Zobrazeno 1 - 10
of 20
pro vyhledávání: '"H��llermeier, Eyke"'
Autor:
Rahnama, Javad, H��llermeier, Eyke
Publikováno v:
Information Processing and Management of Uncertainty in Knowledge-Based Systems
In this paper, we advocate Tversky's ratio model as an appropriate basis for computational approaches to semantic similarity, that is, the comparison of objects such as images in a semantically meaningful way. We consider the problem of learning Tver
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b85b2b31a87857184f8b9108c6682112
http://europepmc.org/articles/PMC7274714
http://europepmc.org/articles/PMC7274714
Autor:
Schneider, Stefanie, Springstein, Matthias, Rahnama, Javad, Kohle, Hubertus, Ewerth, Ralph, H��llermeier, Eyke
Mit iART wird eine offene Web-Plattform zur Suche in kunst- und kulturwissenschaftlichen Bildinventaren pr��sentiert, die von in den Geistes��wissenschaften etablierten Methoden wie dem Vergleichenden Sehen inspiriert ist. Das System integrie
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cfbb12ea9ae02734a0bfd79dd988535d
We study the non-stationary dueling bandits problem with $K$ arms, where the time horizon $T$ consists of $M$ stationary segments, each of which is associated with its own preference matrix. The learner repeatedly selects a pair of arms and observes
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::35b6cfe9ac9b0ede4020dffdf1021fa1
http://arxiv.org/abs/2202.00935
http://arxiv.org/abs/2202.00935
This paper elaborates on the notion of uncertainty in the context of annotation in large text corpora, specifically focusing on (but not limited to) historical languages. Such uncertainty might be due to inherent properties of the language, for examp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9b603c43604611c0efded727b7b7706f
http://arxiv.org/abs/2105.07270
http://arxiv.org/abs/2105.07270
We consider the problem of learning to choose from a given set of objects, where each object is represented by a feature vector. Traditional approaches in choice modelling are mainly based on learning a latent, real-valued utility function, thereby i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bc572a87c74871f082b00e17d8bef19a
http://arxiv.org/abs/2007.06927
http://arxiv.org/abs/2007.06927
Current GNN architectures use a vertex neighborhood aggregation scheme, which limits their discriminative power to that of the 1-dimensional Weisfeiler-Lehman (WL) graph isomorphism test. Here, we propose a novel graph convolution operator that is ba
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7060387a5b1502b9232c1a5ee60058a6
http://arxiv.org/abs/2007.00346
http://arxiv.org/abs/2007.00346
Autor:
Rapp, Michael, Menc��a, Eneldo Loza, F��rnkranz, Johannes, Nguyen, Vu-Linh, H��llermeier, Eyke
In multi-label classification, where the evaluation of predictions is less straightforward than in single-label classification, various meaningful, though different, loss functions have been proposed. Ideally, the learning algorithm should be customi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::61bc23a7ee963cc09abe7b1d6e4ca073
http://arxiv.org/abs/2006.13346
http://arxiv.org/abs/2006.13346
Micro- and smart grids (MSG) play an important role both for integrating renewable energy sources in conventional electricity grids and for providing power supply in remote areas. Modern MSGs are largely driven by power electronic converters due to t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7184e8fe207b80580ea98e5e22349ef1
http://arxiv.org/abs/2005.04869
http://arxiv.org/abs/2005.04869
Algorithm selection (AS) deals with selecting an algorithm from a fixed set of candidate algorithms most suitable for a specific instance of an algorithmic problem, e.g., choosing solvers for SAT problems. Benchmark suites for AS usually comprise can
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::719485f54f6c238a4b12b426b78d7649
http://arxiv.org/abs/2001.10741
http://arxiv.org/abs/2001.10741
Autor:
Bengs, Viktor, H��llermeier, Eyke
In this paper, we introduce the Preselection Bandit problem, in which the learner preselects a subset of arms (choice alternatives) for a user, which then chooses the final arm from this subset. The learner is not aware of the user's preferences, but
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0ad5a48a8226f26440b0149b27c5355c
http://arxiv.org/abs/1907.06123
http://arxiv.org/abs/1907.06123