Factor graph In probability theory and its applications, a factor graph is a particular type of graphical model, with applications in Bayesian inference, that enables efficient computation of marginal distributions through the sum-product algorithm. One of the important success stories of factor graphs and the sum-product algorithm is the decoding of capacity-approaching error-correcting codes, such as LDPC and turbo codes. A factor graph is an example of a hypergraph, in that an arrow (i.e., a factor node) can connect more than one (normal) node.
Prof. Dr. Wolfram Burgard I am a professor for computer science at the University of Freiburg and head of the research lab for Autonomous Intelligent Systems. My areas of interest lie in artificial intelligence and mobile robots. My research mainly focuses on the development of robust and adaptive techniques for state estimation and control. Over the past years my group and I have developed a series of innovative probabilistic techniques for robot navigation and control. They cover different aspects such as localization, map-building, SLAM, path-planning, exploration, and several other aspects. In my previous position from 1996 to 1999 at the University of Bonn I was head of the research lab for Autonomous Mobile Systems.
The Machine is Us/ing Us Final Version - Digital Ethnography Click here to download as a 3Mbps WMV file (55 MB) Click here to download in Quicktime format (96 MB) On January 31st I released the 2nd draft of The Machine is Us/ing Us hoping to receive feedback from my colleagues. (The first draft was only seen by my Digital Ethnography class 2 days before the 2nd draft was released on YouTube.) I sent it to 10 people. Data Mining: Finding Similar Items and Users Because we want to give kick-ass product recommendations. I'm showing you how to find related items based on a really simple formula. If you pay attention, this technique is used all over the web (like on Amazon) to personalize the user experience and increase conversion rates. To get one question out of the way: there are already many available libraries that do this, but as you'll see there are multiple ways of skinning the cat and you won't be able to pick the right one without understanding the process, at least intuitively. Defining the Problem To find similar items to a certain item, you've got to first define what it means for 2 items to be similar and this depends on the problem you're trying to solve:
Henry Kautz Henry Kautz is Chair of the Department of Computer Science and Director of the Institute for Data Science at the University of Rochester. He performs research in social media, machine learning, pervasive computing, search algorithms, and assistive technology. His academic degrees are an A.B. in mathematics from Cornell University, an M.A. in Creative Writing from the Johns Hopkins University, an M.Sc. in Computer Science from the University of Toronto, and a Ph.D. in computer science from the University of Rochester.
Bucket - XKCD Wiki Bucket has an outer shell of metal; within the metal is a protective layer of high density plastic, in which may or may not reside pure HOH. There can only be speculation about what else the Bucket contains. Do not make our Bucket stupid or mean. Any stupiding of the Bucket will get you warned, kicked, and then banned. Oded Goldreich ("fancy" homepage) Mailing Address Oded Goldreich Faculty of Mathematics and Computer Science Weizmann Institute of Science Rehovot, Israel [Home] [Research] [People] [Events] [Contact] [Links] 5 of the Best Free and Open Source Data Mining Software The process of extracting patterns from data is called data mining. It is recognized as an essential tool by modern business since it is able to convert data into business intelligence thus giving an informational edge. At present, it is widely used in profiling practices, like surveillance, marketing, scientific discovery, and fraud detection. There are four kinds of tasks that are normally involve in Data mining: * Classification - the task of generalizing familiar structure to employ to new data* Clustering - the task of finding groups and structures in the data that are in some way or another the same, without using noted structures in the data.* Association rule learning - Looks for relationships between variables.* Regression - Aims to find a function that models the data with the slightest error.
One World. One humanity. One destiny. Tim Flannery is on a mission. He believes that human activity is drastically altering the earth's climate, and that before too long these changes will have a devastating effect on life on this planet. He wants to mobilize the social and political will to address this problem before it's too late. That's why Tim Flannery wrote The Weather Makers: How Man Is Changing the Climate and What It Means for Life on Earth. LingPipe Home How Can We Help You? Get the latest version: Free and Paid Licenses/DownloadsLearn how to use LingPipe: Tutorials Get expert help using LingPipe: Services Join us on Facebook What is LingPipe? LingPipe is tool kit for processing text using computational linguistics. LingPipe is used to do tasks like: Find the names of people, organizations or locations in newsAutomatically classify Twitter search results into categoriesSuggest correct spellings of queries
Open Source Text Analytics by Seth Grimes Open source is a great choice for many text analytics users, especially folks who have programming skills, who need custom capabilities or who are trying to get a feel for possibilities before committing themselves. Excellent options are available for all these users. Tools such as Gate, NLTK, R and RapidMiner share the low cost, power, flexibility and community that have driven adoptionof open-source software by individual users and enterprises alike. RapidMiner even combines text processing with business intelligence (BI) and visualization functions. This article will look at open source text analytics, focusing on those four tools.