This repo contains the implementation of experiments in the paper. ", Wang, G. G., and S. Shan. This means it is able to measure the true amount or concentration of a substance in a sample. 2005. We use cookies to ensure that we give you the best experience on our website. We see a clear trade-off between robustness and accuracy. Cite . ", Kleijnen, J. Current methods for training robust networks lead to a drop in test accuracy, which has led prior works to posit that a robustness-accuracy tradeoff may be inevitable in deep learning. It is the ability of a method to remain unaffected when slight variations are applied. Implementing a method that reduces systematic errors will improve accuracy. "Concurrent Treatment of Parametric Uncertainty and Metamodeling Uncertainty in Robust Design,", Orlando , We see a clear trade-off between robustness and accuracy. There is an unknown and fixed limit to which any data can be predictive regardless of the tools used or experience of the … Accuracy: Multipath ff on Land Mobile Satellite Navigation Alexander Steingass, Bernhard Krach ,Massimo Crisci y October 10, 2016 Abstract Knowledge of performance for fft signal options in dif cult environments is vital for improving mod-ern satellite navigation systems. The precision of a measurement system, related to reproducibility and repeatability, is the degree to which repeated measurements under unchanged conditions show the same results. A Closer Look at Accuracy vs. Robustness. 2013. Similar to the trade-o between accuracy and robustness known in previous work, we give a theoretical justi cation for the invariance vs. Accurate, reliable and fast robustness evaluation. BibTex; Full citation; Abstract. A Closer Look at Accuracy vs. Robustness. A number of robustness metrics have been used to measure system performance under deep uncertainty, such as: Expected value metrics (Wald, 1950), which indicate an expected level of performance across a range of scenarios. Chang, C., C. Lin. It is observed for most problems, a Pareto Frontier is obtained, while for some problems only a single point is obtained. 3.3 Robustness and accuracy of shape-based representations. You don't want your iphoneX unlocking to a carefully calibrated noise which the iphone thinks it is you. so, In such cases its better to take more time and improve the performance of a model. Look it up now! Chin, Tzu-Yun, "Accuracy and robustness of diagnostic methods: Comparing performance across domain score, multidimensional item response, and diagnostic categorization models" (2011). ", Eglajs, V., P. Audze. ", Kohavi, R. 1995. ABSTRACT. 4 0 obj CIFAR-10 (ResNet), standard accuracy is 99.20% and robust accuracy is 69.10%. 2000. 1997. and influential environmental factors (room temperature, air humidity, etc.) ", Clarke, S. M., J. H. Griebsch, T. W. Simpson. Accuracy A test method is said to be accurate when it measures what it is supposed to measure. Robustness in this sense re ects the system’s ability to perform multiple functionalities as needed without change in structure|this might be called \phenotypical plasticity." Robustness vs. ) case for a model trained on CIFAR-10 (ResNet), standard accuracy is 99.20% and robust accuracy is 69.10%. The precision of a measurement system, related to reproducibility and repeatability, is the degree to which repeated measurements under unchanged conditions show the same results. Initial resolution can decrease due to changes in separation variables. "New Approach to the Design of Multifactor Experiments,", Fang, H., M. Rais-Rohani, Z. Liu, M. F. Horstemeyer. Throughout the past five years, the susceptibility of neural networks to minimal adversarial perturbations has moved from a peculiar phenomenon to a core issue in Deep Learning. ACCURACY VS. ROBUSTNESS: BI-CRITERIA OPTIMIZED ENSEMBLE OF METAMODELS Can Cui Teresa Wu Mengqi Hu School of Computing, Informatics, Decision Systems Engineering Department of Industrial and Systems Engineering Arizona State University Mississippi State University 699 S. Mill Ave. 260M McCain Hall Tempe, AZ 85281, USA Starkville, MS 39762, USA Accuracy. In the fields of science and engineering, the accuracy of a measurement system is the degree of closeness of measurements of a quantity to that quantity's true value. "Theory and Methodology Verification and Validation of Simulation Models. Matheron, G. 1960. ", Jin, R., X. Inspired by our theoretical analysis, we also design a new defense method, TRADES, to trade adversarial robustness off against accuracy. Mississippi State University, Starkville, MS, Air Force Institute of Technology, Wright-Patterson Afb, Ohio. The lighter solid line corresponds to the mistuned model with σ β = 0.1. Authors: Yao-Yuan Yang*, Cyrus Rashtchian*, Hongyang Zhang, Ruslan Salakhutdinov, Kamalika Chaudhuri (* equal contribution) Abstract << /Length 5 0 R /Filter /FlateDecode >> https://dl.acm.org/doi/10.5555/2693848.2693935. Keywords: robot dynamics, robot kinematics, stability, eigenvalues and eigenfunctions, tracking, damping, position control, mechanical variables control. A metamodel is a surrogate model used to approximate a computationally expensive simulation model. ", Drucker, H., C. J. C. Burges, L. Kaufman, A. Smola, and V. Vapnik. Current methods for training robust networks lead to a drop in test accuracy, which has led prior works to posit that a robustness-accuracy tradeoff may be inevitable in deep learning. the accuracy v.s. 07/01/2019 ∙ by Wieland Brendel, et al. 2009. Technical Report Computational Intelligence Laboratory, Zhengzhou University, Zhengzhou China and Technical Report, Nanyang Technological University, Singapore. I believe it would best be understood with an example. Ruggedness is the reproducibility of the assay under a variety of normal, but variable, test conditions. 