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Computer Science 论文解读
Computer Science 领域重要论文的 AI 解读列表，按研究动机、方法与结果结构化呈现。
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Deep Networks with Stochastic Depth
Gao Huang, Yu Sun, +3
arXiv (Cornell University)
|
2016
|
287 citations
Is feature selection secure against training data poisoning?
Xiao Huang, Battista Biggio, +4
arXiv (Cornell University)
|
2018
|
287 citations
Large-Scale Adversarial Training for Vision-and-Language Representation Learning
Zhe Gan, Yen-Chun Chen, +4
arXiv (Cornell University)
|
2020
|
287 citations
On Lazy Training in Differentiable Programming
Lénaïc Chizat, Edouard Oyallon, +1
arXiv (Cornell University)
|
2018
|
287 citations
Reinforcement Learning in Large Discrete Action Spaces.
Gabriel Dulac-Arnold, Richard Evans, +2
arXiv (Cornell University)
|
2015
|
287 citations
A simple approach for finding the globally optimal Bayesian network structure
Tomi Silander, Petri Myllymäki
arXiv (Cornell University)
|
2012
|
286 citations
Learning continuous control policies by stochastic value gradients
Nicolas Heess, Greg Wayne, +4
arXiv (Cornell University)
|
2015
|
286 citations
Maximum Entropy Deep Inverse Reinforcement Learning
Markus Wulfmeier, Peter Ondrúška, +1
arXiv (Cornell University)
|
2015
|
286 citations
Pixel-BERT: Aligning Image Pixels with Text by Deep Multi-Modal Transformers
Zhicheng Huang, Zhaoyang Zeng, +3
arXiv (Cornell University)
|
2020
|
286 citations
WILDS: A Benchmark of in-the-Wild Distribution Shifts
Pang Wei Koh
CaltechAUTHORS (California Institute of Technology)
|
2020
|
286 citations
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