Federated Learning by nature is susceptible to low-quality, corrupted, or even malicious data that can severely degrade the quality of the learned model. Traditional techniques for data valuation cannot be applied as the data is never revealed. We present ...
Motivated by the experimental observation of a quantized 5/2 thermal conductance at filling nu = 5/2, a result incompatible with both the Pfaffian and the anti-Pfaffian states, we have pushed the expansion of the effective Hamiltonian of the 5/2-quantized ...
A crucial building block of responsible artificial intelligence is responsible data governance, including data collection. Its importance is also underlined in the latest EU regulations. The data should be of high quality, foremost correct and representati ...
As humans spend most of their time indoors, indoor air quality (IAQ) significantly impacts their health. In parallel, building ventilation consumes significant energy, contributing to climate change. However, the relationships between the building ventilat ...
Endogenous and exogenous uncertainties exert significant influences on energy planning. In this study, we propose a systematic methodology to excavate the uncertainty space, by combining mix-integer linear programming (MILP), Monte Carlo simulation, and ma ...
The aluminium remelting industry relies on natural gas to transform recycled aluminium into aluminium feedstock, entailing significant atmospheric emissions. Hydric resources are also affected as they are used as sinks of waste heat from the casting proces ...
