cécile X., Ivlev, Alexander S., Déprez, Corentin, van Riggelen-Doelman, Floor, Woods, Benjamin D., Hendrickx, Nico W., Lawrie, William I. L., Stehouwer, Lucas E. A., Oosterhout, Stefan D., Sammak, Amir, Friesen, Mark, Scappucci, Giordano, de Snoo, Sander L., Rimbach-Russ, Maximilian, Borsoi, Francesco, Veldhorst, Menno
Qubits that can be efficiently controlled are essential for the development of scalable quantum hardware. While resonant control is used to execute high-fidelity quantum gates, the scalability is challenged by the integration of high-frequency oscill
Externí odkaz:
http://arxiv.org/abs/2402.18382
Autor:
Colla, Sebastien, Hendrickx, Julien M.
We establish that in distributed optimization, the prevalent strategy of minimizing the second-largest eigenvalue modulus (SLEM) of the averaging matrix for selecting communication weights, while optimal for existing theoretical performance bounds, i
Externí odkaz:
http://arxiv.org/abs/2402.05705
Autor:
Hendrickx, Julien, Olshevsky, Alex
We consider the generalization error associated with stochastic gradient descent on a smooth convex function over a compact set. We show the first bound on the generalization error that vanishes when the number of iterations $T$ and the dataset size
Externí odkaz:
http://arxiv.org/abs/2401.04067