受强制性开放获取政策约束的文章 - Sheng Chen了解详情
可在其他位置公开访问的文章:16 篇
Toward mining capricious data streams: A generative approach
Y He, B Wu, D Wu, E Beyazit, S Chen, X Wu
IEEE transactions on neural networks and learning systems, 2020
强制性开放获取政策: US National Science Foundation, 国家自然科学基金委员会
Migrating Gradual Types
JP CAMPORA III, S CHEN, M ERWIG, E WALKINGSHAW
强制性开放获取政策: US National Science Foundation, US Department of Defense
Online Learning in Variable Feature Spaces under Incomplete Supervision
Y He, X Yuan, S Chen, X Wu
强制性开放获取政策: US National Science Foundation, 国家自然科学基金委员会
Casts and costs: harmonizing safety and performance in gradual typing
JP Campora, S Chen, E Walkingshaw
Proceedings of the ACM on Programming Languages 2 (ICFP), 98, 2018
强制性开放获取政策: US National Science Foundation, US Department of Defense
Principal type inference for GADTs
S Chen, M Erwig
Proceedings of the 43rd Annual ACM SIGPLAN-SIGACT Symposium on Principles of …, 2016
强制性开放获取政策: US National Science Foundation
A calculus for variational programming
S Chen, M Erwig, E Walkingshaw
LIPIcs-Leibniz International Proceedings in Informatics 56, 2016
强制性开放获取政策: US National Science Foundation
Generating precise error specifications for C: a zero shot learning approach
B Wu, JP Campora III, Y He, A Schlecht, S Chen
Proceedings of the ACM on Programming Languages 3 (OOPSLA), 1-30, 2019
强制性开放获取政策: US National Science Foundation
Systematic identification and communication of type errors
S Chen, M Erwig
Journal of Functional Programming 28, 2018
强制性开放获取政策: US National Science Foundation
Exploiting diversity in type checkers for better error messages
S Chen, M Erwig, K Smeltzer
Journal of Visual Languages & Computing, 2016
强制性开放获取政策: US National Science Foundation
Unsupervised Lifelong Learning with Curricula
Y He, S Chen, B Wu, X Yuan, X Wu
Proceedings of the Web Conference 2021, 3534-3545, 2021
强制性开放获取政策: US National Science Foundation, 国家自然科学基金委员会
Deep Matrix Tri-Factorization: Mining Vertex-wise Interactions in Multi-Space Attributed Graphs
Y He, S Chen, T Nguyen, BA Wade, X Wu
Proceedings of the 2020 SIAM International Conference on Data Mining, 334-342, 2020
强制性开放获取政策: US National Science Foundation
Blame Tracking and Type Error Debugging
S Chen, JP Campora III
3rd Summit on Advances in Programming Languages (SNAPL 2019), 2019
强制性开放获取政策: US National Science Foundation
Type-Based Gradual Typing Performance Optimization
JP Campora, MW Khan, S Chen
Proceedings of the ACM on Programming Languages 8 (POPL), 2667-2699, 2024
强制性开放获取政策: US National Science Foundation
Migrating gradual types
JP Campora, S Chen, M Erwig, E Walkingshaw
Journal of Functional Programming 32, e14, 2022
强制性开放获取政策: US National Science Foundation
Efficient Counter-factual Type Error Debugging
S Chen, B Wu
2019 International Symposium on Theoretical Aspects of Software Engineering …, 2019
强制性开放获取政策: US National Science Foundation
Improving Type Error Reporting for Type Classes
S Chen, MR Noor
International Symposium on Functional and Logic Programming, 19-38, 2022
强制性开放获取政策: US National Science Foundation
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