Last ten or so pubs of Manfred K. Warmuth

Last ten or so pubs of Manfred K. Warmuth

  • Robust Bi-Tempered Logistic Loss Based on Bregman Divergences arXiv

  • Divergence-Based Motivation for Online EM and Combining Hidden Variable Models arXiv

  • Unlabeled sample compression schemes and corner peelings for ample and maximum classes ICALP19 paper
    To appear in ICALP 2019

  • Minimax experimental design: Bridging the gap between statistical and worst-case approaches to least squares regression COLT19 paper

  • Adaptive scale-invariant online algorithms for learning linear models ICML19 paper supplement

  • Two-temperature logistic regression based on the Tsallis divergence AISTAT19 paper supplement

  • Online Non-Additive Path Learning under Full and Partial Information, ALT19 paper talk

  • Unbiased estimators for random design regression. Expanded paper about the below two conference papers. journal submission

  • Correcting the bias in least squares regression with volume-rescaled sampling AISTAT19 paper supplement

  • Leveraged volume sampling for linear regression NIPS18 paper supplement

  • Reverse iterative volume sampling for linear regression
    Journal paper about the following 2 conference papers and more [JMLR paper]
    Long talk about volume sampling [talk]

  • Subsampling for Ridge Regression via Regularized Volume Sampling [AISTATS18 paper] [talk]

  • Unbiased estimates for linear regression via volume sampling [NIPS17 paper] [poster]

  • Online dynamic programming [NIPS17 paper]