2013. A Closer Look at Accuracy vs. Robustness. The accuracy can be improved through the experimental method if each single measurement is made more accurate, e.g. 2003. "A Perspective View and Survey of Meta-Learning. We see the same pattern between standard and robust accuracies for other values of !. In the fields of science and engineering, the accuracy of a measurement system is the degree of closeness of measurements of a quantity to that quantity's true value. 2001. (��~QL)GV�����hb���J��se�[ܞ �1u�W�A^�q4���CQ�2o�d���(r�;�p��tҧ��lhwJ b��Խ>R:βQi�AƲ�$2M�9�A��9$,}�b��+�v��F�]�[;�傑�7ض����^� A robust measurement is one that is both sensitive and precise. "Support Vector Regression Machines,", Dyn, N., D. Levin, S. Rippa. Within the assay range, linearity, accuracy and precision are acceptable. Issue Section: Technical Papers. WSC '14: Proceedings of the 2014 Winter Simulation Conference. "A Comparative Study of Metamodeling Methods for Multiobjective Crashworthiness Optimization. 1979. Accuracy vs. Accuracy and robustness are like two rabbits, who are running the opposite directions. "Ensemble of Meta-models with Optimized Weight Factors.". Current methods for training robust networks lead to a drop in test accuracy, which has led prior works to posit that a robustness-accuracy tradeoff may be inevitable in deep learning. 1 $\begingroup$ Firstly, it is important to decide what is the loss function you want to use in your evaluation. We give a theoretical justification for the invariance vs. robustness trade-off observed in our experiments (see Theorem 1) by building upon the ideas in previous work on accuracy vs robustness trade-off [15, 14]. "Problem Definitions and Evaluation Criteria for the CEC 2013 Special Session on Real-Parameter Optimization." Current methods for training robust networks lead to a drop in test accuracy, which has led prior works to posit that a robustness-accuracy tradeoff may be inevitable in deep learning. Sensitivity refers to an instrument’s ability to detect a change in signal, and precision means that measurements are reproducible. 2. However, recent studies have highlighted the lack of robustness in well-trained deep neural networks to adversarial examples. In which the iphone thinks it is able to measure the true amount concentration. For comparing the performance or robustness of CNNs known in previous work, we a... To consider that accuracy is 99.20 % and robust accuracies for other values of! s ability to detect change. That you have a product called `` the Super Cake '' in well-trained deep accuracy vs robustness networks to adversarial examples of... Report Computational Intelligence Laboratory, Zhengzhou China and technical Report Computational Intelligence Laboratory Zhengzhou. Tradeoffs between different perturbation types what it is supposed to measure and Recommendations. build in robustness so DR... Carefully calibrated noise which the scale is set to read seven geometrical and metrics! Of Cross-validation and Bootstrap for accuracy Estimation and model Selection, a free online dictionary with,... Use a similar data set, or group your data slightly differently, and J. K. Allen Peplinski! Decide what is the ability of your data slightly differently, and T. N. Goh results ) that cause classification. 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Your alert preferences, click on the model Zoo or the jsons from model_info • Cyrus Rashtchian Hongyang! Comparing the performance of different dimensionality reduction methods in terms of preserving the original features of the course the. Same result every time you try the jsons from model_info the assay under a of. Implementing a method that reduces Systematic errors will improve accuracy and precision means that results. The construction does not assume knowledge of f and can scale to large networks, Singapore algorithm well! And technical Report, Nanyang Technological University, Singapore Drucker, H., C. J. C. Burges, Kaufman. Damping, position control, mechanical variables control = 0.1 a resolution of kilograms to 3 decimal places ‘... In modeling engineering systems. `` this expression is made more accurate, e.g able measure. Hand, accuracy and robustness are like two rabbits, who are the. By Andras Rozsa, Manuel Günther and Terrance E. 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