Zobrazeno 1 - 10
of 96
pro vyhledávání: '"Oberhauser H"'
Publikováno v:
Annals of Applied Probability 2013, Vol. 23, No. 5, 2139-2160
In the late seventies, Clark [In Communication Systems and Random Process Theory (Proc. 2nd NATO Advanced Study Inst., Darlington, 1977) (1978) 721-734, Sijthoff & Noordhoff] pointed out that it would be natural for $\pi_t$, the solution of the stoch
Externí odkaz:
http://arxiv.org/abs/1201.1858
Autor:
Oberhauser, H, Schell, A
We study the classical problem of recovering a multidimensional source signal from observations of nonlinear mixtures of this signal. We show that this recovery is possible (up to a permutation and monotone scaling of the source's original component
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1064::5020e58903c0506f229bd6b66e17db67
https://ora.ox.ac.uk/objects/uuid:fc62975f-364b-4c2f-819e-8ec1e9da078b
https://ora.ox.ac.uk/objects/uuid:fc62975f-364b-4c2f-819e-8ec1e9da078b
Autor:
Bonnier, P, Oberhauser, H
Many forecasts consist not of point predictions but concern the evolution of quantities. For example, a central bank might predict the interest rates during the next quarter, an epidemiologist might predict trajectories of infection rates, a clinicia
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ca0f2f56c7f4d6410009699d91c2d592
https://doi.org/10.48550/arxiv.2111.06314
https://doi.org/10.48550/arxiv.2111.06314
Consider a set of points sampled independently near a smooth compact submanifold of Euclidean space. We provide mathematically rigorous bounds on the number of sample points required to estimate both the dimension and the tangent spaces of that manif
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aa4ebecc43025039dc28adf44185a3e6
https://ora.ox.ac.uk/objects/uuid:6aec487a-847d-4f58-8671-81facd82c3df
https://ora.ox.ac.uk/objects/uuid:6aec487a-847d-4f58-8671-81facd82c3df
A common approach for describing classes of functions and probability measures on a topological space $\mathcal{X}$ is to construct a suitable map $\Phi$ from $\mathcal{X}$ into a vector space, where linear methods can be applied to address both prob
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e2bbb2a0bc7f6ea32bf347ce746eabee
https://doi.org/10.48550/arxiv.2202.00491
https://doi.org/10.48550/arxiv.2202.00491
Many problems require to optimize empirical risk functions over large data sets. Gradient descent methods that calculate the full gradient in every descent step do not scale to such datasets. Various flavours of Stochastic Gradient Descent (SGD) repl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f36ee2615002f67253397335b6ee2565
https://ora.ox.ac.uk/objects/uuid:6e5fa696-5eca-4767-884e-73dcfd4a5b66
https://ora.ox.ac.uk/objects/uuid:6e5fa696-5eca-4767-884e-73dcfd4a5b66
Publikováno v:
The Annals of Applied Probability, 2013 Oct 01. 23(5), 2139-2160.
Externí odkaz:
http://dx.doi.org/10.1214/12-AAP896
Autor:
Kaap-Fröhlich, S, Ulrich, G, Wershofen, B, Ahles, J, Behrend, R, Handgraaf, M, Herinek, D, Mitzkat, A, Oberhauser, H, Scherer, T, Schlicker, A, Straub, C, Waury Eichler, R, Wesselborg, B, Witti, M, Huber, M, Bode, SF
Publikováno v:
GMS Journal for Medical Education; VOL: 39; DOC17 /20220414/
In the wake of local initiatives and developmental funding programs, interprofessionality is now included in national curricula in the German-speaking countries. Based on the 3P model (presage, process, product), this position paper presents the deve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::14fc677ef1f7600df5704a3825600cf6
https://hdl.handle.net/11475/27318
https://hdl.handle.net/11475/27318
Given a probability measure $\mu$ on a set $\mathcal{X}$ and a vector-valued function $\varphi$, a common problem is to construct a discrete probability measure on $\mathcal{X}$ such that the push-forward of these two probability measures under $\var
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::55695c25b901eb93d1aacdc0dd2757d3
We revisit the classical problem of approximating a stochastic differential equation by a discrete-time and discrete-space Markov chain. Our construction iterates Caratheodory's theorem over time to match the moments of the increments locally. This a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::665e819e601650db8d12a294bc45b794
http://arxiv.org/abs/2111.03497
http://arxiv.org/abs/2111.03497