Results 1 - 10 of 30,739

Learning Bayesian networks: The combination of knowledge and statistical data

by David Heckerman, David M. Chickering - Machine Learning , 1995
"... We describe scoring metrics for learning Bayesian networks from a combination of user knowledge and statistical data. We identify two important properties of metrics, which we call event equivalence and parameter modularity. These properties have been mostly ignored, but when combined, greatly simpl ..."
Abstract - Cited by 1158 (35 self) - Add to MetaCart
We describe scoring metrics for learning Bayesian networks from a combination of user knowledge and statistical data. We identify two important properties of metrics, which we call event equivalence and parameter modularity. These properties have been mostly ignored, but when combined, greatly

Route Packets, Not Wires: On-Chip Interconnection Networks

by William J. Dally, Brian Towles , 2001
"... Using on-chip interconnection networks in place of ad-hoc global wiring structures the top level wires on a chip and facilitates modular design. With this approach, system modules (processors, memories, peripherals, etc...) communicate by sending packets to one another over the network. The structur ..."
Abstract - Cited by 885 (10 self) - Add to MetaCart
. The structured network wiring gives well-controlled electrical parameters that eliminate timing iterations and enable the use of high-performance circuits to reduce latency and increase bandwidth. The area overhead required to implement an on-chip network is modest, we estimate 6.6%. This paper introduces

Imagenet classification with deep convolutional neural networks.

by Alex Krizhevsky , Ilya Sutskever , Geoffrey E Hinton - In Advances in the Neural Information Processing System, , 2012
"... Abstract We trained a large, deep convolutional neural network to classify the 1.2 million high-resolution images in the ImageNet LSVRC-2010 contest into the 1000 different classes. On the test data, we achieved top-1 and top-5 error rates of 37.5% and 17.0% which is considerably better than the pr ..."
Abstract - Cited by 1010 (11 self) - Add to MetaCart
the previous state-of-the-art. The neural network, which has 60 million parameters and 650,000 neurons, consists of five convolutional layers, some of which are followed by max-pooling layers, and three fully-connected layers with a final 1000-way softmax. To make training faster, we used non

A Scheme for Real-Time Channel Establishment in Wide-Area Networks

by Domenico Ferrari, Dinesh C. Verma - IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS , 1990
"... Multimedia communication involving digital audio and/or digital video has rather strict delay requirements. A real-time channel is defined in this paper as a simplex connection between a source and a destination characterized by parameters representing the performance requirements of the client. A r ..."
Abstract - Cited by 702 (31 self) - Add to MetaCart
Multimedia communication involving digital audio and/or digital video has rather strict delay requirements. A real-time channel is defined in this paper as a simplex connection between a source and a destination characterized by parameters representing the performance requirements of the client. A

A Review of Current Routing Protocols for Ad-Hoc Mobile Wireless Networks

by Elizabeth M. Royer, Chai-Keong Toh
"... An ad-hoc mobile network is a collection of mobile nodes that are dynamically and arbitrarily located in such a manner that the interconnections between nodes are capable of changing on a continual basis. In order to facilitate communication within the network, a routing protocol is used to discove ..."
Abstract - Cited by 1311 (3 self) - Add to MetaCart
. This paper examines routing protocols for ad-hoc networks and evaluates these protocols based on a given set of parameters. The paper provides an overview of eight different protocols by presenting their characteristics and functionality, and then provides a comparison and discussion of their respective

Versatile Low Power Media Access for Wireless Sensor Networks

by Joseph Polastre, Jason Hill, David Culler , 2004
"... We propose B-MAC, a carrier sense media access protocol for wireless sensor networks that provides a flexible interface to obtain ultra low power operation, effective collision avoidance, and high channel utilization. To achieve low power operation, B-MAC employs an adaptive preamble sampling scheme ..."
Abstract - Cited by 1099 (19 self) - Add to MetaCart
applications. We use the model to show the effect of changing B-MAC’s parameters and predict the behavior of sensor network applications. By comparing B-MAC to conventional 802.11inspired protocols, specifically S-MAC, we develop an experimental characterization of B-MAC over a wide range of network conditions

Tinysec: A link layer security architecture for wireless sensor networks

by Chris Karlof, Naveen Sastry, David Wagner - in Proc of the 2nd Int’l Conf on Embedded Networked Sensor Systems
"... We introduce TinySec, the first fully-implemented link layer security architecture for wireless sensor networks. In our design, we leverage recent lessons learned from design vulnerabilities in security protocols for other wireless networks such as 802.11b and GSM. Conventional security protocols te ..."
Abstract - Cited by 521 (0 self) - Add to MetaCart
the tradeoffs among different cryptographic primitives and use the inherent sensor network limitations to our advantage when choosing parameters to find a sweet spot for security, packet overhead, and resource requirements. TinySec is portable to a variety of hardware and radio platforms. Our experimental

HEED: A Hybrid, Energy-Efficient, Distributed Clustering Approach for Ad Hoc Sensor Networks

by Ossama Younis, Sonia Fahmy - IEEE TRANS. MOBILE COMPUTING , 2004
"... Topology control in a sensor network balances load on sensor nodes and increases network scalability and lifetime. Clustering sensor nodes is an effective topology control approach. In this paper, we propose a novel distributed clustering approach for long-lived ad hoc sensor networks. Our proposed ..."
Abstract - Cited by 590 (1 self) - Add to MetaCart
according to a hybrid of the node residual energy and a secondary parameter, such as node proximity to its neighbors or node degree. HEED terminates in Oð1Þ iterations, incurs low message overhead, and achieves fairly uniform cluster head distribution across the network. We prove that, with appropriate

Dummynet: A Simple Approach to the Evaluation of Network Protocols

by Luigi Rizzo - ACM Computer Communication Review , 1997
"... Network protocols are usually tested in operational networks or in simulated environments. With the former approach it is not easy to set and control the various operational parameters such as bandwidth, delays, queue sizes. Simulators are easier to control, but they are often only an approximate mo ..."
Abstract - Cited by 484 (6 self) - Add to MetaCart
Network protocols are usually tested in operational networks or in simulated environments. With the former approach it is not easy to set and control the various operational parameters such as bandwidth, delays, queue sizes. Simulators are easier to control, but they are often only an approximate

Learning low-level vision

by William T. Freeman, Egon C. Pasztor - International Journal of Computer Vision , 2000
"... We show a learning-based method for low-level vision problems. We set-up a Markov network of patches of the image and the underlying scene. A factorization approximation allows us to easily learn the parameters of the Markov network from synthetic examples of image/scene pairs, and to e ciently prop ..."
Abstract - Cited by 579 (30 self) - Add to MetaCart
We show a learning-based method for low-level vision problems. We set-up a Markov network of patches of the image and the underlying scene. A factorization approximation allows us to easily learn the parameters of the Markov network from synthetic examples of image/scene pairs, and to e ciently
Results 1 - 10 of 30,739