Benchmark generation framework with customizable distortions for image classifier robustness
We present a novel framework for generating adversarial benchmarks to evaluate the
robustness of image classification models. The RLAB framework allows users to customize …
robustness of image classification models. The RLAB framework allows users to customize …
Sustainability of Data Center Digital Twins with Reinforcement Learning
The rapid growth of machine learning (ML) has led to an increased demand for
computational power, resulting in larger data centers (DCs) and higher energy consumption …
computational power, resulting in larger data centers (DCs) and higher energy consumption …
Carbon Footprint Reduction for Sustainable Data Centers in Real-Time
As machine learning workloads are significantly increasing energy consumption,
sustainable data centers with low carbon emissions are becoming a top priority for …
sustainable data centers with low carbon emissions are becoming a top priority for …
Robustness and Visual Explanation for Black Box Image, Video, and ECG Signal Classification with Reinforcement Learning
We present a generic Reinforcement Learning (RL) framework optimized for crafting
adversarial attacks on different model types spanning from ECG signal analysis (1D), image …
adversarial attacks on different model types spanning from ECG signal analysis (1D), image …
SustainDC: Benchmarking for Sustainable Data Center Control
Machine learning has driven an exponential increase in computational demand, leading to
massive data centers that consume significant amounts of energy and contribute to climate …
massive data centers that consume significant amounts of energy and contribute to climate …