Showing papers from Penn State University Show all papers
Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Regularized Muon induces a Hamiltonian probability gradient flow with mirror-descent structure, yielding exponential convergence under gradient dominance and mean-field propagation of chaos.
Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026
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Sobolev-regularized MMD gradient flow penalizes witness function gradients to ensure global convergence without isoperimetric assumptions, applying to both sampling and generative modeling.
Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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FSGD is a streaming SGD method that uses latent factor representations for high-dimensional tasks, achieving scalable optimization with theoretical convergence guarantees including factor estimation error.
Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026
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ForecastCompass organizes forecasting experience into reusable predictive factors and calibration principles via adaptive memory, improving agentic forecasting accuracy and calibration.
Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026
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NoiseCurve uses model curvature from public unlabeled data to improve cross-iteration noise correlation in DP-SGD, significantly boosting accuracy over DP-MF.
Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Forced Deferral Attack uses adversarial image triggers to suppress weak-model confidence and force multimodal LLM cascades to route queries to strong models. It learns universal border triggers via temperature-flattened optimization, consistently increasing unintended strong-model usage across datas
Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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