Zobrazeno 1 - 10
of 3 636
pro vyhledávání: '"Hoos, A."'
Autor:
Becktepe, Jannis, Dierkes, Julian, Benjamins, Carolin, Mohan, Aditya, Salinas, David, Rajan, Raghu, Hutter, Frank, Hoos, Holger, Lindauer, Marius, Eimer, Theresa
Publikováno v:
17th European Workshop on Reinforcement Learning 2024
Hyperparameters are a critical factor in reliably training well-performing reinforcement learning (RL) agents. Unfortunately, developing and evaluating automated approaches for tuning such hyperparameters is both costly and time-consuming. As a resul
Externí odkaz:
http://arxiv.org/abs/2409.18827
Graph-structured data naturally occurs in many research fields, such as chemistry and sociology. The relational information contained therein can be leveraged to statistically model graph properties through geometrical deep learning. Graph neural net
Externí odkaz:
http://arxiv.org/abs/2409.11856
There has been significant progress in deep reinforcement learning (RL) in recent years. Nevertheless, finding suitable hyperparameter configurations and reward functions remains challenging even for experts, and performance heavily relies on these d
Externí odkaz:
http://arxiv.org/abs/2406.18293
The research field of automated negotiation has a long history of designing agents that can negotiate with other agents. Such negotiation strategies are traditionally based on manual design and heuristics. More recently, reinforcement learning approa
Externí odkaz:
http://arxiv.org/abs/2406.15096
The ubiquity of deep learning algorithms in various applications has amplified the need for assuring their robustness against small input perturbations such as those occurring in adversarial attacks. Existing complete verification techniques offer pr
Externí odkaz:
http://arxiv.org/abs/2406.10154
Solver competitions play a prominent role in assessing and advancing the state of the art for solving many problems in AI and beyond. Notably, in many areas of AI, competitions have had substantial impact in guiding research and applications for many
Externí odkaz:
http://arxiv.org/abs/2308.05062
Autor:
Purucker, Lennart, Schneider, Lennart, Anastacio, Marie, Beel, Joeran, Bischl, Bernd, Hoos, Holger
Automated machine learning (AutoML) systems commonly ensemble models post hoc to improve predictive performance, typically via greedy ensemble selection (GES). However, we believe that GES may not always be optimal, as it performs a simple determinis
Externí odkaz:
http://arxiv.org/abs/2307.08364
Autor:
Tuia, Devis, Schindler, Konrad, Demir, Begüm, Zhu, Xiao Xiang, Kochupillai, Mrinalini, Džeroski, Sašo, van Rijn, Jan N., Hoos, Holger H., Del Frate, Fabio, Datcu, Mihai, Markl, Volker, Saux, Bertrand Le, Schneider, Rochelle, Camps-Valls, Gustau
Publikováno v:
IEEE Geoscience and Remote Sensing Magazine, 2024
Earth observation (EO) is a prime instrument for monitoring land and ocean processes, studying the dynamics at work, and taking the pulse of our planet. This article gives a bird's eye view of the essential scientific tools and approaches informing a
Externí odkaz:
http://arxiv.org/abs/2305.08413
Bargaining can be used to resolve mixed-motive games in multi-agent systems. Although there is an abundance of negotiation strategies implemented in automated negotiating agents, most agents are based on single fixed strategies, while it is widely ac
Externí odkaz:
http://arxiv.org/abs/2212.10228
Publikováno v:
BMC Psychiatry, Vol 24, Iss 1, Pp 1-15 (2024)
Abstract Background Motor alterations and lowered physical activity are common in affective disorders. Previous research has indicated a link between depressive symptoms and declining muscle strength primarily focusing on the elderly but not younger
Externí odkaz:
https://doaj.org/article/05fca6f84cd649a2a22e5f7945a1c0c4
