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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.

169,291 papers · 148 categories

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5 results for “Dimension-robust”

Dimension-Robust MCMC in Bayesian Inverse Problemsstat.ME

Develops efficient MCMC for Bayesian inverse problems, robust to high dimensions.

problem Efficient exploration of posterior distributions in high-dimensional latent states.

method Non-centred parameterizations and dimension-robust samplers for latent Gaussian processes.

result Framework is dimension-robust, maintaining efficiency as dimension increases.

Bayesian inverse problems MCMC sampling Dimension-robust Non-centred parameterizations Latent Gaussian processes

2018-03-09abs ↗pdf ↗

Transductive Robust Learning Guaranteescs.LG

Adversarial robust learning improved for transductive setting.

problem Adversarial robust learning in transductive setting.

method Simple transductive learner for bounded VC dimension classes.

result Robust error rate linear in VC dimension, adaptive to perturbation complexity.

Adversarial robustness Transductive learning VC dimension Robust error

2021-10-20abs ↗pdf ↗

Low-dimensional Data Embedding via Robust Rankingcs.AI

A new method for embedding data in low dimensions, robust to noise.

problem Finding high-quality embeddings in noisy data.

method Formulates embedding as a robust ranking problem over triplets.

result Produces better embeddings with less noise and faster computation.

data embedding robust ranking low-dimensional space signature datasets

2016-11-30abs ↗pdf ↗

Robust Mean Estimation in High Dimensions via

\ell_0

Minimizationstat.ML

New method estimates robust mean in high dimensions with minimized outliers.

problem Estimating the mean in high dimensions when a fraction of data is corrupted.

method Formulating the problem as

\ell_0

-norm minimization under second moment constraints, and using

\ell_1

and

\ell_p

minimization techniques.

result The proposed method achieves order optimal robust mean estimation and significantly outperforms existing methods.

mean estimation high dimensions robust statistics compressive sensing minimization

2020-08-21abs ↗pdf ↗

Transfer-Learning Across Datasets with Different Input Dimensions: An Algorithm and Analysis for the Linear Regression Casestat.ML

New algorithm combines new and historical data with different input dimensions for linear regression.

problem Combining new and historical data with different input dimensions for improved accuracy.

method Proposes a transfer learning algorithm with rigorous theoretical robustness analysis.

result Achieves state-of-the-art performance on 9 real-life datasets.

transfer learning linear regression different input dimensions robustness machine learning

2022-02-10abs ↗pdf ↗