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  1. ; ; ( , Journal of machine learning research)
    Large-scale panel data is ubiquitous in many modern data science applications. Conventional panel data analysis methods fail to address the new challenges, like individual impacts of covariates, endogeneity, embedded low-dimensional structure, and heavy-tailed errors, arising from the innovation of data collection platforms on which applications operate. In response to these challenges, this paper studies large-scale panel data with an interactive effects model. This model takes into account the individual impacts of covariates on each spatial node and removes the exogenous condition by allowing latent factors to affect both covariates and errors. Besides, we waive the sub-Gaussian assumption and allow themore »errors to be heavy-tailed. Further, we propose a data-driven procedure to learn a parsimonious yet flexible homogeneity structure embedded in high-dimensional individual impacts of covariates. The homogeneity structure assumes that there exists a partition of regression coeffcients where the coeffcients are the same within each group but different between the groups. The homogeneity structure is flexible as it contains many widely assumed low dimensional structures (sparsity, global impact, etc.) as its special cases. Non-asymptotic properties are established to justify the proposed learning procedure. Extensive numerical experiments demonstrate the advantage of the proposed learning procedure over conventional methods especially when the data are generated from heavy-tailed distributions.« less
    Accepted Manuscript Full Text Available
  2. ; ; ; ; ; ; ; ; ; ( , Physical Review B)
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  3. ; ; ( , Physical Review A)
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  4. ; ; ; ; ; ; ; ; ; ; et al ( , Physical Review Letters)
    Free, publicly-accessible full text available March 1, 2022
  5. ; ; ; ; ; ; ; ; ; ; et al ( , Physical Review Letters)
    Free, publicly-accessible full text available February 1, 2022
  6. ; ; ; ; ; ; ; ; ; ; et al ( , Journal of High Energy Physics)
    A bstract Searches are performed for a low-mass dimuon resonance, X , produced in proton-proton collisions at a center-of-mass energy of 13 TeV, using a data sample corresponding to an integrated luminosity of 5.1 fb − 1 and collected with the LHCb detector. The X bosons can either decay promptly or displaced from the proton-proton collision, where in both cases the requirements placed on the event and the assumptions made about the production mechanisms are kept as minimal as possible. The searches for promptly decaying X bosons explore the mass range from near the dimuon threshold up to 60 GeV,more »with nonnegligible X widths considered above 20 GeV. The searches for displaced X → μ + μ − decays consider masses up to 3 GeV. None of the searches finds evidence for a signal and 90% confidence-level exclusion limits are placed on the X → μ + μ − cross sections, each with minimal model dependence. In addition, these results are used to place world-leading constraints on GeV-scale bosons in the two-Higgs-doublet and hidden-valley scenarios.« less
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  7. ; ; ; ; ; ; ; ; ; ; et al ( , Physical Review Letters)
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  8. ; ; ; ; ; ; ; ; ; ; et al ( , Physical Review Letters)
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  9. ; ; ; ; ; ; ; ; ; ; et al ( , Physical Review D)
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  10. ; ; ; ; ; ; ; ; ; ; et al ( , Physical Review Letters)
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