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ACM SIGMOD International Conference on Management of Data

作者： Hay, Michael Machanavajjhala, Ashwin Miklau, Gerome Chen, Yan Zhang, Dan Bissias, George Colgate Univ Dept Comp Sci Hamilton NY 13346 USA Duke Univ Dept Comp Sci Durham NC 27706 USA UMass Amherst Coll Comp & Informat Sci Amherst MA USA

ISBN: (纸本)9781450335317

The emergence of differential privacy as a primary standard for privacy protection has led to the development, by the research community, of hundreds of algorithms for various data analysis tasks. Yet deployment of these techniques has been slowed by the complexity of algorithms and an incomplete understanding of the cost to accuracy implied by the adoption of differential privacy. In this demonstration we present DPCOMP, a publicly-accessible web-based system, designed to support a broad community of users, including data analysts, privacy researchers, and data owners. Users can use DPCOMP to assess the accuracy of state-of-the-art privacy algorithms and interactively explore algorithm output in order to understand, both quantitatively and qualitatively, the error introduced by the algorithms. In addition, users can contribute new algorithms and new (non-sensitive) datasets. DPCOMP automatically incorporates user contributions into an evolving benchmark based on a rigorous evaluation methodology articulated by Hay et al. [4].

关键词： differential privacy privacy algorithm evaluation

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Generating Structured Argumentation Frameworks: AFBenchGen2

Generating Structured Argumentation Frameworks: AFBenchGen2

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6th International Conference on Computational Models of Argument (COMMA)

作者： Cerutti, Federico Giacomin, Massimiliano Vallati, Mauro Cardiff Univ Sch Comp Sci & Informat Cardiff CF10 3AX S Glam Wales Univ Brescia Dept Informat Engn I-25121 Brescia Italy Univ Huddersfield Sch Comp & Engn Huddersfield HD1 3DH W Yorkshire England

In this paper we describe AFBenchGen2, which allows to randomised argumentation frameworks for testing purposes with a large variety of structures.

ISBN: (纸本)9781614996866

In this paper we describe AFBenchGen2, which allows to randomised argumentation frameworks for testing purposes with a large variety of structures.

关键词： argumentation frameworks benchmarks algorithm evaluation

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Microbial phenomics information extractor (MicroPIE): a natural language processing tool for the automated acquisition of prokaryotic phenotypic characters from text sources

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BMC BIOINFORMATICS 2016年第1期17卷 528-528页

作者： Mao, Jin Moore, Lisa R. Blank, Carrine E. Wu, Elvis Hsin-Hui Ackerman, Marcia Ranade, Sonali Cui, Hong Univ Arizona Sch Informat Tucson AZ 85721 USA Univ Southern Maine Dept Biol Sci Portland ME 04103 USA Univ Montana Dept Geosci Missoula MT 59812 USA

Background: The large-scale analysis of phenomic data (i.e., full phenotypic traits of an organism, such as shape, metabolic substrates, and growth conditions) in microbial bioinformatics has been hampered by the lack of tools to rapidly and accurately extract phenotypic data from existing legacy text in the field of microbiology. To quickly obtain knowledge on the distribution and evolution of microbial traits, an information extraction system needed to be developed to extract phenotypic characters from large numbers of taxonomic descriptions so they can be used as input to existing phylogenetic analysis software packages. Results: We report the development and evaluation of Microbial Phenomics Information Extractor (MicroPIE, version 0.1.0). MicroPIE is a natural language processing application that uses a robust supervised classification algorithm (Support Vector Machine) to identify characters from sentences in prokaryotic taxonomic descriptions, followed by a combination of algorithms applying linguistic rules with groups of known terms to extract characters as well as character states. The input to MicroPIE is a set of taxonomic descriptions (clean text). The output is a taxon-by-character matrix-with taxa in the rows and a set of 42 pre-defined characters (e.g., optimum growth temperature) in the columns. The performance of MicroPIE was evaluated against a gold standard matrix and another student-made matrix. Results show that, compared to the gold standard, MicroPIE extracted 21 characters (50%) with a Relaxed F1 score > 0.80 and 16 characters (38%) with Relaxed F1 scores ranging between 0.50 and 0.80. Inclusion of a character prediction component (SVM) improved the overall performance of MicroPIE, notably the precision. Evaluated against the same gold standard, MicroPIE performed significantly better than the undergraduate students. Conclusion: MicroPIE is a promising new tool for the rapid and efficient extraction of phenotypic character information from p

关键词： Information extraction Phenotypic data extraction Prokaryotic taxonomic descriptions Microbial phenotypes Character matrices Support vector machine Machine learning Text mining algorithm evaluation Natural language processing

