相关论文: Comment: Fisher Lecture: Dimension Reduction in Re…
Rejoinder: 2004 IMS Medallion Lecture: Local Rademacher complexities and oracle inequalities in risk minimization [arXiv:0708.0083]
This is the revised version of a Comment on a paper by C. Escudero (Phys. Rev. Lett. 100, 116101, 2008; arXiv:0804.1898).
Comment on "Enhanced transmission through periodic arrays of subwavelength holes: the role of localized waveguide resonances" [Phys.Rev.Lett. 96, 233901 (2006)]
A comment on the Letter by Le Doussal and Wiese, Phys. Rev. Lett. 96, 197202 (2006).
Dimensionality reduction (DR) is a popular method for preparing and analyzing high-dimensional data. Reduced data representations are less computationally intensive and easier to manage and visualize, while retaining a significant…
Lecture given Thursday 22 October 1992 at a Mathematics-Computer Science Colloquium at the University of New Mexico. The lecture was videotaped; this is an edited transcript.
Supplementary Material for "Estimation of a Multiplicative Correlation Structure in the Large Dimensional Case"
These are lecture notes based on the first part of a course on 'Mathematical Data Science', which I taught to final year BSc students in the UK in 2019-2020. Topics include: concentration of measure in high dimensions; Gaussian random…
Some situations are discussed where subquantum oscillations in momentum arise in connectiion with Fisher information and the quantum potential.
Comment on ``Demystifying Double Robustness: A Comparison of Alternative Strategies for Estimating a Population Mean from Incomplete Data'' [arXiv:0804.2958]
Comment on ``Demystifying Double Robustness: A Comparison of Alternative Strategies for Estimating a Population Mean from Incomplete Data'' [arXiv:0804.2958]
Notes to lectures on the epsilon calculus, covering axioms, semantics, completeness, and the first epsilon theorem.
Rejoinder to "Feature Matching in Time Series Modeling" by Y. Xia and H. Tong [arXiv:1104.3073]
Lecture notes on optimization for machine learning, derived from a course at Princeton University and tutorials given in MLSS, Buenos Aires, as well as Simons Foundation, Berkeley.
These lecture notes cover advanced topics in linear regression, with an in-depth exploration of the existence, uniqueness, relations, computation, and non-asymptotic properties of the most prominent estimators in this setting. The covered…
Rejoinder of "Statistical Inference: The Big Picture" by R. E. Kass [arXiv:1106.2895]
In this contribution I discuss recent and ongoing progress on the inclusion of resummation effects in the fit of parton distributions.
Fisher's fiducial probability has recently received renewed attention under the name confidence. In this paper, we reformulate it within an extended-likelihood framework, a representation that helps to resolve many long-standing…
Comment on [math.ST/0612817]
This is a response to the commentaries on "CoRR: A Computing Research Repository".