Results 1 - 10 of 2,447

Dynamic Bayesian Networks: Representation, Inference and Learning

by Kevin Patrick Murphy , 2002
"... Modelling sequential data is important in many areas of science and engineering. Hidden Markov models (HMMs) and Kalman filter models (KFMs) are popular for this because they are simple and flexible. For example, HMMs have been used for speech recognition and bio-sequence analysis, and KFMs have bee ..."
Abstract - Cited by 770 (3 self) - Add to MetaCart
Modelling sequential data is important in many areas of science and engineering. Hidden Markov models (HMMs) and Kalman filter models (KFMs) are popular for this because they are simple and flexible. For example, HMMs have been used for speech recognition and bio-sequence analysis, and KFMs have

A new approach to the maximum flow problem

by Andrew V. Goldberg, Robert E. Tarjan - JOURNAL OF THE ACM , 1988
"... All previously known efficient maximum-flow algorithms work by finding augmenting paths, either one path at a time (as in the original Ford and Fulkerson algorithm) or all shortest-length augmenting paths at once (using the layered network approach of Dinic). An alternative method based on the pre ..."
Abstract - Cited by 672 (33 self) - Add to MetaCart
to be shortest paths. The algorithm and its analysis are simple and intuitive, yet the algorithm runs as fast as any other known method on dense. graphs, achieving an O(n³) time bound on an n-vertex graph. By incorporating the dynamic tree data structure of Sleator and Tarjan, we obtain a version

A framework for clustering evolving data streams. In:

by Charu C Aggarwal , T J Watson , Resch Jiawei Ctr , Jianyong Han , Wang , Philip Yu , T J Watson , Resch Ctr - Proc of VLDB’03, , 2003
"... Abstract The clustering problem is a difficult problem for the data stream domain. This is because the large volumes of data arriving in a stream renders most traditional algorithms too inefficient. In recent years, a few one-pass clustering algorithms have been developed for the data stream proble ..."
Abstract - Cited by 359 (36 self) - Add to MetaCart
, it is not possible to simultaneously perform dynamic clustering over all possible time horizons for a data stream of even moderately large volume. This paper discusses a fundamentally different philosophy for data stream clustering which is guided by application-centered requirements. The idea is divide

Ownership Types for Flexible Alias Protection

by David G. Clarke, John M. Potter, James Noble - In Object-Oriented Programming, Systems, Languages, and Applications (OOPSLA , 1998
"... Object-oriented programming languages allow inter-object aliasing. Although necessary to construct linked data structures and networks of interacting objects, aliasing is problematic in that an aggregate object's state can change via an alias to one of its components, without the aggregate bein ..."
Abstract - Cited by 365 (41 self) - Add to MetaCart
Object-oriented programming languages allow inter-object aliasing. Although necessary to construct linked data structures and networks of interacting objects, aliasing is problematic in that an aggregate object's state can change via an alias to one of its components, without the aggregate

The distribution of realized exchange rate volatility,

by Torben G Andersen , Francis X Diebold , Tim Bollerslev , Paul Labys - Journal of the American Statistical Association , 2001
"... Using high-frequency data on deutschemark and yen returns against the dollar, we construct model-free estimates of daily exchange rate volatility and correlation that cover an entire decade. Our estimates, termed realized volatilities and correlations, are not only model-free, but also approximatel ..."
Abstract - Cited by 333 (29 self) - Add to MetaCart
Using high-frequency data on deutschemark and yen returns against the dollar, we construct model-free estimates of daily exchange rate volatility and correlation that cover an entire decade. Our estimates, termed realized volatilities and correlations, are not only model-free, but also

Ripple Joins for Online Aggregation

by Peter J. Haas, Joseph M. Hellerstein
"... We present a new family of join algorithms, called ripple joins, for online processing of multi-table aggregation queries in a relational database management system (dbms). Such queries arise naturally in interactive exploratory decision-support applications. Traditional offline join algorithms are ..."
Abstract - Cited by 188 (11 self) - Add to MetaCart
processing in accordance with the statistical properties of the data. Ripple joins also permit the user to dynamically trade off the two key performance factors of online aggregation: the time between successive updates of the running aggregate, and the amount by which the confidence-interval length

Escape analysis for Java

by Jong-deok Choi, Mannish Gupta, Mauricio Serrano, Vugranam C. Sreedhar, Sam Midkiff - OOPSLA , 1999
"... This paper presents a simple and efficient data flow algorithm for escape analysis of objects in Java programs to determine (i) if an object can be allocated on the stack; (ii) if an object is accessed only by a single thread duriing its lifetime, so that synchronization operations on that object ca ..."
Abstract - Cited by 300 (12 self) - Add to MetaCart
This paper presents a simple and efficient data flow algorithm for escape analysis of objects in Java programs to determine (i) if an object can be allocated on the stack; (ii) if an object is accessed only by a single thread duriing its lifetime, so that synchronization operations on that object

A scheme for robust distributed sensor fusion based on average consensus

by Lin Xiao, Stephen Boyd , Sanjay Lall - PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INFORMATION PROCESSING IN SENSOR NETWORKS (IPSN , 2005
"... We consider a network of distributed sensors, where each sensor takes a linear measurement of some unknown parameters, corrupted by independent Gaussian noises. We propose a simple distributed iterative scheme, based on distributed average consensus in the network, to compute the maximum-likelihoo ..."
Abstract - Cited by 257 (3 self) - Add to MetaCart
compute a local weighted least-squares estimate, which converges to the global maximum-likelihood solution. This scheme is robust to unreliable communication links. We show that it works in a network with dynamically changing topology, provided that the infinitely occurring communication graphs

The Alignment-Distribution Graph

by Siddhartha Chatterjee, John R. Gilbert, Robert Schreiber - In Proceedings of the Sixth Workshop on Languages and Compilers for Parallel Computing , 1993
"... Implementing a data-parallel language such as Fortran 90 on a distributed-memory parallel computer requires distributing aggregate data objects (such as arrays) among the memory modules attached to the processors. The mapping of objects to the machine determines the amount of residual communicatio ..."
Abstract - Cited by 143 (3 self) - Add to MetaCart
Implementing a data-parallel language such as Fortran 90 on a distributed-memory parallel computer requires distributing aggregate data objects (such as arrays) among the memory modules attached to the processors. The mapping of objects to the machine determines the amount of residual

Mapreduce online

by Tyson Condie, Neil Conway, Peter Alvaro, Joseph M. Hellerstein, Khaled Elmeleegy, Russell Sears , 2009
"... MapReduce is a popular framework for data-intensive distributed computing of batch jobs. To simplify fault tolerance, many implementations of MapReduce materialize the entire output of each map and reduce task before it can be consumed. In this paper, we propose a modified MapReduce architecture tha ..."
Abstract - Cited by 181 (3 self) - Add to MetaCart
that allows data to be pipelined between operators. This extends the MapReduce programming model beyond batch processing, and can reduce completion times and improve system utilization for batch jobs as well. We present a modified version of the Hadoop MapReduce framework that supports online aggregation
Results 1 - 10 of 2,447