Zobrazeno 1 - 10
of 25
pro vyhledávání: '"André Biedenkapp"'
Autor:
Jack Parker-Holder, Raghu Rajan, Xingyou Song, André Biedenkapp, Yingjie Miao, Theresa Eimer, Baohe Zhang, Vu Nguyen, Roberto Calandra, Aleksandra Faust, Frank Hutter, Marius Lindauer
The combination of Reinforcement Learning (RL) with deep learning has led to a series of impressive feats, with many believing (deep) RL provides a path towards generally capable agents. However, the success of RL agents is often highly sensitive to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e62a633259d1ea57d5ea45012f91a0be
Autor:
Steven Adriaensen, André Biedenkapp, Gresa Shala, Noor Awad, Theresa Eimer, Marius Lindauer, Frank Hutter
The performance of an algorithm often critically depends on its parameter configuration. While a variety of automated algorithm configuration methods have been proposed to relieve users from the tedious and error-prone task of manually tuning paramet
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::889239d3ea79c9aee36885bb20071b29
Funding: Nguyen Dang is a Leverhulme Early Career Fellow. This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No. 945298-ParisRegion-FP. It is al
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8a2b19284320b71ea911ae7f0adf4184
Autor:
André Biedenkapp, Marius Lindauer, Frank Hutter, Theresa Eimer, Steven Adriansen, Maximilian Reimer
Publikováno v:
IJCAI
Dynamic Algorithm Configuration (DAC) aims to dynamically control a target algorithm's hyperparameters in order to improve its performance. Several theoretical and empirical results have demonstrated the benefits of dynamically controlling hyperparam
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4f6b04957738c3f09bd4d8cea1d8cbf2
https://doi.org/10.24963/ijcai.2021/230
https://doi.org/10.24963/ijcai.2021/230
A key challenge in satisficing planning is to use multiple heuristics within one heuristic search. An aggregation of multiple heuristic estimates, for example by taking the maximum, has the disadvantage that bad estimates of a single heuristic can ne
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e460e2af62abece16e99e3046541c154
Autor:
Marius Lindauer, Gresa Shala, Frank Hutter, Noor H. Awad, André Biedenkapp, Steven Adriaensen
Publikováno v:
Parallel Problem Solving from Nature – PPSN XVI ISBN: 9783030581114
PPSN (1)
PPSN (1)
An algorithm’s parameter setting often affects its ability to solve a given problem, e.g., population-size, mutation-rate or crossover-rate of an evolutionary algorithm. Furthermore, some parameters have to be adjusted dynamically, such as lowering
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0b974a2e3deaba47a4bc6705e342a78f
https://doi.org/10.1007/978-3-030-58112-1_48
https://doi.org/10.1007/978-3-030-58112-1_48
Publikováno v:
ECAI: Frontiers in Artificial Intelligence and Applications
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=r3c4b2081b22::bb9e4fe5640be502365e606eb57b682b
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030053475
LION
LION
To achieve peak performance of an algorithm (in particular for problems in AI), algorithm configuration is often necessary to determine a well-performing parameter configuration. So far, most studies in algorithm configuration focused on proposing be
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::20e3e14e0adcac9f36f526f2c4d35d0f
https://doi.org/10.1007/978-3-030-05348-2_10
https://doi.org/10.1007/978-3-030-05348-2_10
Publikováno v:
Scopus-Elsevier
To achieve peak performance, it is often necessary to adjust the parameters of a given algorithm to the class of problem instances to be solved; this is known to be the case for popular solvers for a broad range of AI problems, including AI planning,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::46143a439cf2dc73a95fb0b288c0e830
https://doi.org/10.1609/aaai.v31i1.10657
https://doi.org/10.1609/aaai.v31i1.10657
Autor:
Balcan, Maria-Florina1 ninamf@cs.cmu.edu, Dick, Travis2 tdick@google.com, Sandholm, Tuomas3 sandholm@cs.cmu.edu, Vitercik, Ellen4 vitercik@stanford.edu
Publikováno v:
Journal of the ACM. Apr2024, Vol. 71 Issue 2, p1-73. 73p.