Abstract: Drift analysis is one of the main tools for analyzing the time complexity of evolutionary algorithms. However, it requires manual construction of drift functions to bound hitting time for ...
Personalized algorithms may quietly sabotage how people learn, nudging them into narrow tunnels of information even when they start with zero prior knowledge. In the study, participants using ...
This article was co-authored with Emma Myer, a student at Washington and Lee University who studies Cognitive/Behavioral Science and Strategic Communication. In today’s digital age, social media has ...
Abstract: Ensuring the safety of Deep Reinforcement Learning (DRL) systems remains a significant challenge, particularly in real-time applications such as autonomous driving and robotics, where ...
Change-point detection in time series analysis comprises a suite of statistical and computational techniques aimed at identifying times at which the probabilistic structure of sequential observations ...
SDG-PGMs is a Python framework for building Probabilistic Graphical Models (PGMs) that generate synthetic data with realistic, statistically-grounded relationships between attributes. It extends pgmpy ...
Speaking at WSJ Opinion Live in Washington, D.C., WSJ Editorial Page Editor Paul Gigot and SandboxAQ CEO Jack Hidary discuss Large Quantitative Models (LQMs) and their role in AI applications, the ...
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