Vanishing line for the descent spectral sequence

نویسندگان

چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Vanishing Point and Vanishing Line Estimation with Line Clustering

In conventional methods for detecting vanishing points and vanishing lines, the observed feature points are clustered into collections that represent different lines. The multiple lines are then detected and the vanishing points are detected as points of intersection of the lines. The vanishing line is then detected based on the points of intersection. However, for the purpose of optimization, ...

متن کامل

The E2-term of the descent spectral sequence for continuous G-spectra

Given a profinite group G with finite virtual cohomological dimension, let {Xi} be a tower of discrete G-spectra, each of which is fibrant as a spectrum, so that X = holimi Xi is a continuous G-spectrum, with homotopy fixed point spectrum XhG. The E2-term of the descent spectral sequence for π∗(X) cannot always be expressed as continuous cohomology. However, we show that the E2-term is always b...

متن کامل

Spectral Vanishing Viscosity Method for Nonlinear

We propose a new spectral viscosity (SV) scheme for the accurate solution of nonlinear conservation laws. It is proved that the SV solution converges to the unique entropy solution under appropriate reasonable conditions. The proposed SV scheme is implemented directly on high modes of the computed solution. This should be compared with the original nonperiodic SV scheme introduced by Maday, Oul...

متن کامل

A Free Line Search Steepest Descent Method for Solving Unconstrained Optimization Problems

In this paper, we solve unconstrained optimization problem using a free line search steepest descent method. First, we propose a double parameter scaled quasi Newton formula for calculating an approximation of the Hessian matrix. The approximation obtained from this formula is a positive definite matrix that is satisfied in the standard secant relation. We also show that the largest eigen value...

متن کامل

Stochastic Spectral Descent for Restricted Boltzmann Machines

Restricted Boltzmann Machines (RBMs) are widely used as building blocks for deep learning models. Learning typically proceeds by using stochastic gradient descent, and the gradients are estimated with sampling methods. However, the gradient estimation is a computational bottleneck, so better use of the gradients will speed up the descent algorithm. To this end, we first derive upper bounds on t...

متن کامل

ذخیره 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: Archiv der Mathematik

سال: 2003

ISSN: 0003-889X,1420-8938

DOI: 10.1007/s00013-003-4626-z