Zobrazeno 1 - 10
of 1 033
pro vyhledávání: '"P. Slavomir"'
Learning the structure of Directed Acyclic Graphs (DAGs) presents a significant challenge due to the vast combinatorial search space of possible graphs, which scales exponentially with the number of nodes. Recent advancements have redefined this prob
Externí odkaz:
http://arxiv.org/abs/2410.23862
Autor:
Chen, Hao, Liu, Yun, Zhang, Hexin, Zhao, Shengdi, Nemsak, Slavomir, Liu, Haishan, Salmeron, Miquel
Precisely determining the oxidation states of metal cations within variable-valence transition metal oxides remains a significant challenge, yet it is crucial for understanding and predicting the properties of these technologically important material
Externí odkaz:
http://arxiv.org/abs/2409.15649
Autor:
Jaugstetter, Maximilian, Qi, Xiao, Chan, Emory, Salmeron, Miquel, Wilson, Kevin R., Nemšák, Slavomír, Bluhm, Hendrik
Functionalization and volatilization are competing reactions during the oxidation of carbonaceous materials and are important processes in many different areas of science and technology. Here we present a combined ambient pressure X-ray photoelectron
Externí odkaz:
http://arxiv.org/abs/2407.00598
Autor:
Matte, Livia P., Jaugstetter, Maximilian, Mishra, Tara P., Escudero, Carlos, Conti, Giuseppina, Nemsak, Slavomir, Bernardi, Fabiano
Hydrogen is a promising alternative to fossil fuel, however storing it efficiently poses challenges. One promising solution is to adsorb hydrogen on solid materials demonstrating quasi-molecular bonding with hydrogen. The hydrogen adsorption energy c
Externí odkaz:
http://arxiv.org/abs/2406.06752
This paper investigates the global convergence of stepsized Newton methods for convex functions with H\"older continuous Hessians or third derivatives. We propose several simple stepsize schedules with fast global convergence guarantees, up to $\math
Externí odkaz:
http://arxiv.org/abs/2405.18926
The global food delivery market provides many opportunities for AI-based services that can improve the efficiency of feeding the world. This paper presents the Cloud Kitchen platform as a decision-making tool for restaurants with food delivery and a
Externí odkaz:
http://arxiv.org/abs/2402.10725
Classical neural networks achieve only limited convergence in hard problems such as XOR or parity when the number of hidden neurons is small. With the motivation to improve the success rate of neural networks in these problems, we propose a new neura
Externí odkaz:
http://arxiv.org/abs/2401.06137
Autor:
Hanzely, Slavomír
Machine learning assumes a pivotal role in our data-driven world. The increasing scale of models and datasets necessitates quick and reliable algorithms for model training. This dissertation investigates adaptivity in machine learning optimizers. The
Externí odkaz:
http://arxiv.org/abs/2311.10203
Autor:
Hanzely, Slavomír
In this paper, we propose the first sketch-and-project Newton method with fast $\mathcal O(k^{-2})$ global convergence rate for self-concordant functions. Our method, SGN, can be viewed in three ways: i) as a sketch-and-project algorithm projecting u
Externí odkaz:
http://arxiv.org/abs/2305.13082
Autor:
Chen, Hao, Falling, Lorenz J., Kersell, Heath, Yan, George, Zhao, Xiao, Oliver-Meseguer, Judit, Nemsak, Slavomir, Hunt, Adrian, Waluyo, Iradwikanari, Ogasawara, Hirohito, Bell, Alexis, Sautet, Philippe, Salmeron, Miquel
Using CoOx thin films supported on Au(111) single crystal surfaces as model catalysts for the CO oxidation reaction we show that three reaction regimes exist in response to chemical and topographic restructuring of the CoOx catalyst as a function of
Externí odkaz:
http://arxiv.org/abs/2304.13859