Linear Kernels and Linear-Time Algorithms for Finding Large Cuts

Linear Time Algorithms for Finding

Finding 2 d ham sandwich cuts in linear time ∗

A ham sandwich cut in d dimensions is a (d − 1)-dimensional hyperplane that divides each of d objects in half. While the existence of such a hyperplane was shown in 1938, little is known about how to find one. We are the first to show how this can be done in 2 dimensions when both objects are (possibly overlapping) convex polygons. Our algorithm runs in O(N) time where N is the sum of the numbe...

Linear Time Algorithms for Finding Maximal Forward References

In this paper, two algorithms are designed for finding maximal forward references from very large Web logs, longest sequences of Web pages visited by a user without revisiting some previously visited page in the sequence, and their performance is comparatively analyzed. It is shown that the two algorithms have linear (hence optimal) time complexity.

Laws of Large Numbers for Random Linear

The computational solution of large scale linear programming problems contains various difficulties. One of the difficulties is to ensure numerical stability. There is another difficulty of a different nature, namely the original data, contains errors as well. In this paper, we show that the effect of the random errors in the original data has a diminishing tendency for the optimal value as the...

Kernels for linear time invariant system identification

In this paper, we study the problem of identifying the impulse response of a linear time invariant (LTI) dynamical system from the knowledge of the input signal and a finite set of noisy output observations. We adopt an approach based on regularization in a Reproducing Kernel Hilbert Space (RKHS) that takes into account both continuous and discrete time systems. The focus of the paper is on des...