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stat.ML2026
A Robust Optimization Approach to Sparse Principal Component Analysis
David Vävinggren, Francis Bach, André M. H. Teixeira +2
While principal component analysis (PCA) is a fundamental tool for dimensionality reduction, its dense representations make it ill-suited for high-dimensional data. Existing method…
stat.ML2026
Anytime-Valid Conformal Risk Control
Bror Hultberg, Dave Zachariah, Antônio H. Ribeiro
Prediction sets provide a means of quantifying the uncertainty in predictive tasks. Using held out calibration data, conformal prediction and risk control can produce prediction se…