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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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5 results for “multi-filtering”

Attribute2vec: Deep Network Embedding Through Multi-Filtering GCNcs.LG

Advances deep network embedding through multi-filtering GCN.

problem Existing attribute embedding methods fail to capture different aspects of node features.

method Multi-filtering Graph Convolution Neural Network (GCN) framework.

result Significant improvement in link prediction and node classification tasks with limited training data.

network embedding GCN multi-filtering deep learning attribute2vec

2020-04-03abs ↗pdf ↗

MuRiT: Efficient Computation of Pathwise Persistence Barcodes in Multi-Filtered Flag Complexes via Vietoris-Rips Transformationsmath.AT

MuRiT efficiently computes multi-parameter persistence barcodes.

problem Efficient computation of multi-parameter persistent homology.

method Vietoris-Rips transformation to reduce multi-parameter to single-parameter computation.

result MuRiT computes pathwise persistence barcodes for multi-filtered flag complexes.

persistent homology multi-parameter Vietoris-Rips flag complexes pathwise barcodes

2022-07-07abs ↗pdf ↗

List-Decodable Mean Estimation via Iterative Multi-Filteringcs.LG

New method estimates mean from noisy data with few outliers.

problem Estimate mean from noisy data with few outliers.

method Iterative multi-filtering approach.

result Achieves near-optimal error with practical efficiency.

mean estimation list-decodable spectral techniques outlier removal

2020-06-18abs ↗pdf ↗

A Spectral Algorithm for List-Decodable Covariance Estimation in Relative Frobenius Normcs.DS

Algorithm estimates covariance from noisy data efficiently.

problem Estimating covariance from a noisy set of points.

method Spectral techniques for list-decodable covariance estimation.

result Efficient algorithm with poly(1/α) sample and time complexity.

covariance estimation spectral methods list-decodable Gaussian mixture models relative Frobenius norm

2023-05-01abs ↗pdf ↗

Clustering Mixture Models in Almost-Linear Time via List-Decodable Mean Estimationcs.DS

New algorithm clusters data with almost-linear time, robust to corruption.

problem Clustering mixtures of distributions with adversarial corruption.

method List-decodable mean estimation, robust mean estimation, iterative multi-filtering.

result First almost-linear time algorithms for clustering mixtures of k well-behaved distributions.

clustering mixtures mean estimation robust list-decodable

2021-06-16abs ↗pdf ↗