On-device research index

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.

168,695 papers · 148 categories

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9 results for “power-enhanced”

A Heteroskedasticity-Robust Overidentifying Restriction Test with High-Dimensional Covariatesecon.EM

Paper proposes a robust test for high-dimensional models with large covariates and instruments.

problem Testing high-dimensional linear instrumental variable models with large covariates and instruments.

method Introduces a test based on the maximum norm of multiple parameters and a power-enhanced test.

result The proposed test is robust to heteroskedastic errors and has higher power than existing tests.

high-dimensional models instrumental variable robust test power-enhanced heteroskedasticity

2022-04-30abs ↗pdf ↗

Detection and Estimation of Structural Breaks in High-Dimensional Functional Time Seriesstat.ME

Paper detects and estimates breaks in high-dimensional functional time series.

problem Detecting and estimating structural breaks in heterogeneous mean functions of high-dimensional functional time series.

method Proposes a new test statistic combining functional CUSUM and power enhancement components, with a clustering algorithm for group structure estimation.

result The proposed techniques have satisfactory performance in finite samples, detecting and estimating breaks effectively.

structural breaks functional time series high-dimensional CUSUM statistic power enhancement

2023-04-14abs ↗pdf ↗

Fisher's combined probability test for high-dimensional covariance matricesmath.ST

Enhances power of covariance matrix tests for high-dimensional data.

problem Testing large covariance matrices in high-dimensional data.

method Proposes a new Fisher's combined probability test for quadratic form and maximum form statistics.

result Boosts power against more general alternatives.

covariance matrices high-dimensional data Fisher's method power enhancement quadratic form statistics

2020-05-31abs ↗pdf ↗

DART2: a robust multiple testing method to smartly leverage helpful or misleading ancillary informationstat.ML

DART2 enhances multiple testing by leveraging ancillary information robustly.

problem Enhancing multiple testing power with uncertain ancillary information.

method Distance-assisted multiple testing procedure (DART2) that handles both helpful and misleading ancillary information.

result DART2 asymptotically controls FDR and improves power when ancillary information is helpful, maintaining FDR and power otherwise.

multiple testing ancillary information distance-assisted FDR control power enhancement

2024-09-05abs ↗pdf ↗

SPARC: Spectral Architectures Tackling the Cold-Start Problem in Graph Learningcs.LG

SPARC tackles cold-start nodes in graphs by using spectral embeddings.

problem Cold-start nodes in graphs lacking initial connections.

method Introduces SPARC, a framework utilizing spectral embeddings to predict on cold-start nodes.

result SPARC outperforms existing models on cold-start nodes across tasks.

graph learning spectral embeddings cold-start problem node classification node clustering

2024-11-03abs ↗pdf ↗

Federated Causal Discovery Across Heterogeneous Datasets under Latent Confoundingcs.LG

fedCI and fedCI-IOD enable federated causal discovery across diverse datasets with privacy and power enhancements.

problem Causal discovery across multiple datasets with privacy constraints and heterogeneity.

method federated conditional independence test (fedCI) and Integration of Overlapping Datasets (IOD) algorithm extension (fedCI-IOD).

result fedCI-IOD achieves comparable performance to fully pooled analyses, enhancing statistical power and privacy.

federated learning causal inference conditional independence heterogeneous datasets privacy-preserving

2026-03-05abs ↗pdf ↗

Robust Conformal Outlier Detection under Contaminated Reference Datastat.ML

The paper analyzes how conformal prediction works with contaminated reference data.

problem The impact of contamination on the validity and power of conformal prediction methods.

method The paper analyzes the impact of contamination on the validity of conformal methods and proposes a data-cleaning framework to enhance power.

result The proposed data-cleaning framework can effectively enhance power while maintaining type-I error control.

conformal prediction outlier detection contaminated data type-I error power enhancement

2025-02-07abs ↗pdf ↗

Prediction-Enhanced Monte Carlo: A Machine Learning View on Control Variatestat.ML

PEMC uses ML to enhance Monte Carlo simulations, reducing variance and runtime.

problem Computational inefficiency in Monte Carlo simulations for complex tasks.

method Prediction-Enhanced Monte Carlo (PEMC) framework that uses ML surrogates as predictors.

result PEMC provides unbiased evaluations with reduced variance and runtime compared to standard Monte Carlo.

Monte Carlo Machine Learning Control Variates Variance Reduction Simulation Efficiency

2024-12-15abs ↗pdf ↗

A Unified Combination Framework for Dependent Tests with Applications to Microbiome Association Studiesstat.ME

Unified framework combines dependent microbiome tests.

problem Combining dependent microbiome association tests.

method Generalized meta-analysis framework for dependent tests.

result The vanilla Cauchy combination is a special case.

microbiome association studies meta-analysis dependent tests confidence distributions

2024-04-14abs ↗pdf ↗