Ensemble SARIMA–XGBoost Commodities Strategy
Published:
Hybrid time-series + ML residual model for commodity forecasting and signal-based backtesting (GTSF Quant Sector Commodity ML Team).
Published:
Hybrid time-series + ML residual model for commodity forecasting and signal-based backtesting (GTSF Quant Sector Commodity ML Team).
Published:
Classical ML pipeline for breast cancer classification using structured diagnostic features, emphasizing interpretability and clinically relevant evaluation (team project for CS4641).
We study algorithmic tradeoffs in transitioning from snapshot-based to event-based resilience metrics for power grid analysis. By formalizing event detection and aggregation under realistic grid dynamics, we characterize how design choices impact sensitivity, stability, and interpretability of resilience estimates.
Status: Preprint
Published:
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Published:
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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