Zobrazeno 1 - 10
of 9 311
pro vyhledávání: '"Black-Box Optimization"'
Black-box optimization algorithms have been widely used in various machine learning problems, including reinforcement learning and prompt fine-tuning. However, directly optimizing the training loss value, as commonly done in existing black-box optimi
Externí odkaz:
http://arxiv.org/abs/2410.12457
Offline black-box optimization aims to maximize a black-box function using an offline dataset of designs and their measured properties. Two main approaches have emerged: the forward approach, which learns a mapping from input to its value, thereby ac
Externí odkaz:
http://arxiv.org/abs/2410.00983
Bayesian optimization (BO) is a popular method for computationally expensive black-box optimization. However, traditional BO methods need to solve new problems from scratch, leading to slow convergence. Recent studies try to extend BO to a transfer l
Externí odkaz:
http://arxiv.org/abs/2412.07186
Autor:
Kontar, Raed Al
Publikováno v:
2024 IEEE International Conference on Big Data
We focus on collaborative and federated black-box optimization (BBOpt), where agents optimize their heterogeneous black-box functions through collaborative sequential experimentation. From a Bayesian optimization perspective, we address the fundament
Externí odkaz:
http://arxiv.org/abs/2411.07523
In this survey, we introduce Meta-Black-Box-Optimization~(MetaBBO) as an emerging avenue within the Evolutionary Computation~(EC) community, which incorporates Meta-learning approaches to assist automated algorithm design. Despite the success of Meta
Externí odkaz:
http://arxiv.org/abs/2411.00625
State recognition of the environment and objects, such as the open/closed state of doors and the on/off of lights, is indispensable for robots that perform daily life support and security tasks. Until now, state recognition methods have been based on
Externí odkaz:
http://arxiv.org/abs/2410.22707
Autor:
Nezami, Nazanin, Anahideh, Hadis
Optimizing costly black-box functions within a constrained evaluation budget presents significant challenges in many real-world applications. Surrogate Optimization (SO) is a common resolution, yet its proprietary nature introduced by the complexity
Externí odkaz:
http://arxiv.org/abs/2410.14573
In order for robots to autonomously navigate and operate in diverse environments, it is essential for them to recognize the state of their environment. On the other hand, the environmental state recognition has traditionally involved distinct methods
Externí odkaz:
http://arxiv.org/abs/2409.17519
Autor:
Yun, Taeyoung, Lee, Kanghoon, Yun, Sujin, Kim, Ilmyung, Jung, Won-Woo, Kwon, Min-Cheol, Choi, Kyujin, Lee, Yoohyeon, Park, Jinkyoo
Complex urban road networks with high vehicle occupancy frequently face severe traffic congestion. Designing an effective strategy for managing multiple traffic lights plays a crucial role in managing congestion. However, most current traffic light m
Externí odkaz:
http://arxiv.org/abs/2408.07327
Publikováno v:
IEEE Wireless Communications Letters ( Early Access ) 28 October 2024
Movable antenna (MA) is a new technology which leverages local movement of antennas to improve channel qualities and enhance the communication performance. Nevertheless, to fully realize the potential of MA systems, complete channel state information
Externí odkaz:
http://arxiv.org/abs/2408.04951