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BERT Goes to SQL School: Improving Automatic Grading of SQL Statements

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BERT Goes to SQL School: Improving Automatic Grading of SQL ...

Computer Science, Computer Engineering, & Applied computing (CSCE), Congress in

作者： Pablo Rivas Donald R. Schwartz Ernesto Quevedo Dept. of Computer Science School of Eng. & Computer Science Baylor University Dept. of Computing Technology School of Computer Science & Math. Marist College

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A stochastic modeling approach for traffic analysis of a tramway system with virtual tags and local positioning

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Journal of the Brazilian Computer Society 2021年第1期27卷 1-38页

作者： da Silva, Leandro Dias Lollini, Paolo Mongelli, Diamantea Bondavalli, Andrea Mandò, Gianluca Computing Institute Federal University of Alagoas Maceió Brazil Resiltech S.R.L. Pontedera Italy Dept. of Math. and Computer Science University of Florence Firenze Italy University of Florence Firenze Italy Innovation & Technology Thales Italia SpA Pontedera Italy

Traditional solutions for tramway interlocking systems are based on physical sensors (balizes) distributed along the infrastructure which detect passing of the trams and trigger different actions, like the communications with the ground infrastructure and the interlocking system. This approach is not easily scalable and maintainable, and it is costly. The SISTER project designed new architectural solutions for addressing the previous problems based on the virtualization of the sensors and on the local positioning of each tram. The key idea is to trigger actions when the computed local position corresponds to a virtual tag. However, the computed position can be affected by errors, compared to the real one. Therefore, it is important to understand the impact of these new solutions on the traffic that can be supported by the tramway network. This paper presents a stochastic modeling approach for analysing the performability of a tramway system based on the SISTER architectural solutions, aiming to identify the parts of the tramway network that are more critical and sensible to the variation of the traffic conditions and to the setting of the key architectural parameters. We build a model using Stochastic Activity Networks and run sensitivity analyses on (i) the accuracy of the positioning, (ii) the different SISTER parameters, and (iii) considering possible outages temporarily blocking the journey of a tram. This analysis allows to properly set and fine-tune the key architectural parameters, to understand the impact of the accuracy on the positioning, to understand the impact of the outages. © 2021, The Author(s).

关键词： Stochastic systems

MIXUP-BASED DEEP METRIC LEARNING APPROACHES FOR INCOMPLETE SUPERVISION

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arXiv 2022年

作者： Buris, Luiz H. Pedronette, Daniel C.G. Papa, Joao P. Almeida, Jurandy Carneiro, Gustavo Faria, Fabio Augusto Institute of Science and Technology Universidade Federal de São Paulo Brazil Depart. of Statistics Applied Math. and Computing São Paulo State University Brazil Department of Computing São Paulo State University Brazil Department of Computing Federal University of São Carlos Brazil Australian Institute for Machine Learning The University of Adelaide Australia

Deep learning architectures have achieved promising results in different areas (e.g., medicine, agriculture, and security). However, using those powerful techniques in many real applications becomes challenging due to the large labeled collections required during training. Several works have pursued solutions to overcome it by proposing strategies that can learn more for less, e.g., weakly and semi-supervised learning approaches. As these approaches do not usually address memorization and sensitivity to adversarial examples, this paper presents three deep metric learning approaches combined with Mixup for incomplete-supervision scenarios. We show that some state-of-the-art approaches in metric learning might not work well in such scenarios. Moreover, the proposed approaches outperform most of them in different datasets. Copyright © 2022, The Authors. All rights reserved.

关键词： Deep learning

Higher order hesitant fuzzy Choquet integral operator and its application to multiple criteria decision making

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arXiv 2020年

作者： Farhadinia, B. Aickelin, U. Khorshidi, H.A. Dept. Math. Quchan University of Technology Iran Dept. Computing and Information Systems University of Melbourne Australia

Generally, the criteria involved in a decision making problem are interactive or interdependent, and therefore aggregating them by the use of traditional operators which are based on additive measures is not logical. This verifies that we have to implement fuzzy measures for modelling the interaction phenomena among the criteria. On the other hand, based on the recent extension of hesitant fuzzy set, called higher order hesitant fuzzy set (HOHFS) which allows the membership of a given element to be defined in forms of several possible generalized types of fuzzy set, we encourage to propose the higher order hesitant fuzzy (HOHF) Choquet integral operator. This concept not only considers the importance of the higher order hesitant fuzzy arguments, but also it can reflect the correlations among those arguments. Then, a detailed discussion on the aggregation properties of the HOHF Choquet integral operator will be presented. To enhance the application of HOHF Choquet integral operator in decision making, we first assess the appropriate energy policy for the socio-economic development. Then, the efficiency of the proposed HOHF Choquet integral operator-based technique over a number of exiting techniques is further verified by employing another decision making problem associated with the technique of TODIM (an acronym in Portuguese of Interactive and Multicriteria Decision Making). © 2020, CC-BY.

关键词： Integral equations

Uncertainty measures for probabilistic hesitant fuzzy sets in multiple criteria decision making

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arXiv 2020年

作者： Farhadinia, B. Aickelin, U. Khorshidi, H.A. Dept. Math. Quchan University of Technology Iran Dept. Computing and Information Systems University of Melbourne Australia

This contribution reviews critically the existing entropy measures for probabilistic hesitant fuzzy sets (PHFSs), and demonstrates that these entropy measures fail to effectively distinguish a variety of different PHFSs in some cases. In the sequel, we develop a new axiomatic framework of entropy measures for probabilistic hesitant fuzzy elements (PHFEs) by considering two facets of uncertainty associated with PHFEs which are known as fuzziness and non-specificity. Respect to each kind of uncertainty, a number of formulae are derived to permit flexible selection of PHFE entropy measures. Moreover, based on the proposed PHFE entropy measures, we introduce some entropy-based distance measures which are used in the portion of comparative analysis. Eventually, the proposed PHFE entropy measures and PHFE entropy-based distance measures are applied to decision making in the strategy initiatives where their reliability and effectiveness are verified. © 2020, CC-BY.

