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.

168,742 papers · 148 categories

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10 results for “non-response”

Active learning with biased non-response to label requestscs.LG

Active learning suffers from biased non-response, which this paper addresses.

problem Active learning's effectiveness is compromised by biased non-response in real-world contexts.

method Proposes a cost-based correction to the sampling strategy, UCB-EU, to mitigate the impact of biased non-response.

result UCB-EU successfully reduces the harm from labelling non-response in many settings.

active learning non-response bias UCB-EU e-commerce

2023-12-13abs ↗pdf ↗

Analysis of ELSA COVID-19 Substudy response rate using machine learning algorithmsstat.AP

Study uses ML to predict non-participation in ELSA COVID-19 follow-up studies.

problem Predicting non-participation in follow-up surveys due to various factors.

method Used machine learning algorithms including KNN, RF, AdaBoost, logistic regression, NN, and SVC.

result Random Forest (RF) outperforms other models in balanced accuracy.

Machine Learning Survey Non-Response ELSA COVID-19 Random Forest

2024-11-01abs ↗pdf ↗

Classification Protocols with Minimal Disclosurecs.CR

Protocol minimizes disclosure in classification tasks.

problem Ensuring minimal disclosure in classification protocols.

method Developed a protocol for multi-party classification that minimizes non-responsive document disclosure.

result Guarantees minimal disclosure of non-responsive documents.

classification disclosure multi-party machine learning e-discovery

2022-09-06abs ↗pdf ↗

Privacy Amplification by Missing Datastat.ML

Missing data enhances privacy in differential privacy.

problem Privacy preservation in datasets with missing values.

method Formalized missing data as a privacy amplification mechanism within differential privacy.

result Incomplete data can yield privacy amplification for differentially private algorithms.

differential privacy missing data privacy preservation data analysis

2026-02-02abs ↗pdf ↗

Streaming Adaptation of Deep Forecasting Models using Adaptive Recurrent Unitscs.LG

We present ARU, an Adaptive Recurrent Unit for streaming adaptation of deep globally trained time-series forecasting models. The ARU combines the advantages of learning complex data transformations across multiple time series from deep global models, with per-series localization offered by closed-form linear models. Un…

2019-06-24abs ↗pdf ↗

Modelling of Sickle Cell Anemia Patients Response to Hydroxyurea using Artificial Neural Networksq-bio.QM

Model predicts HU response for sickle cell patients.

problem Predicting which sickle cell patients will respond to Hydroxyurea.

method Developed Deep Artificial Neural Network models.

result 92.6% accuracy in predicting HbF response.

Sickle Cell Anemia Hydroxyurea Artificial Neural Networks Hemoglobin F Patient Response

2019-11-25abs ↗pdf ↗

Outliers Detection in Networks with Missing Linksstat.ML

New algorithm detects network outliers with missing links.

problem Identifying outliers in networks with missing links.

method Proposes a new algorithm that detects outliers and predicts missing links.

result Proves the algorithm exactly detects outliers and achieves best error for missing link prediction.

network analysis outliers detection missing links statistical soundness polynomial computation

2019-11-29abs ↗pdf ↗

Instability, Computational Efficiency and Statistical Accuracycs.LG

The study analyzes the performance of statistical estimators under stability and computational efficiency.

problem Understanding the performance of statistical estimators in relation to stability and computational efficiency.

method Developed a framework to bound statistical accuracy based on the interplay between algorithm convergence rates and stability.

result Unstable algorithms can achieve the same statistical accuracy as stable ones in fewer steps.

statistical estimation stability computational efficiency gradient descent Newton's method

2020-05-22abs ↗pdf ↗

Are deep learning models superior for missing data imputation in large surveys? Evidence from an empirical comparisoncs.LG

Deep learning models outperform MICE in large survey imputation but with hyperparameter tuning.

problem Comparing deep learning and MICE for missing data imputation in large surveys.

method Extensive simulation studies comparing four machine learning-based MI methods: MICE with classification trees, MICE with random forests, generative adversarial imputation networks, and multiple imputation using denoising autoencoders.

result MICE with classification trees consistently outperforms deep learning methods in terms of bias, mean squared error, and coverage.

deep learning missing data imputation machine learning classification trees

2021-03-14abs ↗pdf ↗

Predicting Individualized Effects of Internet-Based Treatment for Genito-Pelvic Pain/Penetration Disorder: Development and Internal Validation of a Multivariable Decision Tree Modelstat.AP

Study predicts internet-based treatment effects for GPPPD based on dyadic coping.

problem Identifying which patients will benefit most from internet-based GPPPD treatment.

method Developed a multivariable decision tree model using recursive partitioning.

result Predicts large effects for high dyadic coping patients, small effects for low dyadic coping patients.

GPPPD Internet-based treatment Decision tree Recursive partitioning Coping

2023-03-15abs ↗pdf ↗