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A statistically-switched adaptive vector median filter

by Rastislav Lukac, Konstantinos N. Plataniotis, ANASTASIOS N. VENETSANOPOULOS, et al. - INTELL. ROBOT. SYST , 2005
"... This paper presents a new cost-effective, adaptive multichannel filter taking advantage of switching schemes, robust order-statistic theory and approximation of the multivariate dispersion. Introducing the statistical control of the switching between the vector median and the identity operation, the ..."
Abstract - Cited by 33 (6 self) - Add to MetaCart
This paper presents a new cost-effective, adaptive multichannel filter taking advantage of switching schemes, robust order-statistic theory and approximation of the multivariate dispersion. Introducing the statistical control of the switching between the vector median and the identity operation

Least Median of Squares Regression

by Peter J. Rousseeuw - JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION , 1984
"... ..."
Abstract - Cited by 622 (22 self) - Add to MetaCart
Abstract not found

The Design and Use of Steerable Filters

by William T. Freeman, Edward H. Adelson - IEEE Transactions on Pattern Analysis and Machine Intelligence , 1991
"... Oriented filters are useful in many early vision and image processing tasks. One often needs to apply the same filter, rotated to different angles under adaptive control, or wishes to calculate the filter response at various orientations. We present an efficient architecture to synthesize filters of ..."
Abstract - Cited by 1079 (11 self) - Add to MetaCart
Oriented filters are useful in many early vision and image processing tasks. One often needs to apply the same filter, rotated to different angles under adaptive control, or wishes to calculate the filter response at various orientations. We present an efficient architecture to synthesize filters

Sparse Bayesian Learning and the Relevance Vector Machine

by Michael E. Tipping, Alex Smola , 2001
"... This paper introduces a general Bayesian framework for obtaining sparse solutions to regression and classication tasks utilising models linear in the parameters. Although this framework is fully general, we illustrate our approach with a particular specialisation that we denote the `relevance vec ..."
Abstract - Cited by 958 (5 self) - Add to MetaCart
vector machine' (RVM), a model of identical functional form to the popular and state-of-the-art `support vector machine' (SVM). We demonstrate that by exploiting a probabilistic Bayesian learning framework, we can derive accurate prediction models which typically utilise dramatically fewer

NewsWeeder: Learning to Filter Netnews

by Ken Lang - in Proceedings of the 12th International Machine Learning Conference (ML95 , 1995
"... A significant problem in many information filtering systems is the dependence on the user for the creation and maintenance of a user profile, which describes the user's interests. NewsWeeder is a netnews-filtering system that addresses this problem by letting the user rate his or her interest l ..."
Abstract - Cited by 555 (0 self) - Add to MetaCart
A significant problem in many information filtering systems is the dependence on the user for the creation and maintenance of a user profile, which describes the user's interests. NewsWeeder is a netnews-filtering system that addresses this problem by letting the user rate his or her interest

Empirical Analysis of Predictive Algorithm for Collaborative Filtering

by John S. Breese, David Heckerman, Carl Kadie - Proceedings of the 14 th Conference on Uncertainty in Artificial Intelligence , 1998
"... 1 ..."
Abstract - Cited by 1481 (4 self) - Add to MetaCart
Abstract not found

Adaptive clustering for mobile wireless networks

by Chunhung Richard Lin, Mario Gerla - IEEE Journal on Selected Areas in Communications , 1997
"... This paper describes a self-organizing, multihop, mobile radio network, which relies on a code division access scheme for multimedia support. In the proposed network architecture, nodes are organized into nonoverlapping clusters. The clusters are independently controlled and are dynamically reconfig ..."
Abstract - Cited by 556 (11 self) - Add to MetaCart
This paper describes a self-organizing, multihop, mobile radio network, which relies on a code division access scheme for multimedia support. In the proposed network architecture, nodes are organized into nonoverlapping clusters. The clusters are independently controlled and are dynamically reconfigured as nodes move. This network architecture has three main advantages. First, it provides spatial reuse of the bandwidth due to node clustering. Secondly, bandwidth can be shared or reserved in a controlled fashion in each cluster. Finally, the cluster algorithm is robust in the face of topological changes caused by node motion, node failure and node insertion/removal. Simulation shows that this architecture provides an efficient, stable infrastructure for the integration of different types of traffic in a dynamic radio network. 1.

The BSD Packet Filter: A New Architecture for User-level Packet Capture

by Steven Mccanne, Van Jacobson , 1992
"... Many versions of Unix provide facilities for user-level packet capture, making possible the use of general purpose workstations for network monitoring. Because network monitors run as user-level processes, packets must be copied across the kernel/user-space protection boundary. This copying can be m ..."
Abstract - Cited by 566 (2 self) - Add to MetaCart
be minimized by deploying a kernel agent called a packet filter, which discards unwanted packets as early as possible. The original Unix packet filter was designed around a stack-based filter evaluator that performs sub-optimally on current RISC CPUs. The BSD Packet Filter (BPF) uses a new, registerbased

Medium Access Control with Coordinated Adaptive Sleeping for Wireless Sensor Networks

by Wei Ye, John Heidemann, Deborah Estrin - IEEE/ACM Transactions on Networking , 2004
"... This paper proposes S-MAC, a medium access control (MAC) protocol designed for wireless sensor networks. Wireless sensor networks use battery-operated computing and sensing devices. A network of these devices will collaborate for a common application such as environmental monitoring. We expect senso ..."
Abstract - Cited by 684 (15 self) - Add to MetaCart
clusters based on common sleep schedules to reduce control overhead and enable traffic-adaptive wake-up. S-MAC uses in-channel signaling to avoid overhearing unnecessary traffic. Finally, S-MAC applies message passing to reduce contention latency for applications that require in-network data processing

Transductive Inference for Text Classification using Support Vector Machines

by Thorsten Joachims , 1999
"... This paper introduces Transductive Support Vector Machines (TSVMs) for text classification. While regular Support Vector Machines (SVMs) try to induce a general decision function for a learning task, Transductive Support Vector Machines take into account a particular test set and try to minimiz ..."
Abstract - Cited by 887 (4 self) - Add to MetaCart
This paper introduces Transductive Support Vector Machines (TSVMs) for text classification. While regular Support Vector Machines (SVMs) try to induce a general decision function for a learning task, Transductive Support Vector Machines take into account a particular test set and try
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