E-LIB Suche - Ergebnisse für: Schleif, Frank-Michael

1

Data-distribution-informed Nyström approximation for struct..:

Münch, Maximilian ; Bohnsack, Katrin Sophie ; Schleif, Frank-Michael.
Neurocomputing. 596 (2024) - p. 128100 , 2024

Link: https://doi.org/10.1016/..

2

A Streaming Approach to the Core Vector Machine:

, In: Artificial Intelligence and Soft Computing; Lecture Notes in Computer Science,

Heusinger, Moritz ; Schleif, Frank-Michael - p. 91-101 , 2023

Link: https://doi.org/10.1007/..

3

How Important is the Temporal Context to Anticipate Oncomin..:

, In: 2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC),

Ewecker, Lukas ; Winkler, Timo ; Vath, Philipp... - p. 1000-1007 , 2023

Link: https://doi.org/10.1109/..

4

Static and adaptive subspace information fusion for indefin..:

Münch, Maximilian ; Röder, Manuel ; Heilig, Simon..
Neurocomputing. 555 (2023) - p. 126635 , 2023

Link: https://doi.org/10.1016/..

5

Unlocking the Potential of Non-PSD Kernel Matrices: A Polar..:

, In: Proceedings of the 32nd ACM International Conference on Information and Knowledge Management,

Münch, Maximilian ; Röder, Manuel ; Schleif, Frank-Michael - p. 1867-1876 , 2023

Link: https://dl.acm.org/doi/1..

6

Domain adversarial tangent subspace alignment for explainab..:

Raab, Christoph ; Röder, Manuel ; Schleif, Frank-Michael
Neurocomputing. 506 (2022) - p. 418-429 , 2022

Link: https://doi.org/10.1016/..

7

Memory Efficient Kernel Approximation for Non-Stationary an..:

, In: 2022 International Joint Conference on Neural Networks (IJCNN),

Heilig, Simon ; Munch, Maximilian ; Schleif, Frank-Michael - p. 1-8 , 2022

Link: https://doi.org/10.1109/..

8

Advances in artificial neural networks, machine learning an..:

Oneto, Luca ; Navarin, Nicoló ; Schleif, Frank-Michael
Neurocomputing. 507 (2022) - p. 311-314 , 2022

Link: https://doi.org/10.1016/..

9

Bridging Adversarial and Statistical Domain Transfer via Sp..:

, In: Computer Vision – ACCV 2020; Lecture Notes in Computer Science,

Raab, Christoph ; Väth, Philipp ; Meier, Peter. - p. 457-473 , 2021

Link: https://doi.org/10.1007/..

10

Complex-Valued Embeddings of Generic Proximity Data:

, In: Lecture Notes in Computer Science; Structural, Syntactic, and Statistical Pattern Recognition,

Münch, Maximilian ; Straat, Michiel ; Biehl, Michael. - p. 14-23 , 2021

Link: https://doi.org/10.1007/..

11

Dimensionality reduction in the context of dynamic social m..:

Heusinger, Moritz ; Raab, Christoph ; Schleif, Frank-Michael
Evolving Systems. 13 (2021) 3 - p. 387-401 , 2021

Link: https://doi.org/10.1007/..

12

Classification in Non-stationary Environments Using Coreset..:

, In: Advances in Computational Intelligence; Lecture Notes in Computer Science,

Heusinger, Moritz ; Schleif, Frank-Michael - p. 126-137 , 2021

Link: https://doi.org/10.1007/..

13

Data-Driven Supervised Learning for Life Science Data:

Münch, Maximilian ; Raab, Christoph ; Biehl, Michael.
Frontiers in Applied Mathematics and Statistics. 6 (2020) - p. , 2020

Link: https://doi.org/10.3389/..

14

Random Projection in the Presence of Concept Drift in Super..:

, In: Artificial Intelligence and Soft Computing; Lecture Notes in Computer Science,

Heusinger, Moritz ; Schleif, Frank-Michael - p. 514-524 , 2020

Link: https://doi.org/10.1007/..

15

Encoding of Indefinite Proximity Data: A Structure Preservi..:

, In: Lecture Notes in Computer Science; Pattern Recognition Applications and Methods,

Münch, Maximilian ; Raab, Christoph ; Schleif, Frank-Michael - p. 112-137 , 2020

Link: https://doi.org/10.1007/..