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.

169,341 papers · 148 categories

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3 results for “CORE-clustering”

COREclust: a new package for a robust and scalable analysis of complex datacs.MS

COREclust detects representative variables in high-dimensional data.

problem Detecting representative variables in high-dimensional data with limited observations.

method CORE-clustering algorithm detects CORE-clusters, variable sets with similar variables, and representative variables are estimated as CORE-cluster centers.

result The CORE-clustering algorithm can handle large datasets efficiently.

variable selection high-dimensional data CORE-clustering robust estimation graph clustering

2018-05-25abs ↗pdf ↗

Clustering with Confidence: Finding Clusters with Statistical Guaranteesstat.ML

New method finds robust clusters with statistical guarantees.

problem Clustering solutions are unstable and lack robustness guarantees.

method Quantifies cluster instability and finds robust clusters (core clusters).

result Core clusters are more stable and robust to changes in data.

clustering robustness statistical guarantees core clusters largest maximal cliques

2016-12-27abs ↗pdf ↗

Computing Web-scale Topic Models using an Asynchronous Parameter Servercs.DC

APS-LDA scales topic modeling to web-scale data using Spark.

problem Scaling topic models to web-scale data.

method Integrates Spark with LDA using an asynchronous parameter server.

result APS-LDA processes up to 135x more data and 10x more topics than Spark LDA.

topic modeling web-scale Spark Latent Dirichlet Allocation asynchronous parameter server

2016-05-24abs ↗pdf ↗