Zobrazeno 1 - 10
of 1 033
pro vyhledávání: '"DEMIDOVICH, A. A."'
Autor:
Demidovich, Yury, Ostroukhov, Petr, Malinovsky, Grigory, Horváth, Samuel, Takáč, Martin, Richtárik, Peter, Gorbunov, Eduard
Non-convex Machine Learning problems typically do not adhere to the standard smoothness assumption. Based on empirical findings, Zhang et al. (2020b) proposed a more realistic generalized $(L_0, L_1)$-smoothness assumption, though it remains largely
Externí odkaz:
http://arxiv.org/abs/2412.02781
Autor:
Wagner, Rene, Ilchen, Markus, Douguet, Nicolas, Schmidt, Philipp, Wieland, Niclas, Callegari, Carlo, Delk, Zachary, Demidovich, Alexander, Di Fraia, Michele, Hofbrucker, Jiri, Manfredda, Michele, Music, Valerija, Plekan, Oksana, Prince, Kevin C., Rivas, Daniel E., Zangrando, Marco, Grum-Grzhimailo, Alexei N., Bartschat, Klaus, Meyer, Michael
The circular dichroism (CD) of photoelectrons generated by near-infrared (NIR) laser pulses using multiphoton ionization of excited He$^+$ ions in the 3p(m=+1) state. The ions were prepared by circularly polarized extreme ultraviolet (XUV) pulses. Fo
Externí odkaz:
http://arxiv.org/abs/2407.14227
This paper presents a comprehensive analysis of a broad range of variations of the stochastic proximal point method (SPPM). Proximal point methods have attracted considerable interest owing to their numerical stability and robustness against imperfec
Externí odkaz:
http://arxiv.org/abs/2405.15941
In this study, we investigate stochastic optimization on Riemannian manifolds, focusing on the crucial variance reduction mechanism used in both Euclidean and Riemannian settings. Riemannian variance-reduced methods usually involve a double-loop stru
Externí odkaz:
http://arxiv.org/abs/2403.06677
Autor:
Richter, Fabian, Saalmann, Ulf, Allaria, Enrico, Wollenhaupt, Matthias, Ardini, Benedetto, Brynes, Alexander, Callegari, Carlo, Cerullo, Giulio, Danailov, Miltcho, Demidovich, Alexander, Dulitz, Katrin, Feifel, Raimund, Di Fraia, Michele, Ganeshamandiram, Sarang Dev, Giannessi, Luca, Gölz, Nicolai, Hartweg, Sebastian, von Issendorff, Bernd, Laarmann, Tim, Landmesser, Friedemann, Li, Yilin, Manfredda, Michele, Manzoni, Cristian, Michelbach, Moritz, Morlok, Arne, Mudrich, Marcel, Ngai, Aaron, Nikolov, Ivaylo, Pal, Nitish, Pannek, Fabian, Penco, Giuseppe, Plekan, Oksana, Prince, Kevin C., Sansone, Giuseppe, Simoncig, Alberto, Stienkemeier, Frank, Squibb, Richard James, Susnjar, Peter, Trovo, Mauro, Uhl, Daniel, Wouterlood, Brendan, Zangrando, Marco, Bruder, Lukas
Tailored light-matter interactions in the strong coupling regime enable the manipulation and control of quantum systems with up to unit efficiency, with applications ranging from quantum information to photochemistry. While strong light-matter intera
Externí odkaz:
http://arxiv.org/abs/2403.01835
Quantization (Alistarh et al., 2017) is an important (stochastic) compression technique that reduces the volume of transmitted bits during each communication round in distributed model training. Suresh et al. (2022) introduce correlated quantizers an
Externí odkaz:
http://arxiv.org/abs/2401.05518
Autor:
René Wagner, Markus Ilchen, Nicolas Douguet, Philipp Schmidt, Niclas Wieland, Carlo Callegari, Zachary Delk, Alexander Demidovich, Giovanni De Ninno, Michele Di Fraia, Jiri Hofbrucker, Michele Manfredda, Valerija Music, Oksana Plekan, Kevin C. Prince, Daniel E. Rivas, Marco Zangrando, Alexei N. Grum-Grzhimailo, Klaus Bartschat, Michael Meyer
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract The circular dichroism (CD) of photoelectrons generated by near-infrared (NIR) laser pulses using multiphoton ionization of excited He+ ions in the 3p(m= +1) state is investigated. The ions were prepared by circularly polarized extreme ultra
Externí odkaz:
https://doaj.org/article/c07fbb36a37d423fbc06063747493ca4
A $k$-deck of a (coloured) graph is a multiset of its induced $k$-vertex subgraphs. Given a graph $G$, when is it possible to reconstruct with high probability a uniformly random colouring of its vertices in $r$ colours from its $k$-deck? In this pap
Externí odkaz:
http://arxiv.org/abs/2308.01671
Stochastic Gradient Descent (SGD) is arguably the most important single algorithm in modern machine learning. Although SGD with unbiased gradient estimators has been studied extensively over at least half a century, SGD variants relying on biased est
Externí odkaz:
http://arxiv.org/abs/2305.16296
Autor:
Langbehn, Bruno, Ovcharenko, Yevheniy, Clark, Andrew, Coreno, Marcello, Cucini, Riccardo, Demidovich, Alexander, Drabbels, Marcel, Finetti, Paola, Di Fraia, Michele, Giannessi, Luca, Grazioli, Cesare, Iablonskyi, Denys, LaForge, Aaron C., Nishiyama, Toshiyuki, de Lara, Verónica Oliver Álvarez, Peltz, Christian, Piseri, Paolo, Plekan, Oksana, Sander, Katharina, Ueda, Kiyoshi, Fennel, Thomas, Prince, Kevin C., Stienkemeier, Frank, Callegari, Carlo, Möller, Thomas, Rupp, Daniela
Publikováno v:
New J. Phys. 24, 113043 (2022)
We have explored the light induced dynamics in superfluid helium nanodroplets with wide-angle scattering in a pump-probe measurement scheme. The droplets are doped with xenon atoms to facilitate the ignition of a nanoplasma through irradiation with n
Externí odkaz:
http://arxiv.org/abs/2205.04154