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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.

169,181 papers · 148 categories

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48 results for Median

Study on median algebra structures on Euclidean spaces and manifolds with local CAT(0) cubulation.

problem Understanding median algebra structures on Euclidean spaces and manifolds.
method Showed local CAT(0) cubulation for median structures on ER homology manifolds.
result Median structures on ER homology manifolds have a local CAT(0) cubulation structure.

A method for estimating the median of gradients in stochastic optimization.

problem Robust gradient estimation in stochastic optimization for various applications.
method Stochastic Proximal Point Method for median gradient estimation.
result The proposed method can converge even under heavy-tailed, state-dependent noise.

This paper introduces online algorithms to estimate robust geometric median in large data streams.

problem Detecting outliers in large data sets using robust statistical measures.
method Online stochastic Newton methods for estimating the geometric median.
result Rates of convergence for online estimation of the geometric median.

The study finds that maximizing median returns is the only viable strategy in portfolio selection.

problem Difficulties in studying optimal portfolio strategies due to discontinuity and time inconsistency in maximizing median and quantile returns.
method Used intra-personal equilibrium approach to analyze portfolio selection under median and quantile maximization.
result Median maximization is the only viable strategy, with no investment in risky assets for other quantiles.

Median sampling reduces the runtime of noisy evolutionary optimization problems.

problem Reduction of noise's negative effect in evolutionary optimization.
method Introducing median sampling into evolutionary algorithms and analyzing its performance.
result Median sampling reduces the expected runtime exponentially under onebit noise.

The consistency of Fréchet medians is proved for probability measures in proper metric spaces. In the context of Riemannian manifolds, assuming that the probability measure has more than a half mass lying in a convex ball and verifies some concentration conditions, the positions of its Fréchet medians are estimated. It…

2011-10-18abs ↗pdf ↗

This paper tackles ranking preferences through local consensus, improving prediction accuracy.

problem Predicting individual preferences over a set of items based on observed characteristics.
method Proposes ranking median regression, introducing local consensus/median for efficient learning.
result Developed efficient methods for ranking median regression, achieving fast learning rates.

In high dimensions, the mean and geometric median are nearly identical.

problem Understanding the relationship between mean and geometric median in high-dimensional spaces.
method Analytical derivation and simulation of the distance between mean and geometric median.
result The distance between mean and geometric median vanishes with dimensionality in high dimensions.

Median-of-means sampling outperforms mean-of-means for large sample sizes in numerical integration.

problem Improving numerical integration accuracy in high dimensions.
method Median-of-means sampling compared to mean-of-means using RQMC methods.
result Median-of-means sampling is superior for large sample sizes, while mean-of-means is better for smaller sample sizes.

Upper bound for Hausdorff distance between hyperbolic space and its medianization.

problem Calculating the Hausdorff distance between hyperbolic space and its medianization.
method Using de Sitter space to model finite-dimensional hyperbolic space and its medianization, calculating the Hausdorff distance.
result An upper bound for the Hausdorff distance between hyperbolic space and its medianization is calculated.

Paper proposes a novel method to improve matrix completion with median loss for large datasets.

problem Matrix completion with absolute deviation loss for large-scale data.
method Proposes a refinement step using pseudo data to improve inefficient estimators of median matrix completion.
result Turns inefficient estimators into a rate (near-)optimal matrix completion procedure.

An efficient algorithm for k-median clustering in a sequential setting without substitutions.

problem Clustering a sequence of examples without being able to substitute centers later.
method An efficient algorithm with a multiplicative approximation factor of twice the offline algorithm's factor, and an optimal offline algorithm.
result The efficient algorithm achieves a good approximation of the optimal offline solution.

Study shows Roller compactification's median graph has limited asymptotic dimension.

problem Understanding the asymptotic dimension of Roller compactifications.
method Proved using finite dimensional CAT(0) cube complexes and Borel median graph.
result Borel asymptotic dimension is bounded by the complex's dimension.

New method for estimating median and mean with high probability privacy.

problem Estimating median and mean with differential privacy.
method Propose, Test, Release (PTR) mechanism with concentration inequalities.
result First sub-Gaussian high probability bounds for differentially private median and mean estimation.

Robust nonparametric regression method removes adversarial noise effectively.

problem Nonparametric regression under adversarial noise contamination.
method Local binning median followed by kernel smoothing or local polynomial regression.
result Minimax optimality over Hölder and Sobolev classes with arbitrary smoothness.

Improved private geometric median estimation with nearly-linear time complexity.

problem Estimating the geometric median of a dataset while maintaining privacy.
method Improved algorithm using subsampling and geometric aggregation, achieving nearly-linear runtime.
result Achieves the same approximation quality as previous methods but with nearly-linear runtime.

New method explains survival analysis models using median-SHAP.

problem Need for explainable AI in medical applications, especially for survival analysis.
method Introduces median-SHAP for explaining survival analysis models.
result Conventionally used mean anchor point can lead to misleading interpretations; median-SHAP provides a better approach.

The paper improves marine buoy placement to detect ships robustly against disruptions.

problem Detecting fishing vessels in the presence of natural and man-made disruptions.
method Formulated as a clustering problem, used dropout k-means and k-median to improve buoy placement robustness.
result Improved ship detection probability with dropout k-means compared to classic methods.

Groups with specific properties have similar cubulations and coarse median structures.

problem Understanding the structure of certain groups through cubical coarsening.
method Analyzing right-angled Artin and Coxeter groups, focusing on automorphisms and cubulations.
result Automorphisms of specific groups preserve coarse median structures and have nice fixed subgroups.

Paper shows how to use geometric median for robust SGD in high dimensions.

problem Robustifying SGD for high-dimensional optimization problems with gross corruption.
method Applying geometric median to only chosen blocks of coordinates at a time.
result Retains optimal breakdown point of 0.5 for smooth non-convex problems.

This paper investigates the phase retrieval problem, which aims to recover a signal from the magnitudes of its linear measurements. We develop statistically and computationally efficient algorithms for the situation when the measurements are corrupted by sparse outliers that can take arbitrary values. We propose a nove…

2016-03-11abs ↗pdf ↗