Results 1 - 10 of 1,379

A tutorial on support vector machines for pattern recognition

by Christopher J. C. Burges - Data Mining and Knowledge Discovery , 1998
"... The tutorial starts with an overview of the concepts of VC dimension and structural risk minimization. We then describe linear Support Vector Machines (SVMs) for separable and non-separable data, working through a non-trivial example in detail. We describe a mechanical analogy, and discuss when SV ..."
Abstract - Cited by 3393 (12 self) - Add to MetaCart
large (even infinite) VC dimension by computing the VC dimension for homogeneous polynomial and Gaussian radial basis function kernels. While very high VC dimension would normally bode ill for generalization performance, and while at present there exists no theory which shows that good generalization

A framework for information systems architecture.

by J A Zachman - IBM Syst. J., , 1987
"... With increasing size and complexity of the implementations of information systems, it is necessary to use some logical construct (or architecture) for defining and controlling the interfaces and the integration of all of the components of the system. This paper defines information systems architect ..."
Abstract - Cited by 546 (0 self) - Add to MetaCart
architecture by creating a d e scriptive framework from disciplines quite independent of information systems, then by analogy specifies information systems architecture based upon the neutral, objective framework. Also, some preliminary conclusions about the implications of the resultant descriptive framework

Real-Time Computing Without Stable States: A New Framework for Neural Computation Based on Perturbations

by Wolfgang Maass, Thomas Natschläger, Henry Markram
"... A key challenge for neural modeling is to explain how a continuous stream of multi-modal input from a rapidly changing environment can be processed by stereotypical recurrent circuits of integrate-and-fire neurons in real-time. We propose a new computational model for real-time computing on time-var ..."
Abstract - Cited by 469 (38 self) - Add to MetaCart
be implemented on generic evolved or found recurrent circuitry. It is shown that the inherent transient dynamics of the high-dimensional dynamical system formed by a sufficiently large and heterogeneous neural circuit may serve as universal analog fading memory. Readout neurons can learn to extract in real

A Memristor-Crossbar/CMOS Integrated Network for Pattern Classification and Recognition

by L. Zhang, Z. J. Chang
"... Abstract-A novel circuit model based on a trainable memristor-crossbar network integrated with a CMOS circuit for pattern classification and recognition is proposed and analyzed in this paper. The configurable memristors along each column wires of the crossbar are trained by a standard pattern input ..."
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/CMOS circuit enables it to classify and recognize patterns with high dimensionality and complexity at a much faster speed than the software-based computers. Keywords-pattern classification; recognition; memristor; crossbar; CMOS analog integrated circuits; probability I.

ICE: Inline calibration for memristor crossbar-based computing engine

by Boxun Li, Yu Wang, Yiran Chen, Hai (helen Li, Huazhong Yang - in Proc. Conf. Design Autom. Test Europe , 2014
"... Abstract—The emerging neuromorphic computation provides a revo-lutionary solution to the alternative computing architecture and effec-tively extends Moore’s Law. The discovery of the memristor presents a promising hardware realization of neuromorphic systems with incredible power efficiency, allowin ..."
Abstract - Cited by 2 (2 self) - Add to MetaCart
, allowing efficiently executing the analog matrix-vector multiplication on the memristor crossbar architecture. However, during computations, the memristor will slowly drift from its initial pro-grammed state, leading to a gradual decline of the computation precision of memristor crossbar-based computing

A Taxonomy of Scheduling in General-Purpose Distributed Computing Systems

by Thomas L. Casavant, Jon G. Kuhl - IEEE TRANSACTIONS ON SOFTWARE ENGINEERING , 1988
"... One measure of usefulness of a general-purpose distributed computing system is the system’s ability to provide a level of performance commensurate to the degree of multiplicity of resources present in the system. Many different approaches and metrics of performance have been proposed in an attempt t ..."
Abstract - Cited by 311 (0 self) - Add to MetaCart
One measure of usefulness of a general-purpose distributed computing system is the system’s ability to provide a level of performance commensurate to the degree of multiplicity of resources present in the system. Many different approaches and metrics of performance have been proposed in an attempt

(a) Metal-oxide memristor

by Beiye Liu , Hai Li , Yiran Chen , Xin Li , Tingwen Huang , Qing Wu , Mark Barnell
"... ABSTRACT Neuromorphic computing system (NCS) is a promising architecture to combat the well-known memory bottleneck in Von Neumann architecture. The recent breakthrough on memristor devices made an important step toward realizing a low-power, smallfootprint NCS on-a-chip. However, the currently low ..."
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dimension of the memristor crossbars in NCS while maintaining high computing accuracy. An IRdrop compensation technique is also proposed to overcome the adverse impacts of the wire resistance and the sneak-path problem in large memristor crossbar designs. Our simulation results show that the proposed

Towards a modern theory of adaptive networks: expectation and prediction

by Richard S. Sutton, Andrew G. Barto - Psychol. Rev , 1981
"... Many adaptive neural network theories are based on neuronlike adaptive elements that can behave as single unit analogs of associative conditioning. In this article we develop a similar adaptive element, but one which is more closely in accord with the facts of animal learning theory than elements co ..."
Abstract - Cited by 282 (18 self) - Add to MetaCart
Many adaptive neural network theories are based on neuronlike adaptive elements that can behave as single unit analogs of associative conditioning. In this article we develop a similar adaptive element, but one which is more closely in accord with the facts of animal learning theory than elements

Matrix Completion with Noise

by Emmanuel J. Candès, Yaniv Plan
"... On the heels of compressed sensing, a remarkable new field has very recently emerged. This field addresses a broad range of problems of significant practical interest, namely, the recovery of a data matrix from what appears to be incomplete, and perhaps even corrupted, information. In its simplest ..."
Abstract - Cited by 255 (13 self) - Add to MetaCart
numerical results which complement our quantitative analysis and show that, in practice, nuclear norm minimization accurately fills in the many missing entries of large low-rank matrices from just a few noisy samples. Some analogies between matrix completion and compressed sensing are discussed throughout.

Practical Gradient-Descent for Memristive Crossbars

by Manu V Nair, Piotr Dudek
"... Abstract — This paper discusses implementations of gradient-descent based learning algorithms on memristive crossbar arrays. The Unregulated Step Descent (USD) is described as a practical algorithm for feed-forward on-line training of large crossbar arrays. It allows fast feed-forward fully parallel ..."
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has been studied via simulations. There is a significant interest in using memristive devices for computation, in particular in the context of neuromorpic systems [1] and artificial neural networks [2-7]. Memristors are typically fabricated in the form of highly-dense crossbar arrays,
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