关键词： Decision making

Competitive Online Optimization under Inventory Constraints

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Performance Evaluation Review 2019年第1期47卷 35-36页

作者： Lin, Qiulin Yi, Hanling Pang, John Chen, Minghua Wierman, Adam Honig, Michael Xiao, Yuanzhang Information Engineering Chinese University of Hong Kong China Computing and Math. Sciences California Institute of Technology United States Electrical Engineering Northwestern University United States Hawaii Center for Adv. Comm. University of Hawaii at Manoa United States

This paper studies online optimization under inventory (budget) constraints. While online optimization is a well-studied topic, versions with inventory constraints have proven difficult. We consider a formulation of inventory-constrained optimization that is a generalization of the classic one-way trading problem and has a wide range of applications. We present a new algorithmic framework, CR-Pursuit, and prove that it achieves the optimal competitive ratio among all deterministic algorithms (up to a problem-dependent constant factor) for inventory-constrained online optimization. Our algorithm and its analysis not only simplify and unify the state-ofthe-art results for the standard one-way trading problem, but they also establish novel bounds for generalizations including concave revenue functions. For example, for one-way trading with price elasticity, CR-Pursuit achieves a competitive ratio within a small additive constant (i.e., 1/3) to the lower bound of ln θ + 1, where θ is the ratio between the maximum and minimum base prices. © 2019 Copyright is held by the owner/author(s).

关键词： Constrained optimization

Competitive online optimization under inventory constraints 19

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Competitive online optimization under inventory constraints

14th Joint Conference of International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS 2019 and IFIP Performance Conference 2019, SIGMETRICS/Performance 2019

ISBN: (纸本)9781450366786

This paper studies online optimization under inventory (budget) constraints. While online optimization is a well-studied topic, versions with inventory constraints have proven difficult. We consider a formulation of inventory-constrained optimization that is a generalization of the classic one-way trading problem and has a wide range of applications. We present a new algorithmic framework, CR-Pursuit, and prove that it achieves the optimal competitive ratio among all deterministic algorithms (up to a problem-dependent constant factor) for inventory-constrained online optimization. Our algorithm and its analysis not only simplify and unify the state-ofthe- art results for the standard one-way trading problem, but they also establish novel bounds for generalizations including concave revenue functions. For example, for one-way trading with price elasticity, CR-Pursuit achieves a competitive ratio within a small additive constant (i.e., 1/3) to the lower bound of ln θ + 1, where θ is the ratio between the maximum and minimum base prices. © 2019 Copyright held by the owner/author(s).

关键词： Constrained optimization

Competitive online optimization under inventory constraints

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arXiv 2019年

作者： Lin, Qiulin Yi, Hanling Wierman, Adam Pang, John Honig, Michael Chen, Minghua Xiao, Yuanzhang Information Engineering Chinese University of Hong Kong Computing and Math. Sciences California Institute of Technology Electrical Engineering Northwestern University Hawaii Center for Adv. Comm. University of Hawaii Manoa United States

This paper studies online optimization under inventory (budget) constraints. While online optimization is a well-studied topic, versions with inventory constraints have proven difficult. We consider a formulation of inventory-constrained optimization that is a generalization of the classic one-way trading problem and has a wide range of applications. We present a new algorithmic framework, CR-Pursuit, and prove that it achieves the minimal competitive ratio among all deterministic algorithms (up to a problem-dependent constant factor) for inventory-constrained online optimization. Our algorithm and its analysis not only simplify and unify the state-of-the-art results for the standard one-way trading problem, but they also establish novel bounds for generalizations including concave revenue functions. For example, for one-way trading with price elasticity, the CR-Pursuit algorithm achieves a competitive ratio that is within a small additive constant (i.e., 1/3) to the lower bound of ln θ + 1, where θ is the ratio between the maximum and minimum base prices. Copyright © 2019, The Authors. All rights reserved.

关键词： Constrained optimization

A second-order and nonuniform time-stepping maximum-principle preserving scheme for time-fractional Allen-Cahn equations

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arXiv 2019年

作者： Liao, Hong-Lin Tang, Tao Zhou, Tao Department of Mathematics Nanjing University of Aeronautics and Astronautics Nanjing211106 China Department of Mathematics and International Center for Mathematics Southern University of Science and Technology Shenzhen Guangdong Province China Division of Science and Technology BNU-HKBU United International College Zhuhai Guangdong Province China NCMIS and LSEC Inst. of Compl. Math. and Sci./Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China

In this work, we present a second-order nonuniform time-stepping scheme for the time-fractional Allen-Cahn equation. We show that the proposed scheme preserves the discrete maximum principle, and by using the convolution structure of consistency error, we present sharp maximum-norm error estimates which reflect the temporal regularity. As our analysis is built on nonuniform time steps, we may resolve the intrinsic initial singularity by using the graded meshes. Moreover, we propose an adaptive time-stepping strategy for large time simulations. Numerical experiments are presented to show the effectiveness of the proposed scheme. This seems to be the first second-order maximum principle preserving scheme for the time-fractional Allen-Cahn *** Codes 35Q99, 65M06, 65M12, 74A50 Copyright © 2019, The Authors. All rights reserved.

关键词： Maximum principle