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pro vyhledávání: '"Schnurr, P P"'
While most ML models expect independent and identically distributed data, this assumption is often violated in real-world scenarios due to distribution shifts, resulting in the degradation of machine learning model performance. Until now, no tabular
Externí odkaz:
http://arxiv.org/abs/2411.10634
The symbolic correlation integral provides a way to measure the complexity of time series and dynamical systems. In the present article we prove limit results for an estimator of this quantity which is based on U-statistics under the assumption of sh
Externí odkaz:
http://arxiv.org/abs/2410.18726
Autor:
Adler, Steven, Hitzig, Zoë, Jain, Shrey, Brewer, Catherine, Chang, Wayne, DiResta, Renée, Lazzarin, Eddy, McGregor, Sean, Seltzer, Wendy, Siddarth, Divya, Soliman, Nouran, South, Tobin, Spelliscy, Connor, Sporny, Manu, Srivastava, Varya, Bailey, John, Christian, Brian, Critch, Andrew, Falcon, Ronnie, Flanagan, Heather, Duffy, Kim Hamilton, Ho, Eric, Leibowicz, Claire R., Nadhamuni, Srikanth, Rozenshtein, Alan Z., Schnurr, David, Shapiro, Evan, Strahm, Lacey, Trask, Andrew, Weinberg, Zoe, Whitney, Cedric, Zick, Tom
Anonymity is an important principle online. However, malicious actors have long used misleading identities to conduct fraud, spread disinformation, and carry out other deceptive schemes. With the advent of increasingly capable AI, bad actors can ampl
Externí odkaz:
http://arxiv.org/abs/2408.07892
Autor:
Aker, M., Batzler, D., Beglarian, A., Behrens, J., Beisenkötter, J., Biassoni, M., Bieringer, B., Biondi, Y., Block, F., Bobien, S., Böttcher, M., Bornschein, B., Bornschein, L., Caldwell, T. S., Carminati, M., Chatrabhuti, A., Chilingaryan, S., Daniel, B. A., Debowski, K., Descher, M., Barrero, D. Díaz, Doe, P. J., Dragoun, O., Drexlin, G., Edzards, F., Eitel, K., Ellinger, E., Engel, R., Enomoto, S., Felden, A., Fengler, C., Fiorini, C., Formaggio, J. A., Forstner, C., Fränkle, F. M., Gauda, K., Gavin, A. S., Gil, W., Glück, F., Grohmann, S., Grössle, R., Gumbsheimer, R., Gutknecht, N., Hannen, V., Hasselmann, L., Haußmann, N., Helbing, K., Henke, H., Heyns, S., Hickford, S., Hiller, R., Hillesheimer, D., Hinz, D., Höhn, T., Huber, A., Jansen, A., Karl, C., Kellerer, J., Khosonthongkee, K., Kleifges, M., Klein, M., Kohpeiß, J., Köhler, C., Köllenberger, L., Kopmann, A., Kovač, N., Kovalík, A., Krause, H., La Cascio, L., Lasserre, T., Lauer, J., Le, T., Lebeda, O., Lehnert, B., Li, G., Lokhov, A., Machatschek, M., Mark, M., Marsteller, A., Martin, E. L., Melzer, C., Mertens, S., Mohanty, S., Mostafa, J., Müller, K., Nava, A., Neumann, H., Niemes, S., Onillon, A., Parno, D. S., Pavan, M., Pinsook, U., Poon, A. W. P., Poyato, J. M. Lopez, Pozzi, S., Priester, F., Ráliš, J., Ramachandran, S., Robertson, R. G. H., Rodenbeck, C., Röllig, M., Röttele, C., Ryšavý, M., Sack, R., Saenz, A., Salomon, R., Schäfer, P., Schlösser, M., Schlösser, K., Schlüter, L., Schneidewind, S., Schnurr, U., Schrank, M., Schürmann, J., Schütz, A., Schwemmer, A., Schwenck, A., Šefčík, M., Siegmann, D., Simon, F., Spanier, F., Spreng, D., Sreethawong, W., Steidl, M., Štorek, J., Stribl, X., Sturm, M., Suwonjandee, N., Jerome, N. Tan, Telle, H. H., Thorne, L. A., Thümmler, T., Tirolf, S., Titov, N., Tkachev, I., Urban, K., Valerius, K., Vénos, D., Weinheimer, C., Welte, S., Wendel, J., Wiesinger, C., Wilkerson, J. F., Wolf, J., Wüstling, S., Wydra, J., Xu, W., Zadorozhny, S., Zeller, G.
The fact that neutrinos carry a non-vanishing rest mass is evidence of physics beyond the Standard Model of elementary particles. Their absolute mass bears important relevance from particle physics to cosmology. In this work, we report on the search
Externí odkaz:
http://arxiv.org/abs/2406.13516
When considering stochastic integration and the theory of stochastic differential equations, P. Protter's textbook \cite{protter} undoubtedly is a main piece of standard literature. Not only is it well-written, but it also contains various profound r
Externí odkaz:
http://arxiv.org/abs/2403.12613
We describe and analyze different approaches to represent ordinal patterns. All of these can be found in the literature. The most important representations (plus sub-classes) are compared in terms of their applicability from different angles. Namely
Externí odkaz:
http://arxiv.org/abs/2402.07478
Autor:
Betken, Annika, Schnurr, Alexander
We establish a definition of ordinal patterns for multivariate time series data based on the concept of Tukey's halfspace depth. Given the definition of these \emph{depth patterns}, we are interested in the probabilities of observing specific pattern
Externí odkaz:
http://arxiv.org/abs/2401.13532
Ordinal pattern dependence has been introduced in order to capture co-monotonic behavior between two time series. This concept has several features one would intuitively demand from a dependence measure. It was believed that ordinal pattern dependenc
Externí odkaz:
http://arxiv.org/abs/2401.13007
Autor:
Schnurr, Alexander, Fischer, Svenja
Publikováno v:
CSDA 171, 107472 (2022)
When using ordinal patterns, which describe the ordinal structure within a data vector, the problem of ties appeared permanently. So far, model classes were used which do not allow for ties; randomization has been another attempt to overcome this pro
Externí odkaz:
http://arxiv.org/abs/2401.12268
The probabilistic symbol is defined as the right-hand side derivative at time zero of the characteristic functions corresponding to the one-dimensional marginals of a time-homogeneous stochastic process. As described in various contributions to this
Externí odkaz:
http://arxiv.org/abs/2308.15801