budgets cuts

What would you do?

Mei Po runs a small artisan shop that makes decorations and gifts for the Chinese New Year. Unique hand-crafted touches and a great word-of-mouth reputation keep her products in high demand.

Recently, Mei Po learned that the space next door was available to lease. The timing was right as she was looking to expand her business. But as she reviewed the loan application, she noticed that in addition to a business plan, she needed to prepare a one-year budget. Mei Po was taken aback.

She planned her cash-

What would you do?

Mei Po runs a small artisan shop that makes decorations and gifts for the Chinese New Year. Unique hand-crafted touches and a great word-of-mouth reputation keep her products in high demand.

Recently, Mei Po learned that the space next door was available to lease. The timing was right as she was looking to expand her business. But as she reviewed the loan application, she noticed that in addition to a business plan, she needed to prepare a one-year budget. Mei Po was taken aback.

She planned her cash-

规范化切割和图像分割

摘要：为解决在视觉上的感知分组的问题，我们提出了一个新的方法。我们目的是提取图像的总体印象，而不是只集中于局部特征和图像数据的一致性。我们把图像分割看成一个图形的划分问题，并且提出一个新的分割图形的全球标准，规范化切割。这一标准衡量了不同组之间的总差异和总相似。我们发现基于广义特征值问题的一个高效计算技术可以用于优化标准。我们已经将这种方法应用于静态图像和运动序列，发现结果是令人鼓舞的。

1简介

近75年前，韦特海默推出的“格式塔”的方法奠定了感知分组和视觉感知组织的重 要性。我的目的是，分组问题可以通过考虑图（1）所示点的集合而更加明确。

通常人类观察者在这个图中会看到四个对象，一个圆环和内部的一团点以及右侧两个松散的点团。然而这并不是唯一的分割情况。有些人认为有三个对象，可以将右侧的两个认为是一个哑铃状的物体。或者只有两个对象，右侧是一个哑铃状的物体，左侧是一个类似结构的圆形星系。如果一个人倒行逆施，他可以认为事实上每一个点是一个不同的对象。

这似乎是一个人为的例子，但每一次图像分割都会面临一个相似的问题—将一个图像的区域D划分成子集Di会有许多可能的划分方式（包括极端的将每一个像素认为是一个单独的

Kernel k-means,Spectral Clustering and Normalized Cuts

Inderjit S.Dhillon Dept.of Computer Sciences University of Texas at Austin Austin,TX78712 inderjit@8db44e052379168884868762caaedd3383c4b5db

Yuqiang Guan

Dept.of Computer Sciences

University of Texas at Austin

Austin,TX78712

yguan@8db44e052379168884868762caaedd3383c4b5db

Brian Kulis

Dept.of Computer Sciences

University of Texas at Austin

Austin,TX78712

kulis@8db44e052379168884868762caaedd3383c4b5db

ABSTRACT

Kernel k-means and spectral clustering have both been used to identify cluste