Data-driven AI systems increasingly influence our choices, raising concerns about autonomy, fairness, and accountability. Achieving algorithmic autonomy requires new infrastructures, motivation ...
Abstract: This study presents an innovative approach for optimizing real-time energy market trading strategies by integrating Proximal Policy Optimization (PPO) with Quantum Annealing (QA). The ...
Abstract: This research develops, compares, and analyzes both a traditional algorithm using computer vision and a deep learning model to deal with dynamic road conditions. In the final testing, the ...
The consultation paper proposes strict oversight of algorithmic trading to curb volatility, manipulation, and system risks. The key takeaway is enhanced accountability and transparency without ...
Researchers introduce a group-driven initialization that fuses search history with graph modularity, boosting state-of-the-art local solvers for k-quasi-clique and k-plex without altering their search ...
This repository contains comprehensive implementations of algorithms from the classic textbook "Fundamentals of Computer Algorithms" (Second Edition) by Ellis Horowitz, Sartaj Sahni, and Sanguthevar ...
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