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A Framework for Algorithm Stability [article]

Wouter Meulemans, Bettina Speckmann, Kevin Verbeek, Jules Wulms
2018 arXiv   pre-print
In this paper we present a framework for analyzing the stability of algorithms.  ...  Our framework allows for three types of stability analysis with increasing degrees of complexity: event stability, topological stability, and Lipschitz stability.  ...  We present a framework to measure and analyze the stability of algorithms.  ... 
arXiv:1704.08000v2 fatcat:3iuaqeswyfbdtk2czx5nr4g2dm

SelfWISE: A Framework for Developing Self-Stabilizing Algorithms [chapter]

Christoph Weyer, Volker Turau
2009 Kommunikation in Verteilten Systemen (KiVS)  
Algorithms defined for abstract models Simple set operations Christoph Weyer Framework for Developing Self-Stabilizing Algorithms Christoph Weyer Framework for Developing Self-Stabilizing Algorithms 11  ...  Christoph Weyer Framework for Developing Self-Stabilizing Algorithms Christoph Weyer Framework for Developing Self-Stabilizing Algorithms 8 8 Need for simplifying the programming Hide low-level  ...  SelfWISE: A Framework for Developing Self-Stabilizing Algorithms  ... 
doi:10.1007/978-3-540-92666-5_6 dblp:conf/kivs/WeyerT09 fatcat:wrrtwm7s5bh6npf6ouqornrd4m

A Framework for Algorithm Stability and Its Application to Kinetic Euclidean MSTs [chapter]

Wouter Meulemans, Bettina Speckmann, Kevin Verbeek, Jules Wulms
2018 Lecture Notes in Computer Science  
We present a framework to analyze the stability of (combinatorial) algorithms.  ...  Conclusion We presented a framework for algorithm stability, which includes three types of stability analysis, namely event stability, topological stability, and Lipschitz stability.  ... 
doi:10.1007/978-3-319-77404-6_58 fatcat:ppdsa32kynhnhfxwbqi7ypjif4

The Stability and Accuracy Tradeoff Under Dataset Shift: A Causal Graphical Analysis [article]

Adarsh Subbaswamy, Bryant Chen, Suchi Saria
2021 arXiv   pre-print
The hierarchy provides a common theoretical underpinning for understanding when and how stability to shifts can be achieved, and in what ways stable distributions can differ.  ...  However, these methods consider different types of shifts and have been developed under disparate frameworks, making it difficult to theoretically analyze how solutions differ with respect to stability  ...  Contributions In this paper, we provide a unifying framework for specifying dataset shifts that can occur, analyzing model stability to these shifts, and determining conditions for achieving the lowest  ... 
arXiv:1905.11374v4 fatcat:4zbmiwwekjchddoz67xl5p5s6a

A variance reduction framework for stable feature selection

Yue Han, Lei Yu
2012 Statistical analysis and data mining  
The framework also suggests a variance reduction approach for improving the stability of feature selection algorithms.  ...  In this study, we present a theoretical framework about the relationship between the stability and accuracy of feature selection based on a formal bias-variance decomposition of feature selection error  ...  In addition, our study proposes an instance weighting framework for improving the stability of feature selection algorithms.  ... 
doi:10.1002/sam.11152 fatcat:duzdmtipjvbbbjo7wqq4b5auza

A Variance Reduction Framework for Stable Feature Selection

Yue Han, Lei Yu
2010 2010 IEEE International Conference on Data Mining  
The framework also suggests a variance reduction approach for improving the stability of feature selection algorithms.  ...  In this study, we present a theoretical framework about the relationship between the stability and accuracy of feature selection based on a formal bias-variance decomposition of feature selection error  ...  In addition, our study proposes an instance weighting framework for improving the stability of feature selection algorithms.  ... 
doi:10.1109/icdm.2010.144 dblp:conf/icdm/HanY10 fatcat:3zipero2f5dlxgjjpjvlzp5ojm

Impact of EPON DBA Components on Performance

Michael P. McGarry, Martin Reisslein, Frank Aurzada, Michael Scheutzow
2011 2011 Proceedings of 20th International Conference on Computer Communications and Networks (ICCCN)  
We introduce a convenient notational framework for Dynamic Bandwidth Allocation (DBA) algorithms in Ethernet Passive Optical Networks (EPONs) that uses the three principal axes of grant scheduling framework  ...  We find that the grant sizing has the strongest impact on the delay and the combined grant scheduling framework and policy have the strongest impact on the stability limit.  ...  CONCLUSION In conclusion, we presented a novel notational framework for identifying DBA algorithms and have conducted a performance evaluation that varies all three components of a DBA algorithm.  ... 
doi:10.1109/icccn.2011.6005773 dblp:conf/icccn/McGarryRAS11 fatcat:qhwni2iqarc2db7stacijekp2e

Self-Controllable Super-Resolution Deep Learning Framework for Surveillance Drones in Security Applications

Soohyun Park, Yeongeun Kang, Jeman Park, Joongheon Kim
2020 EAI Endorsed Transactions on Security and Safety  
This paper proposes a self-controllable super-resolution adaptation algorithm in drone platforms. The drone platforms are generally used for surveillance in target network areas.  ...  Thus, super-resolution algorithms which are for enhancing surveillance video quality are essential.  ...  [19] design a secure learning framework for CCTVbased surveillance applications.  ... 
doi:10.4108/eai.30-6-2020.165502 fatcat:6hfw4eyta5fujac2op5ouilohy

