Zobrazeno 1 - 10
of 19 130
pro vyhledávání: '"A. Röder"'
Data integration has become increasingly common in aligning multiple heterogeneous datasets. With high-dimensional outcomes, data integration methods aim to extract low-dimensional embeddings of observations to remove unwanted variations, such as bat
Externí odkaz:
http://arxiv.org/abs/2410.04996
Autor:
Röder, Manuel, Schleif, Frank-Michael
This extended abstract explores the integration of federated learning with deep transfer hashing for distributed prediction tasks, emphasizing resource-efficient client training from evolving data streams. Federated learning allows multiple clients t
Externí odkaz:
http://arxiv.org/abs/2409.12575
Autor:
Srivastava, Nikit, Kuchelev, Denis, Ngoli, Tatiana Moteu, Shetty, Kshitij, Röder, Michael, Moussallem, Diego, Zahera, Hamada, Ngomo, Axel-Cyrille Ngonga
This paper presents LOLA, a massively multilingual large language model trained on more than 160 languages using a sparse Mixture-of-Experts Transformer architecture. Our architectural and implementation choices address the challenge of harnessing li
Externí odkaz:
http://arxiv.org/abs/2409.11272
Publikováno v:
The Semantic Web . ISWC 2022. ISWC 2022. Lecture Notes in Computer Science, vol 13489. Springer, Cham
We consider fact-checking approaches that aim to predict the veracity of assertions in knowledge graphs. Five main categories of fact-checking approaches for knowledge graphs have been proposed in the recent literature, of which each is subject to pa
Externí odkaz:
http://arxiv.org/abs/2409.06692
Autor:
Röder, Manuel, Schleif, Frank-Michael
We present a numerically robust, computationally efficient approach for non-I.I.D. data stream sampling in federated client systems, where resources are limited and labeled data for local model adaptation is sparse and expensive. The proposed method
Externí odkaz:
http://arxiv.org/abs/2408.17108
Autor:
Roeder, Franz, Gnanavel, Abira, Pollmann, René, Brecht, Olga, Stefszky, Michael, Padberg, Laura, Eigner, Christof, Silberhorn, Christine, Brecht, Benjamin
The latest applications in ultrafast quantum metrology require bright, broadband bi-photon sources with one of the photons in the mid-infrared and the other in the visible to near infrared. However, existing sources based on bulk crystals are limited
Externí odkaz:
http://arxiv.org/abs/2408.12203
Autor:
Watt, R., Kettle, B., Gerstmayr, E., King, B., Alejo, A., Astbury, S., Baird, C., Bohlen, S., Campbell, M., Colgan, C., Dannheim, D., Gregory, C., Harsh, H., Hatfield, P., Hinojosa, J., Hollatz, D., Katzir, Y., Morton, J., Murphy, C. D., Nurnberg, A., Osterhoff, J., Pérez-Callejo, G., Põder, K., Rajeev, P. P., Roedel, C., Roeder, F., Salgado, F. C., Samarin, G. M., Sarri, G., Seidel, A., Spindloe, C., Steinke, S., Streeter, M. J. V., Thomas, A. G. R., Underwood, C., Wu, W., Zepf, M., Rose, S. J., Mangles, S. P. D.
We report on a direct search for elastic photon-photon scattering using x-ray and $\gamma$ photons from a laser-plasma based experiment. A gamma photon beam produced by a laser wakefield accelerator provided a broadband gamma spectrum extending to ab
Externí odkaz:
http://arxiv.org/abs/2407.12915
Knowledge Graph Embedding (KGE) transforms a discrete Knowledge Graph (KG) into a continuous vector space facilitating its use in various AI-driven applications like Semantic Search, Question Answering, or Recommenders. While KGE approaches are effec
Externí odkaz:
http://arxiv.org/abs/2407.06855
With the evolution of single-cell RNA sequencing techniques into a standard approach in genomics, it has become possible to conduct cohort-level causal inferences based on single-cell-level measurements. However, the individual gene expression levels
Externí odkaz:
http://arxiv.org/abs/2404.09119
Quantitative measurements produced by mass spectrometry proteomics experiments offer a direct way to explore the role of proteins in molecular mechanisms. However, analysis of such data is challenging due to the large proportion of missing values. A
Externí odkaz:
http://arxiv.org/abs/2403.15802