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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,657 papers · 148 categories

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7 results for “learn-then-test”

Adaptive Learn-then-Test: Statistically Valid and Efficient Hyperparameter Selectionstat.ML

aLTT selects hyperparameters efficiently with statistical guarantees.

problem Statistical validity and efficiency in hyperparameter selection.

method Sequential data-dependent multiple hypothesis testing with early termination.

result Reduces testing rounds while maintaining statistical validity.

hyperparameter selection statistical guarantees sequential testing multiple hypothesis testing early termination

2024-09-24abs ↗pdf ↗

Statistically Valid Hyperparameter Selection: From Tuning to Guaranteesstat.ML

Statistical guarantees for hyperparameter selection

problem Hyperparameter selection in AI systems

method Learn-then-test framework

result Provable reliability and safety

hyperparameter selection statistical guarantees learn-then-test AI systems

2026-06-24abs ↗pdf ↗

Early Time Classification with Accumulated Accuracy Gap Controlcs.LG

Paper introduces a method to control early classification accuracy gaps.

problem Maintaining accuracy in early classification without full input processing.

method Statistical framework for a calibrated stopping rule.

result Reduces up to 94% of timesteps while controlling accuracy gaps.

early classification accuracy gap sequential classifier stopping rule Learn-then-Test

2024-02-01abs ↗pdf ↗

Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Controlcs.LG

Framework calibrates ML models for risk control in various tasks.

problem Achieving statistical guarantees for model predictions.

method Reframing risk control as multiple hypothesis testing, applying statistical techniques.

result New calibration methods for multi-label classification, instance segmentation, outlier detection, and confidence set coverage.

machine learning calibration risk control multiple hypothesis testing statistical guarantees

2021-10-03abs ↗pdf ↗

Two-stage Risk Control with Application to Ranked Retrievalcs.IR

Two-stage risk control for ranked retrieval systems.

problem Assessing prediction uncertainty and risk control in sequential machine learning systems.

method Developed two-stage risk control methods based on LTT and CRC frameworks, leveraging sequential nature of retrieval and ranking phases.

result The proposed methods provide theoretical guarantees and reduce computational burden compared to prior work.

machine learning risk control sequential systems ranked retrieval prediction uncertainty

2024-04-27abs ↗pdf ↗

Conformal Prediction Sets for Instance Segmentationcs.CV

Algorithm generates adaptive confidence sets for instance segmentation with guaranteed coverage.

problem Uncalibrated predictions and lack of uncertainty quantification in instance segmentation models.

method Conformal prediction algorithm to generate adaptive confidence sets with provable guarantees.

result Empirically, prediction sets vary in size based on query difficulty and attain target coverage, outperforming baselines.

instance segmentation conformal prediction uncertainty quantification IoU agricultural field delineation

2026-02-10abs ↗pdf ↗

Cross-Domain Uncertainty Quantification for Selective Prediction: A Comprehensive Bound Ablation with Transfer-Informed Bettingcs.LG

A new method combines multiple bounds and betting strategies for selective prediction, improving risk coverage in data-scarce settings.

problem Selective prediction with risk control in data-scarce domains.

method Combines concentration inequalities, multiple-testing corrections, and betting-based confidence sequences.

result Transfer-Informed Betting achieves tighter bounds and better coverage in data-scarce settings.

Selective prediction Risk control Cross-domain uncertainty Transfer-Informed Betting Concentration inequalities

2026-03-09abs ↗pdf ↗