Zobrazeno 1 - 10
of 77
pro vyhledávání: '"Meinolf Sellmann"'
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 26:493-498
We present a dynamic branching scheme for set partitioning problems. The idea is to trace features of the underlying MIP model and to base search decisions on the features of the current subproblem to be solved. We show how such a system can be train
Publikováno v:
Annals of Mathematics and Artificial Intelligence. 90:715-734
Algorithm configuration has emerged as an essential technology for the improvement of high-performance solvers. We present new algorithmic ideas to improve state-of-the-art solver configurators automatically by tuning. Particularly, we introduce 1. a
Autor:
Meinolf Sellmann
Publikováno v:
Proceedings of the Genetic and Evolutionary Computation Conference.
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031248658
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e70e6122bbaa07a09626da48d781bb64
https://doi.org/10.1007/978-3-031-24866-5_8
https://doi.org/10.1007/978-3-031-24866-5_8
Autor:
Meinolf Sellmann, Hermann Schichl
Publikováno v:
AAAI
We consider the task of aggregating scores provided by experts that each have scored only a subset of all objects to be rated. Since experts only see a subset of all objects, they lack global information on the overall quality of all objects, as well
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030921200
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4bed0d55d6c0e1e8af34069e34389fbc
https://doi.org/10.1007/978-3-030-92121-7_2
https://doi.org/10.1007/978-3-030-92121-7_2
Autor:
Meinolf Sellmann, Kevin Tierney
This book constitutes the refereed proceedings of the 17th International Conference on Learning and Intelligent Optimization, LION-17, held in Nice, France, during June 4–8, 2023.The 40 full papers presented have been carefully reviewed and selecte
Publikováno v:
Advances in Artificial Intelligence ISBN: 9783030473570
Canadian Conference on AI
Canadian Conference on AI
We present a new methodology for assessing when data-based predictive models can be trusted. Particularly, we propose to learn a model from experimentation that determines, for a given labeled data set and a learning technique, when the model generat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a2126f77627cd8a0a48924fd180a8c96
https://doi.org/10.1007/978-3-030-47358-7_10
https://doi.org/10.1007/978-3-030-47358-7_10
Autor:
Meinolf Sellmann
Publikováno v:
IEEE Intelligent Systems. 32:35-39
A brief overview of algorithms that improve other algorithms and their role in cognitive computing.
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030300470
CP
CP
We propose a new framework for decision making under uncertainty to overcome the main drawbacks of current technology: modeling complexity, scenario generation, and scaling limitations. We consider three NP-hard optimization problems: the Stochastic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a77da4404eae568a9541a2efd3c1c274
https://doi.org/10.1007/978-3-030-30048-7_40
https://doi.org/10.1007/978-3-030-30048-7_40