• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • DMCA
  • Donate

CiteSeerX logo

Advanced Search Include Citations

Tools

Sorted by:
Try your query at:
Semantic Scholar Scholar Academic
Google Bing DBLP
Results 1 - 10 of 101,144
Next 10 →

Data Streams: Algorithms and Applications

by S. Muthukrishnan , 2005
"... In the data stream scenario, input arrives very rapidly and there is limited memory to store the input. Algorithms have to work with one or few passes over the data, space less than linear in the input size or time significantly less than the input size. In the past few years, a new theory has emerg ..."
Abstract - Cited by 533 (22 self) - Add to MetaCart
In the data stream scenario, input arrives very rapidly and there is limited memory to store the input. Algorithms have to work with one or few passes over the data, space less than linear in the input size or time significantly less than the input size. In the past few years, a new theory has

SplitStream: High-Bandwidth Multicast in Cooperative Environments

by Miguel Castro, Peter Druschel, Anne-Marie Kermarrec, Animesh Nandi, Antony Rowstron, Atul Singh - SOSP '03 , 2003
"... In tree-based multicast systems, a relatively small number of interior nodes carry the load of forwarding multicast messages. This works well when the interior nodes are highly available, d d cated infrastructure routers but it poses a problem for application-level multicast in peer-to-peer systems. ..."
Abstract - Cited by 578 (17 self) - Add to MetaCart
In tree-based multicast systems, a relatively small number of interior nodes carry the load of forwarding multicast messages. This works well when the interior nodes are highly available, d d cated infrastructure routers but it poses a problem for application-level multicast in peer-to-peer systems

Sorting networks and their applications

by K. E. Batcher , 1968
"... To achieve high throughput rates today's computers perform several operations simultaneously. Not only are I/O operations performed concurrently with computing, but also, in multiprocessors, several computing ..."
Abstract - Cited by 662 (0 self) - Add to MetaCart
To achieve high throughput rates today's computers perform several operations simultaneously. Not only are I/O operations performed concurrently with computing, but also, in multiprocessors, several computing

Scalable Application Layer Multicast

by Suman Banerjee, Bobby Bhattacharjee, Christopher Kommareddy , 2002
"... We describe a new scalable application-layer multicast protocol, specifically designed for low-bandwidth, data streaming applications with large receiver sets. Our scheme is based upon a hierarchical clustering of the application-layer multicast peers and can support a number of different data deliv ..."
Abstract - Cited by 731 (21 self) - Add to MetaCart
We describe a new scalable application-layer multicast protocol, specifically designed for low-bandwidth, data streaming applications with large receiver sets. Our scheme is based upon a hierarchical clustering of the application-layer multicast peers and can support a number of different data

Equation-based congestion control for unicast applications

by Sally Floyd , Mark Handley , Jitendra Padhye , Jörg Widmer - SIGCOMM '00 , 2000
"... This paper proposes a mechanism for equation-based congestion control for unicast traffic. Most best-effort traffic in the current Internet is well-served by the dominant transport protocol, TCP. However, traffic such as best-effort unicast streaming multimedia could find use for a TCP-friendly cong ..."
Abstract - Cited by 830 (29 self) - Add to MetaCart
This paper proposes a mechanism for equation-based congestion control for unicast traffic. Most best-effort traffic in the current Internet is well-served by the dominant transport protocol, TCP. However, traffic such as best-effort unicast streaming multimedia could find use for a TCP

An improved data stream summary: The Count-Min sketch and its applications

by Graham Cormode, S. Muthukrishnan - J. Algorithms , 2004
"... Abstract. We introduce a new sublinear space data structure—the Count-Min Sketch — for summarizing data streams. Our sketch allows fundamental queries in data stream summarization such as point, range, and inner product queries to be approximately answered very quickly; in addition, it can be applie ..."
Abstract - Cited by 413 (43 self) - Add to MetaCart
be applied to solve several important problems in data streams such as finding quantiles, frequent items, etc. The time and space bounds we show for using the CM sketch to solve these problems significantly improve those previously known — typically from 1/ε 2 to 1/ε in factor. 1

The geometry of graphs and some of its algorithmic applications

by Nathan Linial, Eran London, Yuri Rabinovich - COMBINATORICA , 1995
"... In this paper we explore some implications of viewing graphs as geometric objects. This approach offers a new perspective on a number of graph-theoretic and algorithmic problems. There are several ways to model graphs geometrically and our main concern here is with geometric representations that res ..."
Abstract - Cited by 524 (19 self) - Add to MetaCart
In this paper we explore some implications of viewing graphs as geometric objects. This approach offers a new perspective on a number of graph-theoretic and algorithmic problems. There are several ways to model graphs geometrically and our main concern here is with geometric representations

A tutorial on hidden Markov models and selected applications in speech recognition

by Lawrence R. Rabiner - PROCEEDINGS OF THE IEEE , 1989
"... Although initially introduced and studied in the late 1960s and early 1970s, statistical methods of Markov source or hidden Markov modeling have become increasingly popular in the last several years. There are two strong reasons why this has occurred. First the models are very rich in mathematical s ..."
Abstract - Cited by 5892 (1 self) - Add to MetaCart
structure and hence can form the theoretical basis for use in a wide range of applications. Sec-ond the models, when applied properly, work very well in practice for several important applications. In this paper we attempt to care-fully and methodically review the theoretical aspects of this type

Face description with local binary patterns: Application to face recognition

by Abdenour Hadid, Senior Member - IEEE Trans. Pattern Analysis and Machine Intelligence , 2006
"... Abstract—This paper presents a novel and efficient facial image representation based on local binary pattern (LBP) texture features. The face image is divided into several regions from which the LBP feature distributions are extracted and concatenated into an enhanced feature vector to be used as a ..."
Abstract - Cited by 526 (27 self) - Add to MetaCart
face descriptor. The performance of the proposed method is assessed in the face recognition problem under different challenges. Other applications and several extensions are also discussed. Index Terms—Facial image representation, local binary pattern, component-based face recognition, texture features

TOSSIM: Accurate and Scalable Simulation of Entire TinyOS Applications

by Philip Levis, Nelson Lee, Matt Welsh, David Culler , 2003
"... Accurate and scalable simulation has historically been a key enabling factor for systems research. We present TOSSIM, a simulator for TinyOS wireless sensor networks. By exploiting the sensor network domain and TinyOS’s design, TOSSIM can capture network behavior at a high fidelity while scaling to ..."
Abstract - Cited by 784 (19 self) - Add to MetaCart
to thousands of nodes. By using a probabilistic bit error model for the network, TOSSIM remains simple and efficient, but expressive enough to capture a wide range of network interactions. Using TOSSIM, we have discovered several bugs in TinyOS, ranging from network bitlevel MAC interactions to queue overflows
Next 10 →
Results 1 - 10 of 101,144
Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2019 The Pennsylvania State University