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Exploration of a physiologically-inspired hearing-aid algorithm using a computer model mimicking impaired hearing

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International Audiology 2016年第6期55卷 346-357页

Objective: To use a computer model of impaired hearing to explore the effects of a physiologically-inspired hearing-aid algorithm on a range of psychoacoustic ***: A computer model of a hypothetical impaired listener’s hearing was constructed by adjusting parameters of a computer model of normal hearing. Absolute thresholds, estimates of compression, and frequency selectivity (summarized to a hearing profile) were assessed using this model with and without pre-processing the stimuli by a hearing-aid algorithm. The influence of different settings of the algorithm on the impaired profile was investigated. To validate the model predictions, the effect of the algorithm on hearing profiles of human impaired listeners was *** sample: A computer model simulating impaired hearing (total absence of basilar membrane compression) was used, and three hearing-impaired listeners ***: The hearing profiles of the model and the listeners showed substantial changes when the test stimuli were pre-processed by the hearing-aid algorithm. These changes consisted of lower absolute thresholds, steeper temporal masking curves, and sharper psychophysical tuning ***: The hearing-aid algorithm affected the impaired hearing profile of the model to approximate a normal hearing profile. Qualitatively similar results were found with the impaired listeners’ hearing profiles.

关键词： Auditory model algorithm evaluation normal and impaired hearing psychoacoustics

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Improved Boosting Performance by Explicit Handling of Ambiguous Positive Examples 2

Improved Boosting Performance by Explicit Handling of Ambigu...

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2nd International Conference on Pattern Recognition Applications and Methods (ICPRAM)

作者： Kobetski, Miroslav Sullivan, Josephine KTH Comp Vis & Act Percept S-11428 Stockholm Sweden

ISBN: (纸本)9783319126104;9783319126098

Visual classes naturally have ambiguous examples, that are different depending on feature and classifier and are hard to disambiguate from surrounding negatives without overfitting. Boosting in particular tends to overfit to such hard and ambiguous examples, due to its flexibility and typically aggressive loss functions. We propose a two-pass learning method for identifying ambiguous examples and relearning, either subjecting them to an exclusion function or using them in a later stage of an inverted cascade. We provide an experimental comparison of different boosting algorithms on the VOC2007 dataset, training them with and without our proposed extension. Using our exclusion extension improves the performance of almost all of the tested boosting algorithms, without adding any additional test-time cost. Our proposed inverted cascade adds some test-time cost but gives additional improvements in performance. Our results also suggest that outlier exclusion is complementary to positive jittering and hard negative mining.

关键词： Boosting Image classification algorithm evaluation Dataset pruning VOC2007

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algorithms for network-based identification of differential regulators from transcriptome data: a systematic evaluation

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Science China(Life Sciences) 2014年第11期57卷 1090-1102页

作者： YU Hui MITRA Ramkrishna YANG Jing LI YuanYuan ZHAO ZhongMing Department of Biomedical Informatics Vanderbilt University School of Medicine School of Biotechnology East China University of Science and Technology Shanghai Center for Bioinformation Technology Department of Cancer Biology Vanderbilt University School of Medicine Department of Psychiatry Vanderbilt University School of Medicine Center for Quantitative Sciences Vanderbilt University

Identification of differential regulators is critical to understand the dynamics of cellular systems and molecular mechanisms of *** computational algorithms have recently been developed for this purpose by using transcriptome and network ***,it remains largely unclear which algorithm performs better under a specific *** knowledge is important for both appropriate application and future enhancement of these ***,we systematically evaluated seven main algorithms(TED,TDD,TFactS,RIF1,RIF2,dCSA_t2t,and dCSA_r2t),using both simulated and real *** our simulation evaluation,we artificially inactivated either a single regulator or multiple regulators and examined how well each algorithm detected known gold standard *** found that all these algorithms could effectively discern signals arising from regulatory network differences,indicating the validity of our simulation *** the seven tested algorithms,TED and TFactS were placed first and second when both discrimination accuracy and robustness against data variation were *** applied to two independent lung cancer datasets,both TED and TFactS replicated a substantial fraction of their respective differential *** TED and TFactS rely on two distinct features of transcriptome data,namely differential co-expression and differential expression,both may be applied as mutual references during practical application.

