Visit Original: Morning Radio Mysteries 1 "Kidnapped Sidekick"
2 wacky WRZR morning radio hosts must solve a mystery before the end of a 12 song rock block.
Author: blamesocietyfilms
Keywords: morning radio mystery scooby doo jimmy samson satire parody sketch series wacky kidnap
Added: July 31, 2008
Visit Original: Adobe CS: More on Typography in InDesign CS2
InDesign is the undisputed champ when it comes to Typography control in a page layout application. Special Guest Mike McHugh. Mike has his own “Creative Sweet” podcast which he’ll tell you about at the end of this episode. Mike will concentrate on ways to make your type fit perfectly in just about any given situation.
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Visit Original: VideoCopilot #38: 3D Camera Projection 2
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Visit Original: Adobe CS: Create Perfect Dashed Lines in Photoshop
Photoshop can do many things, most never think to use it to “draw” with. Well, may Bert Monroy thinks about that everyday. However, for the rest of us it’s not something that comes to mind usually. Special Guest Chita Hunter takes us through an easy method to get perfect dashed lines.
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Visit Original: DimeCasts.Net #30: Diving Deeper into Ninject - Contextual Binding
In this episode we will walk you through how to use the Ninject IoC (Inversion of Control) Container for contextual binding.
Contextual binding is the ability to register more than one binding (object or interface) for a given type. You can then at runtime determine which type you would like by asking for that type.
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Visit Original: Learn Excel Episode 813: Code Genie
Ever wonder how MrExcel spends his free time? He watches the macro recorder write code before his eyes. In Episode 813, learn how to arrange the VBA window and the Excel window to watch which lines of code appear in response to actions in Excel.
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The information age has made it easy to store large amounts of data.The proliferation of documents available on the Web, on corporate intranets, on news wires, and elsewhere is overwhelming. However, while the amount of data available to us is constantly increasing, our ability to absorb and process this information remains constant. Search engines only exacerbate the problem by making more and more documents available in a matter of a few key strokes. Link Analysis is a new and exciting research area that tries to solve the information overload problem by using techniques from data mining, machine learning, Information Extraction, Text Categorization, Visualization and Knowledge Management.
Author: Ronen Feldman, Bar Ilan University
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Visit Original: Random walk graph kernels and rational kernels
Random walk graph kernels (Gartner et al., 2003 [5]; Borgwardt et al., 2005 [1]) count matching random walks, and are defined using the tensor product graph. Loosely speaking, rational kernels (Cortes et al., 2004, 2003, 2002 [4, 3, 2]) use the weight assigned by a transducer to define a kernel. The kernel is shown to be positive semi-definite when the transducer can be written as a composition of two identical transducers. In our talk we will establish explicit connections between random walk graph kernels and rational kernels. More concretely, we show that composition of transducers is analogous to computing product graphs, and that rational kernels on weighted transducers may be viewed as generalizations of random walk kernels to weighted automata. In order to make these connections explicit we adapt slightly non-standard notation for weighted transducers, extensively using matrices and tensors wherever possible. We prove that under certain conditions rational kernels are positive semi-definite. Our proof only uses basic linear algebra and is simpler than the one presented in Cortes et al., 2004[4].
Author: S.V.N. Vishwanathan, National Ict Australia
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Visit Original: Fast Clustering based on Kernel Density Estimation
The Denclue algorithm employs a cluster model based on kernel density estimation. A cluster is defined by a local maximum of the estimated density function. Data points are assigned to clusters by hill climbing, i.e. points going to the same local maximum are put into the same cluster. A disadvantage of Denclue 1.0 is, that the used hill climbing may make unnecessary small steps in the beginning and never converges exactly to the maximum, it just comes close. We introduce a new hill climbing procedure for Gaussian kernels, which adjusts the step size automatically at no extra costs. We prove that the procedure converges exactly towards a local maximum by reducing it to a special case of the expectation maximization algorithm. We show experimentally that the new procedure needs much less iterations and can be accelerated by sampling based methods with sacrificing only a small amount of accuracy.
Author: Alexander Hinneburg, Martin-Luther University
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Visit Original: Optimization for Kernel Methods
Optimization methods play a crucial role in kernel methods such as Support Vector Machines and Kernel Logistic Regression. In a variety of scenarios, different optimization algorithms are better suited than others. The aims of the six lectures in this topic are: (1) to introduce a range of optimization problems that arise in the solution of classification problems by kernel methods; (2) to briefly review the relevant optimization algorithms; and (3) to point out in some detail as to which optimization methods are suited for these varied problems.
Author: Sathiya Keerthi, Yahoo! Research
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