Building Self-stabilizing Overlay Networks with the Transitive Closure Framework [chapter]

Andrew Berns, Sukumar Ghosh, Sriram V. Pemmaraju
2011 Lecture Notes in Computer Science  
The goal in these papers is to design self-stabilizing algorithms for overlay network construction; these algorithms run on the individual nodes of a weakly-connected network and, by node actions that  ...  We demonstrate the power of our framework by deriving from TCF a simple self-stabilizing protocol for constructing Skip+ graphs (Jacob et al., PODC 2009) which presents optimal convergence time from any  ...  This is a "framework" rather than an algorithm and by instantiating certain subroutines in this framework we can obtain self-stabilizing algorithms for specific overlay networks.  ... 
doi:10.1007/978-3-642-24550-3_7 fatcat:34oi5wnxojgntdwthrqls2prdi

Building self-stabilizing overlay networks with the transitive closure framework

Andrew Berns, Sukumar Ghosh, Sriram V. Pemmaraju
2013 Theoretical Computer Science  
The goal in these papers is to design self-stabilizing algorithms for overlay network construction; these algorithms run on the individual nodes of a weakly-connected network and, by node actions that  ...  We demonstrate the power of our framework by deriving from TCF a simple self-stabilizing protocol for constructing Skip+ graphs (Jacob et al., PODC 2009) which presents optimal convergence time from any  ...  This is a "framework" rather than an algorithm and by instantiating certain subroutines in this framework we can obtain self-stabilizing algorithms for specific overlay networks.  ... 
doi:10.1016/j.tcs.2013.02.021 fatcat:mb2w6ywbkvdqdbfyfqrqxulxli

Consensus group stable feature selection

Steven Loscalzo, Lei Yu, Chris Ding
2009 Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '09  
We propose a novel framework for stable feature selection which first identifies consensus feature groups from subsampling of training samples, and then performs feature selection by treating each consensus  ...  In this paper, we show that stability of feature selection has a strong dependency on sample size.  ...  ACKNOWLEDGMENTS The authors would like to thank anonymous reviewers for their helpful comments. C. Ding is partially supported by NSF-CCF-0830780 and NSF-DMS-0844497.  ... 
doi:10.1145/1557019.1557084 dblp:conf/kdd/LoscalzoYD09 fatcat:p6phltvaurf5hffpwj7w644nn4

Stable Feature Selection with Minimal Independent Dominating Sets

Le Shu, Tianyang Ma, Longin Jan Latecki
2007 Proceedings of the International Conference on Bioinformatics, Computational Biology and Biomedical Informatics - BCB'13  
Furthermore, the proposed MIDS framework complements standard feature selection algorithms like SVM-RFE, stability lasso and ensemble SVM RFE.  ...  The main contribution is a novel framework for selecting most informative features which can preserve the linear combination property of the original feature space.  ...  The proposed MIDS framework with the other two stability feature selection algorithms also has a higher stability on average.  ... 
doi:10.1145/2506583.2506600 dblp:conf/bcb/ShuML13 fatcat:5vfgxproqnhpdkbuhigs25hjtm

Programming Wireless Sensor Networks in a Self-Stabilizing Style

Christoph Weyer, Volker Turau, Andreas Lagemann, Jörg Nolte
2009 2009 Third International Conference on Sensor Technologies and Applications  
The analysis is accomplished with Self-WISE, a framework providing programming abstractions for self-stabilizing algorithms.  ...  This demonstrates the usability of SelfWISE for evaluating self-stabilizing algorithms under a wide range of models.  ...  It consists of the SelfWISE framework (see Fig. 2 ) that is the runtime environment for executing self-stabilizing algorithm and a language to express those algorithms (see Fig. 1, reffig:color, and  ... 
doi:10.1109/sensorcomm.2009.100 fatcat:5eojslgr7rc23eeehhizlmvkgy

Margin Based Sample Weighting for Stable Feature Selection [chapter]

Yue Han, Lei Yu
2010 Lecture Notes in Computer Science  
A key factor affecting the stability of a feature selection algorithm is the sample size of training set.  ...  We also develop an efficient algorithm under the framework.  ...  To improve the stability of a feature selection Algorithm 2.  ... 
doi:10.1007/978-3-642-14246-8_65 fatcat:lfakjzm6djeixifv6wzhxjsrbq

Fast Stability Scanning for Future Grid Scenario Analysis [article]

Ruidong Liu, Gregor Verbic, Jin Ma
2016 arXiv   pre-print
In this paper, we propose a planning framework for fast stability scanning of future grid scenarios using a novel feature selection algorithm and a novel self-adaptive PSO-k-means clustering algorithm.  ...  As a case study, we perform small-signal stability and steady-state voltage stability scanning of a simplified model of the Australian National Electricity Market with significant penetration of renewable  ...  We propose a framework for fast stability scanning to achieve a significant computational speed-up.  ... 
arXiv:1701.03436v1 fatcat:6dopos5ab5g57kh5dr7hryc3c4
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