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incremental singular value decomposition for some numerical aspects of multiblock redundancy analysis

COMPUTATIONAL STATISTICS 2023年 1-29页

作者： Martinez-Ruiz, Alba Lauro, Natale Carlo Univ Diego Portales Santiago Chile Univ Napoli Federico II Naples Italy

Simultaneously processing several large blocks of streaming data is a computationally expensive problem. Based on the incremental singular value decomposition algorithm, we propose a new procedure for calculating the factorization of the multiblock redundancy matrix M, which makes the multiblock method more fast and efficient when analyzing large streaming data and high-dimensional dense matrices. The procedure transforms a big data problem into a small one by processing small high-dimensional matrices where variables are in rows. Numerical experiments illustrate the accuracy and performance of the incremental solution for analyzing streaming multiblock redundancy data. The experiments demonstrate that the incremental algorithm may decompose a large matrix with a 75% reduction in execution time. It is more efficient to first partition the matrix M and then decompose it with the incremental algorithm than to decompose the entire matrix M using the standard singular value decomposition algorithm.

关键词： Matrix decomposition incremental algorithms Multiblock methods Streaming data High-dimensional data

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Creating ensemble classifiers through order and incremental data selection in a stream

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PATTERN ANALYSIS AND APPLICATIONS 2013年第3期16卷 333-347页

作者： Saunier, Nicolas Midenet, Sophie Ecole Polytech Civil Min & Geol Engn Dept Montreal PQ H3C 3A7 Canada Univ Paris Est GRETTIA IFSTTAR F-93166 Noisy Le Grand France

This paper presents an original time-sensitive traffic management application for road safety diagnosis in signalized intersections. Such applications require to deal with data streams that may be subject to concept drift over various time scales. The method for road safety analysis relies on the estimation of severity indicators for vehicle interactions based on complex and noisy spatial occupancy information. An expert provides imprecise labels based on video recordings of the traffic scenes. In order to improve the performance-overall and for each class-and the stability of learning in a stream, this paper presents new ensemble methods based on incremental algorithms that rely on their sensitivity to the processing order of instances. Different data selection criteria, many used in active learning methods, are studied in a comprehensive experimental evaluation, including benchmark datasets from the UCI machine learning repository and the prediction of severity indicators. The best performance is obtained with a criterion that selects instances which are misclassified by the current hypothesis. The proposed ensemble methods using this criterion and AdaBoost have similar principles and performance, while the proposed methods have a smaller computational training cost.

关键词： Road safety Traffic management Ensemble methods incremental algorithms

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incremental maintenance of all-pairs shortest paths in relational DBMSs

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SOCIAL NETWORK ANALYSIS AND MINING 2017年第1期7卷 1-18页

作者： Greco, Sergio Molinaro, Cristian Pulice, Chiara Quintana, Ximena Univ Calabria Arcavacata Di Rende Italy Univ Maryland College Pk MD 20742 USA

Computing shortest paths is a classical graph theory problem and a central task in many applications. Although many algorithms to solve this problem have been proposed over the years, they are designed to work in the main memory and/or with static graphs, which limits their applicability to many current applications where graphs are highly dynamic, that is, subject to frequent updates. In this paper, we propose novel efficient incremental algorithms for maintaining all-pairs shortest paths and distances in dynamic graphs. We experimentally evaluate our approach on several real-world datasets, showing that it significantly outperforms current algorithms designed for the same problem.

关键词： Shortest paths Shortest distances incremental algorithms Relational databasesn

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incremental FUZZY CLUSTERING WITH MULTIPLE KERNELS

INCREMENTAL FUZZY CLUSTERING WITH MULTIPLE KERNELS

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1st International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)

作者： Baili, Naouel Frigui, Hichem Univ Louisville Louisville KY 40292 USA

ISBN: (纸本)9781479948888

This paper presents two incremental clustering algorithms based on FCMK, a fuzzy clustering with multiple kernels algorithm we developed earlier [1]. The FCMK algorithm has a memory requirement of O(N-2), where N is the number of objects in the data set. Thus, even data sets that have nearly 1, 000, 000 objects require terabytes of working memory-impractical for most computers. One way to attack this problem is by using incremental algorithms;these algorithms sequentially process chunks or samples of the data, combining the results from each chunk. The proposed incremental algorithms neither use any complicated data structure nor any complicated data compression techniques, yet produce data partitions comparable to FCMK. We assess the performance of our incremental algorithms by, first, comparing their clustering results to that of the FCMK and, second, by showing that these algorithms can produce reasonable partitions of large data sets.

