Related papers: Comment on "Support Vector Machines with Applicati…

We present a new approach to obtaining photometric redshifts using a kernel learning technique called Support Vector Machines (SVMs). Unlike traditional spectral energy distribution fitting, this technique requires a large and…

A comment on ``Comment on ``Standard Model Mass Spectrum and Interactions In The Holomorphic Unified Field Theory""

Comment on recent paper by I. Horv\'ath and P. Marko\v{s}, "Super-universality in Anderson localization", Phys. Rev. Lett. 129, 106601 (2022) [arXiv:2110.11266].

The article presents a new method of integration of functions with values in Banach spaces. This integral and related notions prove to be a useful tool in the study of Banach space geomtry.

We make several comments on "Note on the Analytical Solution of the Rabi Model" (arXiv:1210.4946).

A comment to the paper by S. Chen, H. B\"uttner, and J. Voit, [Phys. Rev. Lett. {\bf 87}, 087205 (2001)].

Accurate transient stability assessment is a crucial prerequisite for proper power system operation and planning with various operational constraints. Transient stability assessment of modern power systems is becoming very challenging due…

We reply to the criticism raised by Volovik in his Comment (cond-mat/9805159) and by Hirschfeld et al. in their Comment (cond-mat/9806085).

A sequence function alternative representation of state machines.

Rejoinder: Monitoring Networked Applications With Incremental Quantile Estimation [arXiv:0708.0302]

We give a new proof of Theorem 6 in [L. Qiu and X. Zhan, On the span of Hadamard products of vectors, Linear Algebra Appl. 422 (2007) 304--307].

Comment on ``Gibbs Sampling, Exponential Families and Orthogonal Polynomials'' [arXiv:0808.3852]

Support vector machines (SVMs) are special kernel based methods and belong to the most successful learning methods since more than a decade. SVMs can informally be described as a kind of regularized M-estimators for functions and have…

We propose a method for support vector machine classification using indefinite kernels. Instead of directly minimizing or stabilizing a nonconvex loss function, our algorithm simultaneously computes support vectors and a proxy kernel matrix…

A support vector machine (SVM) is an algorithm that finds a hyperplane which optimally separates labeled data points in $\mathbb{R}^n$ into positive and negative classes. The data points on the margin of this separating hyperplane are…

This is a Reply to the Comment posted as arXiv:1207.1261.

Comment on ``Wigner phase space description of a Morse oscillator''

I comment on a recent preprint "Neutrino Velocity Anomalies: A Resolution without a Revolution" that appeared recently as arXiv:1110.0989 [hep-ph]

This paper is a comment to M Wilkinson, EPL 106 (2014) 40001, arXiv:1401.4620 [physics.ao-ph,cond-mat.soft], which draws conclusion from our data that are at variance with our observations.

We remark on the validity of the concerns raised in the comment(cond-mat/0304626) by Fal'ko, Lerner, Tsyplyatyev, and Aleiner..