Results 271 to 280 of about 275,247 (311)

Distributed Incremental Graph Analysis

2016 IEEE International Congress on Big Data (BigData Congress), 2016
Distributed frameworks, such as MapReduce and Spark, have been developed by industry and research groups to analyze the vast amount of data that is being generated on a daily basis. Many graphs of interest, such as the Web graph and Social Networks, increase their size daily at an unprecedented scale and rate.
Upa Gupta, Leonidas Fegaras
openaire   +1 more source

Incremental analysis in machine learning

Proceedings of the 24th European Conference on Pattern Languages of Programs, 2019
Supervised learning requires data to be labeled. However, labels may not always be available, or creating a labeled dataset may be costly. Even when the data is labeled, labeling is often inconsistent, incomplete and inaccurate. If the data changes over time, a model also needs to be retrained periodically. A machine learning model, therefore, needs to
Michael Weiss 0001, Steven Muegge, Ali Nazari   +2 more
openaire   +1 more source

Incremental data flow analysis

Proceedings of the 10th ACM SIGACT-SIGPLAN symposium on Principles of programming languages - POPL '83, 1983
In this paper we present ACINCF and ACINCB, incremental update algorithms for forward and backward data flow problems, which are based on a linear equations model of Allen/Cocke interval analysis [Allen 77, Ryder 82a]. We have studied their performance on a robust structured programming language L.
openaire   +1 more source

Incremental tensor analysis

ACM Transactions on Knowledge Discovery from Data, 2008
How do we find patterns in author-keyword associations, evolving over time? Or in data cubes (tensors), with product-branchcustomer sales information? And more generally, how to summarize high-order data cubes (tensors)? How to incrementally update these patterns over time?
Jimeng Sun 0001, Dacheng Tao, Spiros Papadimitriou, Philip S. Yu, Christos Faloutsos   +4 more
openaire   +1 more source

On Incremental Analysis in Resource Allocations

Operational Research Quarterly (1970-1977), 1976
This paper discusses the use of incremental analysis for solving a generalized version of the one constraint resource allocation problem considered by Shih. It also provides a proof of the optimality of his solution procedure.
openaire   +1 more source

Incremental Kernel Principal Component Analysis

IEEE Transactions on Image Processing, 2007
The kernel principal component analysis (KPCA) has been applied in numerous image-related machine learning applications and it has exhibited superior performance over previous approaches, such as PCA. However, the standard implementation of KPCA scales badly with the problem size, making computations for large problems infeasible.
Tat-Jun Chin, David Suter
openaire   +3 more sources

Incremental dynamic analysis

Earthquake Engineering & Structural Dynamics, 2001
AbstractIncremental dynamic analysis (IDA) is a parametric analysis method that has recently emerged in several different forms to estimate more thoroughly structural performance under seismic loads. It involves subjecting a structural model to one (or more) ground motion record(s), each scaled to multiple levels of intensity, thus producing one (or ...
Dimitrios Vamvatsikos, C. Allin Cornell
openaire   +1 more source

Incremental analysis of interference among aspects

Proceedings of the 7th workshop on Foundations of aspect-oriented languages, 2008
Often, insertion of several aspects into one system is desired and in that case the problem of interference among the different aspects might arise, even if each aspect individually woven is correct relative to its specification. In this type of interference, one aspect can prevent another from having the required effect on a woven system.
Emilia Katz, Shmuel Katz
openaire   +1 more source

Incremental Sensitivity Analysis for Kernelized Models

2021
Despite their superior accuracy to simpler linear models, kernelized models can be prohibitively expensive in applications where the training set changes frequently, since training them is computationally intensive. We provide bounds for the changes in a kernelized model when its training set has changed, as well as bounds on the prediction of the new ...
Hadar Sivan, Moshe Gabel, Assaf Schuster
openaire   +1 more source

Incremental Large-Scale Electrostatic Analysis

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2009
In this paper, we propose methods to accelerate the solution of multiple related linear systems of equations. Such systems arise, for example, in building pattern libraries for interconnect parasitic extraction, parasitic extraction under process variation, and parameterized interconnect characterization.
Zuochang Ye, Zhenhai Zhu, Joel R. Phillips   +2 more
openaire   +1 more source