AIoT

TESLA: Thermally Safe, Load-Aware, and Energy-Efficient Cooling Control System for Data Centers
The increasing demand for artificial intelligence and cloud computing has led to skyrocketing energy consumption of data centers (DCs). …
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A Fully Data-Driven Approach for Realistic Traffic Signal Control Using Offline Reinforcement Learning
The optimization of traffic signal control (TSC) is critical for an efficient transportation system. In recent years, reinforcement …
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Data-Driven Methods for Sustainable Industrial and AIoT Systems
Using advanced data-driven AI methods to optimize real-world complex industrial and AIoT systems.
Data-Driven Methods for Sustainable Industrial and AIoT Systems
Look Beneath the Surface: Exploiting Fundamental Symmetry for Sample-Efficient Offline RL
Offline reinforcement learning (RL) offers an appealing approach to real-world tasks by learning policies from pre-collected datasets …
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An Efficient Multi-Agent Optimization Approach for Coordinated Massive MIMO Beamforming
Beamforming plays an important role in 5G Massive Multiple-Input Multiple-Output (MMIMO) communications. Optimizing beamforming …
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DeepThermal: Combustion Optimization for Thermal Power Generating Units Using Offline Reinforcement Learning
Optimizing the combustion efficiency of a thermal power generating unit (TPGU) is a highly challenging and critical task in the energy …
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