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Guaranteed Validity for Empirical Approaches to Adaptive Data Analysis
[article]
2020
arXiv
pre-print
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Our main contribution is to design a framework for providing valid, instance-specific confidence intervals for point estimates that can be generated by heuristics. ...
We design a general framework for answering adaptive statistical queries that focuses on providing explicit confidence intervals along with point estimates. ...
Acknowledgements The authors would like to thank Omer Tamuz for helpful comments regarding a conjecture that existed in a prior version of this work. ...
arXiv:1906.09231v2
fatcat:suzno2narbg73moropqjv4vxry
The Everlasting Database: Statistical Validity at a Fair Price
[article]
2019
arXiv
pre-print
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Crucially, we guarantee statistical validity without any assumptions on how the queries are generated. ...
The problem of handling adaptivity in data analysis, intentional or not, permeates a variety of fields, including test-set overfitting in ML challenges and the accumulation of invalid scientific discoveries ...
Preserving statistical validity in adaptive data analysis. CoRR, abs/1411.2664, 2014. ...
arXiv:1803.04307v3
fatcat:u2uhicg2uzht5atwjnpvadcvjq
Robust domain-adaptive discriminant analysis
2021
Pattern Recognition Letters
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a non-adaptive classifier without having to rely on the validity of strong assumptions. ...
Consider a domain-adaptive supervised learning setting, where a classifier learns from labeled data in a source domain and unlabeled data in a target domain to predict the corresponding target labels. ...
Since there is no labeled target data available for validation, we set the regularization parameter to a small value, namely 0.01. ...
doi:10.1016/j.patrec.2021.05.005
fatcat:dtquptrsrvcupbtq37s5xk4w4u
CURRENT CHALLENGES AND SOLUTION APPROACHES IN EMPIRICAL ENGINEERING DESIGN RESEARCH – A WORKSHOP FOR EMPIRICAL RESEARCH
2020
Proceedings of the Design Society: DESIGN Conference
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AbstractThe requirements on validity for studies in design research are very high. ...
Resulting main challenges are to find a suitable task, to operationalise the variables and to deal with a high analysis effort per participant. ...
Acknowledgements We would like to thank all studies' participants, data collectors and analysers, who enabled a data basis rich enough to be analysed systematically and thus contributed to empirical design ...
doi:10.1017/dsd.2020.280
fatcat:4lcli2udj5b3zlffac6ps524gm
A Logical Approach for Empirical Risk Minimization in Machine Learning for Data Stratification
2017
Research Journal of Mathematics and Computer Science
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Hence the logical approach to determine the empirical risk minimization function for in machine learning for CML data stratification is shown in figure 1 . ...
Methodology A logical approach for Empirical Risk Minimization in machine learning for Data Stratification is developed to aid a better grouping of Chronic Myeloid Leukemia disease dataset. ...
doi:10.28933/rjmcs-2017-10-3002
fatcat:nidkvqzadbhxfbhqzkyutiu5fe
Understanding and Comparing Approaches for Performance Engineering of Self-adaptive Systems Based on Queuing Networks
2021
Journal of Ubiquitous Systems and Pervasive Networks
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Enabling self-adaptation within hardware/software systems is a complex task, mainly due to environment uncertainty that has to be faced while the system is providing its functionalities. ...
Besides, non-functional goals that have to be met by the system may be introduced, defining Quality-of-Service (QoS) requirements which drive the adaptation. ...
The author would like to thank Dott. Davide Di Ruscio for his precious suggestions concerning paper presentation. ...
doi:10.5383/juspn.14.02.004
fatcat:aj24mmmfcrfolk3mu5hpzrflza
PAC Prediction Sets for Meta-Learning
[article]
2022
arXiv
pre-print
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We study this problem in the context of meta learning, where the goal is to quickly adapt a predictor to new tasks. ...
In particular, our prediction sets satisfy the PAC guarantee while having smaller size compared to other baselines that also satisfy this guarantee. ...
A limitation of the current approach is that it requires enough calibration datapoints to satisfy the PAC guarantee, see [3] for an analysis. ...
arXiv:2207.02440v1
fatcat:baxqc6r7dbbfpbiorgjmbj3g5i
Preserving Statistical Validity in Adaptive Data Analysis
[article]
2016
arXiv
pre-print
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In this work we initiate a principled study of how to guarantee the validity of statistical inference in adaptive data analysis. ...
A great deal of effort has been devoted to reducing the risk of spurious scientific discoveries, from the use of sophisticated validation techniques, to deep statistical methods for controlling the false ...
