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This paper describes using wearable computing devices to perform "sousveillance" (inverse surveillance) as a counter to organizational surveillance. A variety of wearable computing devices generated different kinds of responses, and allowed for the collection of data in different situations. Visible sousveillance often evoked counter-performances by(More)
This set of notes presents the Support Vector Machine (SVM) learning algorithm. SVMs are among the best (and many believe are indeed the best) " off-the-shelf " supervised learning algorithm. To tell the SVM story, we'll need to first talk about margins and the idea of separating data with a large " gap. " Next, we'll talk about the optimal margin(More)
We describe a soft-x-ray laser interferometry technique that allows two-dimensional diagnosis of plasma electron density with picosecond time resolution. It consists of the combination of a robust high-throughput amplitude-division interferometer and a 14.7-nm transient-inversion soft-x-ray laser that produces approximately 5-ps pulses. Because of its(More)
Spectrally resolved scattering of ultrafast K-alpha x-rays has provided experimental validation of the modeling of the compression and heating of shocked matter. The elastic scattering component has characterized the evolution and coalescence of two shocks launched by a nanosecond laser pulse into lithium hydride with an unprecedented temporal resolution of(More)
So far, we've mainly been talking about learning algorithms that model p(y|x; θ), the conditional distribution of y given x. For instance, logistic regression modeled p(y|x; θ) as h θ (x) = g(θ T x) where g is the sigmoid function. In these notes, we'll talk about a different type of learning algorithm. Consider a classification problem in which we want to(More)