关键词： differential regulation differential co-expression differential expression simulation algorithm evaluation transcription factor

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Analysis of Four Remote Image Fusion algorithms for Landsat7 ETM+ PAN and Multi- spectral Imagery

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INTERNATIONAL JOURNAL OF ONLINE ENGINEERING 2014年第3期10卷 49-52页

作者： Yuan, Debao Hong, Xueqian Yu, Shiwei Li, Liangjian Zhao, Yanbo CUMTB Coll Geosci & Surveying Engn Beijing 100083 Peoples R China

This study takes the southeastern part of Beijing as an example to compare four remote image fusion algorithms for improving the visualization of Landsat7 ETM+ imagery. This paper introduces four remote image fusion algorithms including the Smoothing Filter Based Intensity Modulation (SFIM), High Pass Filter (HPF) Transform, Brovey Transform, and Multiplication (MLT) Transform. The effectiveness of the four remote image fusion algorithms is evaluated based on different quantitative indexes, including mean, deviation, information entropy, average gradient and correlation. The study reveals that the SFIM transform is the best method to remain spectral information of the original remote image, which does not cause spectral distortion and has highest spatial frequency information. Moreover, the fused remote images from the same sensor system are of high quality and can be used for improving the latter visual interpretation.

关键词： remote data fusion algorithm ETM+ PAN and multi-spectral algorithm evaluation

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Shape Analysis, A Field in Need of Careful Validation

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HUMAN BRAIN MAPPING 2014年第10期35卷 4965-4978页

作者： Gao, Yi Riklin-Raviv, Tammy Bouix, Sylvain Univ Alabama Birmingham Dept Elect & Comp Engn Birmingham AL USA Univ Alabama Birmingham Ctr Comprehens Canc Neurooncol Program Birmingham AL 35294 USA Ben Gurion Univ Negev Dept Elect & Comp Engn IL-84105 Beer Sheva Israel Harvard Univ Sch Med Psychiat Neuroimaging Lab Dept PsychiatBrigham & Womens Hosp Boston MA 02115 USA

In the last two decades, the statistical analysis of shape has become an actively studied field and finds applications in a wide range of areas. In addition to algorithmic development, many researchers have distributed end-user orientated toolboxes, which further enable the utilization of the algorithms in an off the shelf fashion. However, there is little work on the evaluation and validation of these techniques, which poses a rather serious challenge when interpreting their results. To address this lack of validation, we design a validation framework and then use it to test some of the most widely used toolboxes. Our initial results show inconsistencies and disagreement among four different methods. We believe this type of analysis to be critical not only for the community of algorithm designers but also perhaps more importantly to researchers who use these tools without knowing the algorithm details and seek objective criteria for tool selection. Hum Brain Mapp 35:4965-4978, 2014. (c) 2014 Wiley Periodicals, Inc.

关键词： statistical shape analysis algorithm evaluation reproducibility

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Generating Challenging Benchmark AFs 5

Generating Challenging Benchmark <i>AF</i>s

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5th Conference on Computational Models of Argument (COMMA)

作者： Cerutti, Federico Giacomin, Massimiliano Vallati, Mauro Univ Aberdeen Kings Coll Dept Comp Sci Aberdeen AB9 1FX Scotland Univ Brescia Dept Informat Engn I-25121 Brescia Italy Univ Huddersfield Sch Comp & Engn Huddersfield HD1 3DH W Yorkshire England

In this paper we describe the AFBenchGen system, which allows to automatically generate randomised argumentation frameworks for testing purposes.

ISBN: (纸本)9781614994367;9781614994350

In this paper we describe the AFBenchGen system, which allows to automatically generate randomised argumentation frameworks for testing purposes.

关键词： argumentation frameworks argumentation benchmarks algorithm evaluation

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Evaluating Lesion Segmentation on Breast Sonography as Related to Lesion Type

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JOURNAL OF ULTRASOUND IN MEDICINE 2013年第9期32卷 1659-1670页

作者： Pons, Gerard Marti, Joan Marti, Robert Ganau, Sergi Caries Vilanova, Joan Noble, J. Alison Univ Girona Dept Comp Architecture & Technol Girona 17071 Spain Corp Parc Tauli UDIAT Diagnost Ctr Dept Radiol Sabadell Spain Univ Girona Girona Magnet Resonance Imaging Ctr Girona 17071 Spain Univ Oxford Dept Engn Sci Oxford OX1 3PJ England

Breast sonography currently provides a complementary diagnosis when other modalities are not conclusive. However, lesion segmentation on sonography is still a challenging problem due to the presence of artifacts. To solve these problems, Markov random fields and maximum a posteriori-based methods are used to estimate a distortion field while identifying regions of similar intensity inhomogeneity. In this study, different initialization approaches were exhaustively evaluated using a database of 212 B-mode breast sonograms and considering the lesion types. Finally, conclusions about the relationship between the segmentation results and lesions types are described.

关键词： algorithm evaluation breast lesion segmentation Markov random fields maximum a posteriori sonography

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