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  2. WHEN CAN YOU TRUST FEATURE SELECTION? – II: ON ...

    www.damtp.cam.ac.uk/research/afha/anders/InitialSubmitFeatureSelectionProbabilistic.pdf
    18 Dec 2023: entries. Then for each t > 0(1) limN P(δ > t) = et if each entry of A is exponentially distributed.(2) limN P(δ > tσ/. ... 6.2). As the distribution for the entries of A is absolutely continuous with respect to the Lebesgue measure on RN ,we can
  3. WHEN CAN YOU TRUST FEATURE SELECTION? – I: A ...

    www.damtp.cam.ac.uk/research/afha/anders/InitialSubmitFeatureSelectionDeterministic.pdf
    18 Dec 2023: 6. Hence, we will strengthen assumption (4.1) with the bounds (4.2) for the entries of Unij and bni. ... It follows that each entry of x̃S isnon-zero and that s(x̃)S = s(x)S and so,.
  4. COMPUTING SPECTRA – ON THE SOLVABILITY COMPLEXITY INDEX HIERARCHYAND…

    www.damtp.cam.ac.uk/research/afha/anders/SCI_FINAL.pdf
    20 Nov 2023: More generally, we can consideroperators with sparse matrices (only finitely many non-zero entries in each row and column) wheref captures the sparsity pattern.

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