• 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 49,197
Next 10 →

Problem Domains:

by David Tan, Chair Yahoo, Hadoop Sig
"... Video files are one of the most proliferated data: � 1,000s CCTVs added per Month � UK alone has 4 million of public CCTVs operated by the government � 1,000s Youtube video added In the internet and viewed per day � Millions of Searches per month � Growing trends of Terabytes-Petabytes of data gener ..."
Abstract - Cited by 1 (1 self) - Add to MetaCart
Video files are one of the most proliferated data: � 1,000s CCTVs added per Month � UK alone has 4 million of public CCTVs operated by the government � 1,000s Youtube video added In the internet and viewed per day � Millions of Searches per month � Growing trends of Terabytes-Petabytes of data generated per day!

Problem domain

by unknown authors
"... In an increasingly wired world, digital libraries are increasingly serving a worldwide audience. Even if initially designed for a local user population, a digital library can easily fi nd itself not only ..."
Abstract - Add to MetaCart
In an increasingly wired world, digital libraries are increasingly serving a worldwide audience. Even if initially designed for a local user population, a digital library can easily fi nd itself not only

Problem Domain

by Dorina Petriu, Gurudas Somadder
"... The paper describes a set of patterns that extend the pattern language proposed in [Meszaros96] for improving the capacity of reactive systems. The intent of these patterns is to identify some specific causes that limit the efficiency of a distributed layered client-server system with multi-threaded ..."
Abstract - Add to MetaCart
The paper describes a set of patterns that extend the pattern language proposed in [Meszaros96] for improving the capacity of reactive systems. The intent of these patterns is to identify some specific causes that limit the efficiency of a distributed layered client-server system with multi-threaded servers, and to find appropriate corrective measures. The type of systems considered here is a subclass of the larger category of reactive systems, and the new patterns are dealing with their specific performance characteristics. The effects of the patterns are illustrated with performance measurements conducted on a layered client-server system.

Planning and acting in partially observable stochastic domains

by Leslie Pack Kaelbling, Michael L. Littman, Anthony R. Cassandra - ARTIFICIAL INTELLIGENCE , 1998
"... In this paper, we bring techniques from operations research to bear on the problem of choosing optimal actions in partially observable stochastic domains. We begin by introducing the theory of Markov decision processes (mdps) and partially observable mdps (pomdps). We then outline a novel algorithm ..."
Abstract - Cited by 1095 (38 self) - Add to MetaCart
In this paper, we bring techniques from operations research to bear on the problem of choosing optimal actions in partially observable stochastic domains. We begin by introducing the theory of Markov decision processes (mdps) and partially observable mdps (pomdps). We then outline a novel algorithm

The Vocabulary Problem in Human-System Communication

by G. W. Furnas, T. K. Landauer, L. M. Gomez, S. T. Dumais - COMMUNICATIONS OF THE ACM , 1987
"... In almost all computer applications, users must enter correct words for the desired objects or actions. For success without extensive training, or in first-tries for new targets, the system must recognize terms that will be chosen spontaneously. We studied spontaneous word choice for objects in five ..."
Abstract - Cited by 562 (8 self) - Add to MetaCart
in five application-related domains, and found the variability to be surprisingly large. In every case two people favored the same term with probability <0.20. Simulations show how this fundamental property of language limits the success of various design methodologies for vocabulary-driven interaction

PDDL2.1: An Extension to PDDL for Expressing Temporal Planning Domains

by Maria Fox, Derek Long , 2003
"... In recent years research in the planning community has moved increasingly towards application of planners to realistic problems involving both time and many types of resources. For example, interest in planning demonstrated by the space research community has inspired work in observation scheduling, ..."
Abstract - Cited by 609 (41 self) - Add to MetaCart
In recent years research in the planning community has moved increasingly towards application of planners to realistic problems involving both time and many types of resources. For example, interest in planning demonstrated by the space research community has inspired work in observation scheduling

Cognitive load during problem solving: effects on learning

by John Sweller - COGNITIVE SCIENCE , 1988
"... Considerable evidence indicates that domain specific knowledge in the form of schemes is the primary factor distinguishing experts from novices in problem-solving skill. Evidence that conventional problem-solving activity is not effective in schema acquisition is also accumulating. It is suggested t ..."
Abstract - Cited by 639 (13 self) - Add to MetaCart
Considerable evidence indicates that domain specific knowledge in the form of schemes is the primary factor distinguishing experts from novices in problem-solving skill. Evidence that conventional problem-solving activity is not effective in schema acquisition is also accumulating. It is suggested

The University of Florida sparse matrix collection

by Timothy A. Davis - NA DIGEST , 1997
"... The University of Florida Sparse Matrix Collection is a large, widely available, and actively growing set of sparse matrices that arise in real applications. Its matrices cover a wide spectrum of problem domains, both those arising from problems with underlying 2D or 3D geometry (structural enginee ..."
Abstract - Cited by 536 (17 self) - Add to MetaCart
The University of Florida Sparse Matrix Collection is a large, widely available, and actively growing set of sparse matrices that arise in real applications. Its matrices cover a wide spectrum of problem domains, both those arising from problems with underlying 2D or 3D geometry (structural

Constrained K-means Clustering with Background Knowledge

by Kiri Wagstaff, Claire Cardie, Seth Rogers, Stefan Schroedl - In ICML , 2001
"... Clustering is traditionally viewed as an unsupervised method for data analysis. However, in some cases information about the problem domain is available in addition to the data instances themselves. In this paper, we demonstrate how the popular k-means clustering algorithm can be pro tably modi- ed ..."
Abstract - Cited by 488 (9 self) - Add to MetaCart
Clustering is traditionally viewed as an unsupervised method for data analysis. However, in some cases information about the problem domain is available in addition to the data instances themselves. In this paper, we demonstrate how the popular k-means clustering algorithm can be pro tably modi- ed

Markov Random Field Models in Computer Vision

by S. Z. Li , 1994
"... . A variety of computer vision problems can be optimally posed as Bayesian labeling in which the solution of a problem is defined as the maximum a posteriori (MAP) probability estimate of the true labeling. The posterior probability is usually derived from a prior model and a likelihood model. The l ..."
Abstract - Cited by 516 (18 self) - Add to MetaCart
. The latter relates to how data is observed and is problem domain dependent. The former depends on how various prior constraints are expressed. Markov Random Field Models (MRF) theory is a tool to encode contextual constraints into the prior probability. This paper presents a unified approach for MRF modeling
Next 10 →
Results 1 - 10 of 49,197
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