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Detecting intrusions using system calls: alternative data models
Intrusion detection systems rely on a wide variety of observable data to distinguish between legitimate and illegitimate activities. We study one such observable-sequences of system calls into theExpand
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Results of the Abbadingo One DFA Learning Competition and a New Evidence-Driven State Merging Algorithm
This paper first describes the structure and results of the Abbadingo One DFA Learning Competition. The competition was designed to encourage work on algorithms that scale well—both to larger DFAsExpand
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Fast Exact Multiplication by the Hessian
Just storing the Hessian H (the matrix of second derivatives 2E/wiwj of the error E with respect to each pair of weights) of a large neural network is difficult. Since a common use of a large matrixExpand
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Automatic differentiation in machine learning: a survey
Derivatives, mostly in the form of gradients and Hessians, are ubiquitous in machine learning. Automatic differentiation (AD), also called algorithmic differentiation or simply “auto-diff”, is aExpand
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Learning State Space Trajectories in Recurrent Neural Networks
Many neural network learning procedures compute gradients of the errors on the output layer of units after they have settled to their final values. We describe a procedure for finding E/wij, where EExpand
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Gradient calculations for dynamic recurrent neural networks: a survey
Surveys learning algorithms for recurrent neural networks with hidden units and puts the various techniques into a common framework. The authors discuss fixed point learning algorithms, namelyExpand
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Blind Source Separation by Sparse Decomposition in a Signal Dictionary
The blind source separation problem is to extract the underlying source signals from a set of linear mixtures, where the mixing matrix is unknown. This situation is common in acoustics, radio,Expand
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A Context-Sensitive Generalization of ICA
Source separation arises in a surprising number of signal processing applications, from speech recognition to EEG analysis. In the square linear blind source separation problem without time delays,Expand
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Survey of sparse and non‐sparse methods in source separation
Source separation arises in a variety of signal processing applications, ranging from speech processing to medical image analysis. The separation of a superposition of multiple signals isExpand
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The VESPA: A method for the rapid estimation of a visual evoked potential
Faster and less obtrusive means for measuring a Visual Evoked Potential would be valuable in clinical testing and basic neuroscience research. This study presents a method for accomplishing this byExpand
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