关键词： Fuzzy clustering multiple kernels incremental algorithms

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incremental Closeness Centrality for Dynamically Changing Social Networks

Incremental Closeness Centrality for Dynamically Changing So...

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IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)

作者： Kas, Miray Carley, Kathleen M. Carley, L. Richard Carnegie Mellon Univ Pittsburgh PA 15213 USA

ISBN: (纸本)9781450322409

Automation of data collection using online resources has led to significant changes in traditional practices of social network analysis. Social network analysis has been an active research field for many decades;however, most of the early work employed very small datasets. In this paper, a number of issues with traditional practices of social network analysis in the context of dynamic, large-scale social networks are pointed out. Given the continuously evolving nature of modern online social networking, we postulate that social network analysis solutions based on incremental algorithms will become more important to address high computation times for large, streaming, over-time datasets. incremental algorithms can benefit from early pruning by updating the affected parts only when an incremental update is made in the network. This paper provides an example of this case by demonstrating the design of an incremental closeness centrality algorithm that supports efficient computation of all-pairs of shortest paths and closeness centrality in dynamic social networks that are continuously updated by addition, removal, and modification of nodes and edges. Our results obtained on various synthetic and real-life datasets provide significant speedups over the most commonly used method of computing closeness centrality, suggesting that incremental algorithm design is a fruitful research area for social network analysts.

关键词： Closeness Centrality incremental algorithms Dynamic All-Pair Shortest Path Dynamic Networks

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Video content representation by incremental non-negative matrix factorization

Video content representation by incremental non-negative mat...

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IEEE International Conference on Image Processing (ICIP 2007)

作者： Bucak, Serhat S. Gunsel, Bilge Istanbul Tech Univ Dept Elect & Comm Engn Multimedia Signal Proc & Pattern Recognit Lab TR-34469 Maslak Turkey

ISBN: (纸本)9781424414369

Nonnegative Matrix Factorization (NMF) is a powerful decomposition tool which has been used in several content representation applications recently. However, there are some difficulties in implementing NMF in on-line video applications. This paper introduces an incremental NMF (INMF) without deviating from conventional NMFs main objective function, which is minimizing the reconstruction error. The proposed algorithm is capable of modeling dynamic content of the video;thus controls contribution of the subsequent observations to the NMF representation properly. It is shown that the INMF preserves additive, parts-based representation capability of the NW with a low computational load while offering dimension reduction. Experimental results are given to compare the reconstruction performances of the conventional and incremental NMF In addition, video scene change detection and dynamic video content representation by INMF are investigated. Test results demonstrate that the INMF can be used as a powerful on-line factorization tool.

关键词： non-negative matrix factorization incremental algorithms video content representation

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Fast incremental Least Square Pose Estimation for Hardware Implementation with Rolling Shutter Camera 28

Fast Incremental Least Square Pose Estimation for Hardware I...

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28th Signal Processing and Communications Applications Conference (SIU)

作者： Guzel, Aydin Emre Hisar, Dilara Claesen, Luc Ugurdag, H. Fatih Ozyegin Univ Istanbul Turkey Hasselt Univ Hasselt Belgium

ISBN: (纸本)9781728172064

6 DoF position and orientation estimation is vital for many real-time applications. It is essential to meet low latency, high accuracy and reliability requirements, especially when used for real-time haptic feedback calculation in medical applications. Considering the low latency requirement, designing dedicated hardware promises significant improvements relative to running software on the processor. In our jaw surgery application, we aim to calculate the pose of the rigid object with the tracked marker from the rolling shutter camera by exploiting parallelism and pipe-lining concepts under 1 millisecond latency without sacrificing accuracy on field programmable gate arrays (FPGA) to flow from the camera with rolling shutter effect. Therefore, the iterative least squared algorithm, which is used with high precision in the current applications, has been given an incremental shape to react within the same frame according to the instantaneous data. The algorithm was evaluated by testing with different parameters over the software with synthetically produced fixed and rolling shutter effect images.

