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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.

168,742 papers · 148 categories

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3 results for “support-aware”
CASP: Support-Aware Offline Policy Selection for Two-Stage Recommender Systemscs.IR

CASP selects reliable policies for two-stage recommender systems by considering both value and support.

problem The selection of a generator in two-stage recommender systems affects both the policy value and the data support used to estimate it.
method CASP combines doubly robust value estimation with a support-burden penalty.
result CASP selects lower-burden policies when estimated value and support credibility are in tension.
recommender systemstwo-stagegenerator selectionsupport-awareoffline selection
2026-04-24abs ↗pdf ↗
Support-aware offline policy selection for advertising marketplacesstat.ML

Develops a support-aware framework for reserve-policy selection in advertising markets.

problem Log-based reserve-price evaluation risks weak support and subgroup harm.
method Support-aware offline decision framework converting logged evidence into certified policies.
result Preserves the best gate-passing policy while eliminating only policies with certified regret.
reserve pricingadvertising marketsoffline evaluationsupport awarenesspolicy selection
2026-05-20abs ↗pdf ↗
Locally Private Online Quantile Regression: Estimation and Inferencestat.ML

Locally private online quantile regression method addresses privacy constraints.

problem Estimating and inferring quantile regression under local differential privacy constraints.
method Developed a finite-alphabet channel where users compute local contributions, apply randomized response, and send reports. A public decoder corrects distortion and reconstructs inputs for averaging.
result Established local privacy, decoder unbiasedness, consistency, asymptotic normality, and inference for scalar contrasts.
quantile regressionlocal differential privacyonline learningprivacy-preservingstochastic quantization
2026-07-06abs ↗pdf ↗