Zobrazeno 1 - 10
of 979
pro vyhledávání: '"REITER, MICHAEL A."'
Autor:
Weijler, Lisa, Reiter, Michael, Hermosilla, Pedro, Maurer-Granofszky, Margarita, Dworzak, Michael
This paper evaluates various deep learning methods for measurable residual disease (MRD) detection in flow cytometry (FCM) data, addressing questions regarding the benefits of modeling long-range dependencies, methods of obtaining global information,
Externí odkaz:
http://arxiv.org/abs/2411.15621
Cryptocurrency introduces usability challenges by requiring users to manage signing keys. Popular signing key management services (e.g., custodial wallets), however, either introduce a trusted party or burden users with managing signing key shares, p
Externí odkaz:
http://arxiv.org/abs/2407.16473
Auditing the use of data in training machine-learning (ML) models is an increasingly pressing challenge, as myriad ML practitioners routinely leverage the effort of content creators to train models without their permission. In this paper, we propose
Externí odkaz:
http://arxiv.org/abs/2407.15100
Autor:
Lygizou, Elpiniki Maria, Reiter, Michael, Maurer-Granofszky, Margarita, Dworzak, Michael, Grosu, Radu
Acute Leukemia is the most common hematologic malignancy in children and adolescents. A key methodology in the diagnostic evaluation of this malignancy is immunophenotyping based on Multiparameter Flow Cytometry (FCM). However, this approach is manua
Externí odkaz:
http://arxiv.org/abs/2406.18309
Autor:
Reiter, Michael, Son, Duong Ngoc
We determine all CR maps from the sphere in $\mathbb{C}^3$ into the tube over the future light cone in $\mathbb{C}^4$. This result leads to a complete characterization of proper holomorphic maps from the three-dimensional unit ball into the classical
Externí odkaz:
http://arxiv.org/abs/2406.16428
Autor:
Sheng, Peiyao, Wu, Chenyuan, Malkhi, Dahlia, Reiter, Michael K., Stathakopoulou, Chrysoula, Wei, Michael, Yin, Maofan
This paper introduces and develops the concept of ``ticketing'', through which atomic broadcasts are orchestrated by nodes in a distributed system. The paper studies different ticketing regimes that allow parallelism, yet prevent slow nodes from hamp
Externí odkaz:
http://arxiv.org/abs/2407.00030
Federated Learning (FL) is a decentralized machine learning method that enables participants to collaboratively train a model without sharing their private data. Despite its privacy and scalability benefits, FL is susceptible to backdoor attacks, whe
Externí odkaz:
http://arxiv.org/abs/2405.06206
Autor:
Bandarupalli, Akhil, Bhat, Adithya, Bagchi, Saurabh, Kate, Aniket, Liu-Zhang, Chen-Da, Reiter, Michael K.
Agreement protocols are crucial in various emerging applications, spanning from distributed (blockchains) oracles to fault-tolerant cyber-physical systems. In scenarios where sensor/oracle nodes measure a common source, maintaining output within the
Externí odkaz:
http://arxiv.org/abs/2405.02431
Autor:
Reiter, Michael, Son, Duong Ngoc
In this paper, we study CR maps between hyperquadrics and Winkelmann hypersurfaces. Based on a previous study on the CR Ahlfors derivative of Lamel-Son and a recent result of Huang-Lu-Tang-Xiao on CR maps between hyperquadrics, we prove that a transv
Externí odkaz:
http://arxiv.org/abs/2404.16543
Foundation model has become the backbone of the AI ecosystem. In particular, a foundation model can be used as a general-purpose feature extractor to build various downstream classifiers. However, foundation models are vulnerable to backdoor attacks
Externí odkaz:
http://arxiv.org/abs/2402.14977