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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.

168,978 papers · 148 categories

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5 results for confidence-classifier

A new classifier method detects out-of-distribution samples by minimizing KL divergence.

problem Detecting out-of-distribution samples in neural networks.
method Training a confident-classifier by minimizing KL divergence and maximizing entropy, or adding a reject class.
result The confident-classifier still yields high confidence for OOD samples far from the in-distribution.

Guarantees robustness of Gaussian process classifiers against adversarial attacks.

problem Protecting machine learning classifiers from adversarial perturbations.
method Developed an adversarial bound (AB) for Gaussian process classifiers, providing a formal guarantee of robustness.
result Proves that the proposed method produces a practical, useful, and provably robust classifier.

EoS selectively shapes learning, affecting some groups more than others.

problem EoS affects learning differently across the data distribution.
method Branching intervention to enter or exit EoS regime, controlled perturbation to isolate mechanisms.
result EoS redistributes learning, amplifying progress on some groups and suppressing others.