相关论文: Comment on "Support Vector Machines with Applicati…

Comment on paper "Towards a bulk theory of flexoelectricity" by R.Resta [Phys.Rew. Lett. v. 105, 127601 (2010)]

Kernel-based support vector machines (SVMs) are supervised machine learning algorithms for classification and regression problems. We introduce a method to train SVMs on a D-Wave 2000Q quantum annealer and study its performance in…

Lecture notes on quantum machine learning for computer scientists.

We give a survey of the foundations of statistical queries and their many applications to other areas. We introduce the model, give the main definitions, and we explore the fundamental theory statistical queries and how how it connects to…

Comment on "New Mean-Field Theory of the tt't"J Model Applied to the High-Tc Superconductors" by T. C. Ribeiro and X.-G. Wen [cond-mat/0410750; Physical Review Letters 95, 057001 (2005)].

Based on easy-to-follow considerations it is not difficult to be vehemently opposed not only the solutions found in that paper but also the conclusions manifested there.

A compendium for outsiders.

We comment on recent e-print by L. Mardoyan et al. [cond-mat/0609768]

This is a reply to a comment on our work recently posted in arXiv. To our knowledge, this comment has not been published anywhere else. We show that the points raised in the comment are invalid

Support Vector Machines have been a popular topic for quite some time now, and as they develop, a need for new methods of feature selection arises. This work presents various approaches SVM feature selection developped using new tools such…

Comment on "Indispensable Finite Time Correlations for Fokker-Planck Equations from Time Series Data"

Reply to comment appeared on hep-lat/9912014.

We survey some recent applications of machine learning to problems in geometry and theoretical physics. Pure mathematical data has been compiled over the last few decades by the community and experiments in supervised, semi-supervised and…

Survey article on the geometry of spherical varieties. Invited survey for Transformation Groups.

This is a reply to the paper by S.C.Benjamin, quant-ph/0008127.

Comment on "Quantifying the Fraction of Missing Information for Hypothesis Testing in Statistical and Genetic Studies" [arXiv:1102.2774]

Comment on "Quantifying the Fraction of Missing Information for Hypothesis Testing in Statistical and Genetic Studies" [arXiv:1102.2774]

The Support Vector Machine (SVM) of Vapnik (1998) has become widely established as one of the leading approaches to pattern recognition and machine learning. It expresses predictions in terms of a linear combination of kernel functions…

The goal of the article is to get a satisfactory theory of cosupport in the derived category $\mathrm{D}(R)$, this is done by introducing another versions of the "big" and "small" cosupport for complexes. We provide some properties for…

Short review article on quantum computation accepted for Supplement III, Encyclopaedia of Mathematics (publication expected Summer 2001). See also http://www.wkap.nl/series.htm/ENM