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pro vyhledávání: '"Gangopadhyay, Briti"'
Current keyword decision-making in sponsored search advertising relies on large, static datasets, limiting the ability to automatically set up keywords and adapt to real-time KPI metrics and product updates that are essential for effective advertisin
Externí odkaz:
http://arxiv.org/abs/2412.03577
Recent advancements in offline Reinforcement Learning (Offline RL) have led to an increased focus on methods based on conservative policy updates to address the Out-of-Distribution (OOD) issue. These methods typically involve adding behavior regulari
Externí odkaz:
http://arxiv.org/abs/2406.07117
With the ability to learn from static datasets, Offline Reinforcement Learning (RL) emerges as a compelling avenue for real-world applications. However, state-of-the-art offline RL algorithms perform sub-optimally when confronted with limited data co
Externí odkaz:
http://arxiv.org/abs/2406.07041
Recent advances in Reinforcement Learning (RL) combined with Deep Learning (DL) have demonstrated impressive performance in complex tasks, including autonomous driving. The use of RL agents in autonomous driving leads to a smooth human-like driving e
Externí odkaz:
http://arxiv.org/abs/2103.13861
Human vision is able to compensate imperfections in sensory inputs from the real world by reasoning based on prior knowledge about the world. Machine learning has had a significant impact on computer vision due to its inherent ability in handling imp
Externí odkaz:
http://arxiv.org/abs/2004.12152
Akademický článek
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Publikováno v:
In Pattern Recognition Letters December 2021 152:143-149
Publikováno v:
IEEE Transactions on Intelligent Vehicles; February 2023, Vol. 8 Issue: 2 p1889-1899, 11p
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems; Aug2022, Vol. 23 Issue 8, p10902-10911, 10p