IntersectNET: Traffic flow? Managed
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IntersectNet enhances traffic flow by modeling intersections with transition functions between lanes, generating matrices whose elements, determined through machine learning, optimize vehicle movement. This approach aims to streamline urban traffic efficiency through data-driven intersection management strategies.
RLHF-BMF: Bias Mitigation Framework
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RLHF-BMF is an iterative model comprising a chain of RLHF model annotators, with RLHF models annotating each other in a chain, culminating in a final RLHF model annotated by a human.
Sentiment-STARity: Shopping Score Analysis
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Explore sentiment and star rating alignment in e-commerce reviews with Sentiment-STARity. Analyzing 82.83 million of Amazon product reviews to enhance shopping decisions through consistent rating evaluation.
BURST: Bayesian Uncertainty-driven Reinforcement Sampling Technique
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Our method integrates uncertainty estimation into the action selection process of a Deep Q-Network (DQN) agent. The agent uses a Bayesian neural network to model the Q-function, providing both expected Q-values and uncertainty estimates for each action. The uncertainty estimates guide the exploration strategy.