Optimal Expected-Distance Separating Halfspace

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

Optimal Expected-Distance Separating Halfspace

One recently proposed criterion to separate two datasets in discriminant analysis, is to use a hyperplane which minimises the sum of distances to it from all the misclassified data points. Here all distances are supposed to be measured by way of some fixed norm, while misclassification means lying on the wrong side of the hyperplane, or rather in the wrong halfspace. In this paper we study the ...

متن کامل

Optimal distance separating halfspace ∗

One recently proposed criterion to separate two datasets in discriminant analysis, is to use a hyperplane which minimises the sum of distances to it from all the misclassified data points. Here all distances are supposed to be measured by way of some fixed norm, while misclassification means lying on the wrong side of the hyperplane, or rather in the wrong halfspace. In this paper we study the ...

متن کامل

Unified Distance Formulas for Halfspace Fog

In many real-time rendering applications, it is necessary to model a fog volume that is bounded by a single plane but is otherwise infinite in extent. This paper presents unified formulas that provide the correct distance traveled through a fog halfspace for all possible camera and surface point locations. Such formulas effectively remove the need to code for multiple cases separately, thereby ...

متن کامل

Optimal halfspace range reporting in three dimensions

We give the first optimal solution to a standard problem in computational geometry: three-dimensional halfspace range reporting. We show that n points in 3-d can be stored in a linear-space data structure so that all k points inside a query halfspace can be reported in O(log n + k) time. The data structure can be built in O(n logn) expected time. The previous methods with optimal query time req...

متن کامل

Learning Expected Hitting Time Distance

Most distance metric learning (DML) approaches focus on learning a Mahalanobis metric for measuring distances between examples. However, for particular feature representations, e.g., histogram features like BOW and SPM, Mahalanobis metric could not model the correlations between these features well. In this work, we define a nonMahalanobis distance for histogram features, via Expected Hitting 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: Mathematics of Operations Research

سال: 2008

ISSN: 0364-765X,1526-5471

DOI: 10.1287/moor.1070.0309