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 …
Function approximation for reinforcement learning controller for energy from spread waves
S Sarkar, V Gundecha, S Ghorbanpour… - arXiv preprint arXiv …, 2024 - arxiv.org
The industrial multi-generator Wave Energy Converters (WEC) must handle multiple
simultaneous waves coming from different directions called spread waves. These complex …
simultaneous waves coming from different directions called spread waves. These complex …
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 …
A configurable pythonic data center model for sustainable cooling and ml integration
There have been growing discussions on estimating and subsequently reducing the
operational carbon footprint of enterprise data centers. The design and intelligent control for …
operational carbon footprint of enterprise data centers. The design and intelligent control 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 …
EARL-BO: Reinforcement Learning for Multi-Step Lookahead, High-Dimensional Bayesian Optimization
Conventional methods for Bayesian optimization (BO) primarily involve one-step optimal
decisions (eg, maximizing expected improvement of the next step). To avoid myopic …
decisions (eg, maximizing expected improvement of the next step). To avoid myopic …
[PDF][PDF] Meta-Learned Bayesian Optimization for Energy Yield in Inertial Confinement Fusion
With the growing demand for clean energy, fusion presents a promising path to sustainable
power generation. Inertial confinement fusion (ICF) experiments trigger nuclear reactions by …
power generation. Inertial confinement fusion (ICF) experiments trigger nuclear reactions by …