Recasts sampling-based nonconvex optimization as smoothed gradient descent to obtain non-asymptotic convergence guarantees and introduces the DIDA annealed algorithm that converges to the global optimum.
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Foundations and Trends in Machine Learning 2, 1–127
2 Pith papers cite this work, alongside 6,910 external citations. Polarity classification is still indexing.
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ModernBERT-labeled analysis of 306k social posts yields six major public-sentiment clusters on Advanced Air Mobility spanning noise, safety, regulation, workforce, drones, and military use.
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Global Convergence of Sampling-Based Nonconvex Optimization through Diffusion-Style Smoothing
Recasts sampling-based nonconvex optimization as smoothed gradient descent to obtain non-asymptotic convergence guarantees and introduces the DIDA annealed algorithm that converges to the global optimum.
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From Sentiment to Actionable Insights: Public Sentiment Analysis of Advanced Air Mobility
ModernBERT-labeled analysis of 306k social posts yields six major public-sentiment clusters on Advanced Air Mobility spanning noise, safety, regulation, workforce, drones, and military use.