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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.

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0111 · Jun 201919922001200920172026
1 result for “HDAIC”
Model selection for high-dimensional linear regression with dependent observationsstat.ML

OGA and HDAIC improve high-dimensional regression with dependent data.

problem High-dimensional linear regression with dependent observations.
method Orthogonal greedy algorithm (OGA) and high-dimensional Akaike's information criterion (HDAIC).
result OGA and HDAIC achieve optimal convergence rate without knowing sparsity.
high-dimensional regressiondependent observationsOGAHDAICAkaike's information criterion
2019-06-18abs ↗pdf ↗