Zobrazeno 1 - 10
of 1 245
pro vyhledávání: '"P, Yurtsever"'
We introduce an extension of the Difference of Convex Algorithm (DCA) in the form of a block coordinate approach for problems with separable structure. For $n$ coordinate-blocks and $k$ iterations, our main result proves a non-asymptotic convergence
Externí odkaz:
http://arxiv.org/abs/2411.11664
Solving non-convex, NP-hard optimization problems is crucial for training machine learning models, including neural networks. However, non-convexity often leads to black-box machine learning models with unclear inner workings. While convex formulatio
Externí odkaz:
http://arxiv.org/abs/2410.22311
Autor:
Giri, K., González-Sánchez, L., Gianturco, F. A., Lourderaj, U., María, A. Martín Santa, Rana, S., Sathyamurthy, N., Yurtsever, E., Wester, R.
The anions C$_7$N$^-$ and C$_{10}$H$^-$ are the two longest of the linear (C,N)-bearing and (C,H)-bearing chains which have so far been detected in the Interstellar Medium. In order to glean information on their collision-induced rotational state-cha
Externí odkaz:
http://arxiv.org/abs/2409.12685
Federated learning (FL) has gained a lot of attention in recent years for building privacy-preserving collaborative learning systems. However, FL algorithms for constrained machine learning problems are still limited, particularly when the projection
Externí odkaz:
http://arxiv.org/abs/2408.10090
The key challenge of personalized federated learning (PerFL) is to capture the statistical heterogeneity properties of data with inexpensive communications and gain customized performance for participating devices. To address these, we introduced per
Externí odkaz:
http://arxiv.org/abs/2407.14251
Autor:
Liu, Mingyu, Yurtsever, Ekim, Brede, Marc, Meng, Jun, Zimmer, Walter, Zhou, Xingcheng, Zagar, Bare Luka, Cui, Yuning, Knoll, Alois
Accurate and effective 3D object detection is critical for ensuring the driving safety of autonomous vehicles. Recently, state-of-the-art two-stage 3D object detectors have exhibited promising performance. However, these methods refine proposals indi
Externí odkaz:
http://arxiv.org/abs/2405.06782
Recently, the rings whose injective right modules are R-projective (respectively, max-projective) were investigated and studied in [2]. Such ring are called right almost-QF (respectively, max-QF). In this paper, our aim is to give some further charac
Externí odkaz:
http://arxiv.org/abs/2404.01771
Principal Component Analysis (PCA) is one of the most commonly used statistical methods for data exploration, and for dimensionality reduction wherein the first few principal components account for an appreciable proportion of the variability in the
Externí odkaz:
http://arxiv.org/abs/2401.04797
Autor:
Liu, Mingyu, Yurtsever, Ekim, Fossaert, Jonathan, Zhou, Xingcheng, Zimmer, Walter, Cui, Yuning, Zagar, Bare Luka, Knoll, Alois C.
Autonomous driving has rapidly developed and shown promising performance due to recent advances in hardware and deep learning techniques. High-quality datasets are fundamental for developing reliable autonomous driving algorithms. Previous dataset su
Externí odkaz:
http://arxiv.org/abs/2401.01454
Publikováno v:
ACS Omega, Vol 9, Iss 46, Pp 45920-45925 (2024)
Externí odkaz:
https://doaj.org/article/00e9605823d3418281f2847ba06d5f98
