A Multi-step Nonlinear Dimension-reduction Approach with Applications to Bigdata
نویسندگان
چکیده
منابع مشابه
Variational dimension reduction in nonlinear elasticity: a Young measure approach
Starting form 3D elasticity, we deduce the variational limit of the string and of the membrane on the space of one and two-dimensional gradient Young measures, respectively. The physical requirement that the energy becomes infinite when the volume locally vanishes is taken into account in the string model. The rate at which the energy density blows up characterizes the effective domain of the l...
متن کاملNonlinear Dimension Reduction
A series of different data sets were used for testing eight different non-linear dimension reduction methods. The data sets provided insight to various ways of using the methods and to their applications. The results are compared for the different methods and reasons for their behaviour is searched for. Results are mostly quite encouraging and usable.
متن کاملA Semiparametric Approach to Dimension Reduction.
We provide a novel and completely different approach to dimension-reduction problems from the existing literature. We cast the dimension-reduction problem in a semiparametric estimation framework and derive estimating equations. Viewing this problem from the new angle allows us to derive a rich class of estimators, and obtain the classical dimension reduction techniques as special cases in this...
متن کاملthe aesthetic dimension of howard barkers art: a frankfurtian approach to scenes from an execution and no end of blame
رابطه ی میانِ هنر و شرایطِ اجتماعیِ زایش آن همواره در طولِ تاریخ دغدغه ی ذهنی و دل مشغولیِ اساسیِ منتقدان و نیز هنرمندان بوده است. از آنجا که هنر در قفس آهنیِ زندگیِ اجتماعی محبوس است، گسترش وابستگیِ آن با نهاد ها و اصولِ اجتماعی پیرامون، صرفِ نظر از هم سو بودن و یا غیرِ هم سو بودنِ آن نهاد ها، امری اجتناب ناپذیر به نظر می رسد. با این وجود پدیدار گشتنِ چنین مباحثِ حائز اهمییتی در میان منتقدین، با ظهورِ مکتب ما...
Dimension reduction in functional regression with applications
Two dimensional reduction regression methods to predict a scalar response from a discretized sample path of a continuous time covariate process are presented. The methods take into account the functional nature of the predictor and are both based on appropriate wavelet decompositions. Using such decompositions, we derive prediction methods that are similar to minimum average variance estimation...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Procedia Computer Science
سال: 2018
ISSN: 1877-0509
DOI: 10.1016/j.procs.2018.10.507