关键词： incremental algorithms least squares optimizations pose estimation

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Work-Efficient Batch-incremental Minimum Spanning Trees with Applications to the Sliding-Window Model 20

Work-Efficient Batch-Incremental Minimum Spanning Trees with...

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32nd ACM Symposium on Parallelism in algorithms and Architectures (SPAA)

作者： Anderson, Daniel Blelloch, Guy E. Tangwongsan, Kanat Carnegie Mellon Univ Pittsburgh PA 15213 USA Mahidol Univ Int Coll Bangkok Thailand

ISBN: (纸本)9781450369350

algorithms for dynamically maintaining minimum spanning trees (MSTs) have received much attention in both the parallel and sequential settings. While previous work has given optimal algorithms for dense graphs, all existing parallel batch-dynamic algorithms perform polynomial work per update in the worst case for sparse graphs. In this paper, we present the first work-efficient parallel batch-dynamic algorithm for incremental MST, which can insert l edges in O(l lg(1 + n/l)) work in expectation and O(polylog(n)) span w.h.p. The key ingredient of our algorithm is an algorithm for constructing a compressed path tree of an edge-weighted tree, which is a smaller tree that contains all pairwise heaviest edges between a given set of marked vertices. Using our batch-incremental MST algorithm, we demonstrate a range of applications that become efficiently solvable in parallel in the sliding-window model, such as graph connectivity, approximate MSTs, testing bipartiteness, k-certificates, cycle-freeness, and maintaining sparsifiers.

关键词： dynamic algorithms minimum spanning trees dynamic graphs parallel algorithms incremental algorithms

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incremental reconstruction of generalized Voronoi diagrams on grids

Incremental reconstruction of generalized Voronoi diagrams o...

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9th International Conference on Intelligent Autonomous Systems (IAS-9)

作者： Kalra, Nidhi Ferguson, Dave Stentz, Anthony RAND Corp Pittsburgh PA 15213 USA Intel Res Pittsburgh PA USA Carnegie Mellon Univ Inst Robot Pittsburgh PA 15213 USA

ISBN: (纸本)1586035959

We present an incremental algorithm for constructing and reconstructing Generalized Voronoi Diagrams (GVDs) oil grids. Our algorithm, Dynamic Brushfire, uses techniques from the path planning community to efficiently update GVDs when the underlying environment changes or when new information concerning the environment is received. Dynamic Brushfire is an order of magnitude more efficient than current approaches. In this paper we present the algorithm, compare it to current approaches oil several experimental domains involving loth simulated and real data, and demonstrate its usefulness for multirobot path planning. (C) 2007 Elsevier B.V. All rights reserved.

关键词： Voronoi diagrams incremental algorithms Robot navigation

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incremental Algorithm for Updating Betweenness Centrality in Dynamically Growing Networks

Incremental Algorithm for Updating Betweenness Centrality in...

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IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)

作者： Kas, Miray Wachs, Matthew Carley, Kathleen M. Carley, L. Richard Carnegie Mellon Univ Pittsburgh PA 15213 USA

ISBN: (纸本)9781450322409

The increasing availability of dynamically growing digital data that can be used for extracting social networks has led to an upsurge of interest in the analysis of dynamic social networks. One key aspect of social network analysis is to understand the central nodes in a network. However, dynamic calculation of centrality values for rapidly growing networks might be unfeasibly expensive, especially if it involves recalculation from scratch for each time period. This paper proposes an incremental algorithm that effectively updates betweenness centralities of nodes in dynamic social networks while avoiding re-computations by exploiting information from earlier computations. Our performance results suggest that our incremental betweenness algorithm can achieve substantial performance speedup, on the order of thousands of times, over the state of the art, including the best-performing non-incremental betweenness algorithm and a recently proposed betweenness update algorithm.

关键词： Betweenness Centrality incremental algorithms Dynamic Networks All-Pairs Shortest Paths

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