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Computer Science 논문 리뷰
Computer Science 분야 주요 연구 논문을 연구 동기·방법·결과로 구조화한 AI 논문 리뷰 목록입니다.
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필터
9999+개의 결과
Deep Networks with Stochastic Depth
Gao Huang, Yu Sun 외 3명
arXiv (Cornell University)
|
2016
|
287 회 인용
Is feature selection secure against training data poisoning?
Xiao Huang, Battista Biggio 외 4명
arXiv (Cornell University)
|
2018
|
287 회 인용
Large-Scale Adversarial Training for Vision-and-Language Representation Learning
Zhe Gan, Yen-Chun Chen 외 4명
arXiv (Cornell University)
|
2020
|
287 회 인용
On Lazy Training in Differentiable Programming
Lénaïc Chizat, Edouard Oyallon 외 1명
arXiv (Cornell University)
|
2018
|
287 회 인용
Reinforcement Learning in Large Discrete Action Spaces.
Gabriel Dulac-Arnold, Richard Evans 외 2명
arXiv (Cornell University)
|
2015
|
287 회 인용
A simple approach for finding the globally optimal Bayesian network structure
Tomi Silander, Petri Myllymäki
arXiv (Cornell University)
|
2012
|
286 회 인용
Learning continuous control policies by stochastic value gradients
Nicolas Heess, Greg Wayne 외 4명
arXiv (Cornell University)
|
2015
|
286 회 인용
Maximum Entropy Deep Inverse Reinforcement Learning
Markus Wulfmeier, Peter Ondrúška 외 1명
arXiv (Cornell University)
|
2015
|
286 회 인용
Pixel-BERT: Aligning Image Pixels with Text by Deep Multi-Modal Transformers
Zhicheng Huang, Zhaoyang Zeng 외 3명
arXiv (Cornell University)
|
2020
|
286 회 인용
WILDS: A Benchmark of in-the-Wild Distribution Shifts
Pang Wei Koh
CaltechAUTHORS (California Institute of Technology)
|
2020
|
286 회 인용
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