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arXiv (Cornell University)
DICE: Diversity in Deep Ensembles via Conditional Redundancy Adversarial\n Estimation
2021
Deep ensembles perform better than a single network thanks to the diversity\namong their members. Recent approaches regularize predictions to increase\ndiversity; however, they also drastically decrease individual members'\nperformances. In this paper, we arg…
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Computer Science

Study of computation

Computer science is the study of computation, information, and automation. Computer science spans theoretical disciplines (such as algorithms, theory of computation, and information theory) to applied disciplines (including the design and implementation of hardware and software).

Algorithms and data structures are central to computer science. The theory of computation concerns abstract models of computation and general classes of problems that can be solved using them. The fields of cryptography and computer security involve studying the means for secure communication and preventing security vulnerabilities. Computer graphics and computational geometry address the generation of images.

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arXiv (Cornell University)
DICE: Diversity in Deep Ensembles via Conditional Redundancy Adversarial\n Estimation
2021
Deep ensembles perform better than a single network thanks to the diversity\namong their members. Recent approaches regularize predictions to increase\ndiversity; however, they also drastically decrease individual members'\nperformances. In this paper, we argue that learning strategies for deep\nensembles need to tackle the trade-off between ensemble diversity and\nindividual accuracies. Motivated by arguments from information theory and\nleveraging recent advances in neural estimation of conditional mutual\ninfor…
Click Computer Science Vs:
Dice
Artificial Intelligence
Machine Learning
Redundancy (Engineering)
Deep Learning
Diversity (Politics)
Mathematics
Statistics
Embedded System
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Anthropology