Results 1 - 10 of 7,012

Mega: molecular evolutionary genetic analysis software for microcomputers

by Sudhir Kumar, Koichiro Tamura, Masatoshi Nei - CABIOS , 1994
"... A computer program package called MEGA has been developed for estimating evolutionary distances, reconstructing phylogenetic trees and computing basic statistical quantities from molecular data. It is written in C+ + and is intended to be used on IBM and IBM-compatible personal computers. In this pr ..."
Abstract - Cited by 505 (10 self) - Add to MetaCart
in nucleotide and amino acid sequences. Advanced on-screen sequence data and phylogenetic-tree editors facilitate publication-quality outputs with a wide range of printers. Integrated and interactive designs, on-line context-sensitive helps, and a text-file editor make MEGA easy to use.

Data Mining: Concepts and Techniques

by Jiawei Han, Micheline Kamber , 2000
"... Our capabilities of both generating and collecting data have been increasing rapidly in the last several decades. Contributing factors include the widespread use of bar codes for most commercial products, the computerization of many business, scientific and government transactions and managements, a ..."
Abstract - Cited by 3142 (23 self) - Add to MetaCart
, and advances in data collection tools ranging from scanned texture and image platforms, to on-line instrumentation in manufacturing and shopping, and to satellite remote sensing systems. In addition, popular use of the World Wide Web as a global information system has flooded us with a tremendous amount

On-Line Q-Learning Using Connectionist Systems

by G. A. Rummery, M. Niranjan , 1994
"... Reinforcement learning algorithms are a powerful machine learning technique. However, much of the work on these algorithms has been developed with regard to discrete finite-state Markovian problems, which is too restrictive for many real-world environments. Therefore, it is desirable to extend these ..."
Abstract - Cited by 381 (1 self) - Add to MetaCart
of different algorithms based around Q-Learning (Watkins 1989) combined with the Temporal Difference algorithm (Sutton 1988), including a new algorithm (Modified Connectionist Q-Learning), and Q() (Peng and Williams 1994). In addition, we present algorithms for applying these updates on-line during trials

Randomized Gossip Algorithms

by Stephen Boyd, Arpita Ghosh, Balaji Prabhakar, Devavrat Shah - IEEE TRANSACTIONS ON INFORMATION THEORY , 2006
"... Motivated by applications to sensor, peer-to-peer, and ad hoc networks, we study distributed algorithms, also known as gossip algorithms, for exchanging information and for computing in an arbitrarily connected network of nodes. The topology of such networks changes continuously as new nodes join a ..."
Abstract - Cited by 532 (5 self) - Add to MetaCart
and old nodes leave the network. Algorithms for such networks need to be robust against changes in topology. Additionally, nodes in sensor networks operate under limited computational, communication, and energy resources. These constraints have motivated the design of “gossip ” algorithms: schemes which

On-line selection of discriminative tracking features

by Robert T. Collins, Yanxi Liu, Marius Leordeanu , 2003
"... This paper presents an on-line feature selection mechanism for evaluating multiple features while tracking and adjusting the set of features used to improve tracking performance. Our hypothesis is that the features that best discriminate between object and background are also best for track-ing the ..."
Abstract - Cited by 356 (5 self) - Add to MetaCart
This paper presents an on-line feature selection mechanism for evaluating multiple features while tracking and adjusting the set of features used to improve tracking performance. Our hypothesis is that the features that best discriminate between object and background are also best for track-ing

Bullet: High Bandwidth Data Dissemination Using an Overlay Mesh

by Dejan Kostic, Adolfo Rodriguez, Jeannie Albrecht, Amin Vahdat , 2003
"... In recent years, overlay networks have become an effective alternative to IP multicast for efficient point to multipoint communication across the Internet. Typically, nodes self-organize with the goal of forming an efficient overlay tree, one that meets performance targets without placing undue burd ..."
Abstract - Cited by 424 (22 self) - Add to MetaCart
burden on the underlying network. In this paper, we target high-bandwidth data distribution from a single source to a large number of receivers. Applications include large-file transfers and real-time multimedia streaming. For these applications, we argue that an overlay mesh, rather than a tree, can

An overview of data warehousing and OLAP technology

by Surajit Chaudhuri, Umeshwar Dayal - SIGMOD Record , 1997
"... Data warehousing and on-line analytical processing (OLAP) are essential elements of decision support, which has increasingly become a focus of the database industry. Many commercial products and services are now available, and all of the principal database management system vendors now have offering ..."
Abstract - Cited by 386 (3 self) - Add to MetaCart
Data warehousing and on-line analytical processing (OLAP) are essential elements of decision support, which has increasingly become a focus of the database industry. Many commercial products and services are now available, and all of the principal database management system vendors now have

An optimal on-line algorithm for metrical task systems

by Allan Borodin, Nathan Linial, Michael E. Saks - JOURNAL OF THE ACM , 1992
"... In practice, almost all dynamic systems require decisions to be made on-line, without full knowledge of their future impact on the system. A general model for the processing of sequences of tasks is introduced, and a general on-line decision algorithm is developed. It is shown that, for an importan ..."
Abstract - Cited by 209 (8 self) - Add to MetaCart
task processing costs and state transition costs incurred. An on-line scheduling algorithm is one that chooses s, only knowing T1 Tz ~.. T’. Such an algorithm is w-competitive if, on any input task sequence, its cost is within an additive constant of w times the optimal offline schedule cost

An analysis of temporal-difference learning with function approximation

by John N. Tsitsiklis, Benjamin Van Roy - IEEE Transactions on Automatic Control , 1997
"... We discuss the temporal-difference learning algorithm, as applied to approximating the cost-to-go function of an infinite-horizon discounted Markov chain. The algorithm weanalyze updates parameters of a linear function approximator on-line, duringasingle endless trajectory of an irreducible aperiodi ..."
Abstract - Cited by 313 (8 self) - Add to MetaCart
about the dynamics of temporal-difference learning. In addition to proving new and stronger positive results than those previously available, we identify the significance of on-line updating and potential hazards associated with the use of nonlinear function approximators. First, we prove

Privacy-Preserving Public Auditing for Data Storage Security in Cloud Computing

by Cong Wang, Qian Wang, Kui Ren, Wenjing Lou - In INFOCOM , 2010
"... Abstract. Cloud Computing is the long dreamed vision of computing as a utility, where users can remotely store their data into the cloud so as to enjoy the on-demand high quality applications and services from a shared pool of configurable computing resources. By data outsourcing, users can be relie ..."
Abstract - Cited by 135 (1 self) - Add to MetaCart
), the following two fundamental requirements have to be met: 1) TPA should be able to efficiently audit the cloud data storage without demanding the local copy of data, and introduce no additional on-line burden to the cloud user; 2) The third party auditing process should bring in no new vulnerabilities towards
Results 1 - 10 of 7,012