Acknowledgements We would like to thank Sanjeev Arora, Nina Balcan, Avrim Blum, Dean Foster, Michael Kearns, Jon Kleinberg, Sasha Rakhlin, and Jon Ullman for enlightening discussions and helpful comments ...
arXiv:1411.2664v3
fatcat:q2oslwlcx5co7fnjdybn4n5pse
Claims and Evidence for Architecture-Based Self-adaptation: A Systematic Literature Review
[chapter]
2013
Lecture Notes in Computer Science
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studies used for data collection. ...
Architecture-based self-adaptation is a promising approach to tackle these challenges. ...
However, reflecting on the results and analysis of our study, we conclude that there are opportunities for improving coherence in research to move the field forward. ...
doi:10.1007/978-3-642-39031-9_22
fatcat:svpmyzvjvfbsdi5jqsa3i2ktki
On the Fundamental Tautology of Validating Data-Driven Models and Simulations
[chapter]
2005
Lecture Notes in Computer Science
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This paper discusses the fundamental irrelevance of conventional validation procedures with respect to data-driven models and simulations. ...
need for a critical evaluation of paradigms underlying Qualification, Validation and Verification (QV&V). ...
Darema for her support of our DDDAS-related activities. Partial support from NRL's 6.1 core-funding is also greatly acknowledged. ...
doi:10.1007/11428848_95
fatcat:xy2h6y24zzhadpse7cec3ot45i
Target Robust Discriminant Analysis
[article]
2021
arXiv
pre-print
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We construct robust parameter estimators for discriminant analysis that guarantee performance improvements of the adaptive classifier over the non-adaptive source classifier. ...
In practice, the data distribution at test time often differs, to a smaller or larger extent, from that of the original training data. ...
Since no labelled target data is available for validation, the regularization parameter was set to 0.01 for logistic and 0.01n for quadratic losses. ...
arXiv:1806.09463v2
fatcat:iivrruu3xraxzku7wzpvhqsbde
Preserving Statistical Validity in Adaptive Data Analysis
2015
Proceedings of the Forty-Seventh Annual ACM on Symposium on Theory of Computing - STOC '15
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In this work we initiate a principled study of how to guarantee the validity of statistical inference in adaptive data analysis. ...
A great deal of effort has been devoted to reducing the risk of spurious scientific discoveries, from the use of sophisticated validation techniques, to deep statistical methods for controlling the false ...
Acknowledgements We would like to particularly thank Jon Ullman for many enlightening discussions about this work. ...
doi:10.1145/2746539.2746580
dblp:conf/stoc/DworkFHPRR15
fatcat:4bwgkro545gonpjd72m7pvacre
Distribution-Free Federated Learning with Conformal Predictions
[article]
2022
arXiv
pre-print
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2021 pre-print arXiv:2110.07661v1 fatcat:2gozf3nvgvhjxgpf73kamjpcuq
In this paper, we propose to address these challenges by incorporating an adaptive conformal framework into federated learning to ensure distribution-free prediction sets that provide coverage guarantees ...
Empirical results on the MedMNIST medical imaging benchmark demonstrate our federated method provides tighter coverage over local conformal predictions on 6 different medical imaging datasets for 2D and ...
Ethical approval was not required as confirmed by the license attached with the open access data. ...
arXiv:2110.07661v2
fatcat:rcyyd74vlnfojfoqp3rgxzkblm
A Triple-A supply chain measurement model: validation and analysis
2018
International Journal of Physical Distribution & Logistics Management
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scale for future empirical research and industrial applications. ...
Design/methodology/approach -Following a literature review, Triple-A SC variables (agility, alignment and adaptability) are conceptualized and a list of possible items is created for their measurement. ...
The findings provide guidance for empirical research with parsimonious data. ...
doi:10.1108/ijpdlm-06-2018-0233
fatcat:73tjj3z3krh47if7ifbd6lmpoe
Adaptive Kalman Filtering
1985
Journal of Research of the National Bureau of Standards
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Modifications to the filter involve allowing the filter to adapt the measurement model to the experimental data through matching the theoretical and observed covariance of the filter innovations sequence ...
When valid models are available, many methods work well, but when models used in the estimation are in error, most methods fail. ...
Approaches using factor analysis [7] have Bracketed figures indicate literature refrencrs. been developed for situations where the model is unknown, but these approaches are generally limited to very ...
doi:10.6028/jres.090.032
pmid:34566171
pmcid:PMC6644984
fatcat:pty5ponyrfaj5mrguqdq6wczja
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