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20162025
most citedMMDetection: Open MMLab Detection Toolbox and Benchmark

794 citations · 2.4k across the 85 of their papers we have counts for

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Showing cs.LGShow all

8 papers · 1 filter

cs.LG2023

Adaptive Hierarchical SpatioTemporal Network for Traffic Forecasting

Yirong Chen, Ziyue Li, Wanli Ouyang +1

Accurate traffic forecasting is vital to intelligent transportation systems, which are widely adopted to solve urban traffic issues. Existing traffic forecasting studies focus on m…

cs.LG20231 cited

Stimulative Training++: Go Beyond The Performance Limits of Residual Networks

Peng Ye, Tong He, Shengji Tang +4

Residual networks have shown great success and become indispensable in recent deep neural network models. In this work, we aim to re-investigate the training process of residual ne…

cs.LG20224 cited

ACE: Cooperative Multi-agent Q-learning with Bidirectional Action-Dependency

Chuming Li, Jie Liu, Yinmin Zhang +5

Multi-agent reinforcement learning (MARL) suffers from the non-stationarity problem, which is the ever-changing targets at every iteration when multiple agents update their policie…

cs.LG202215 cited

-DARTS: Beta-Decay Regularization for Differentiable Architecture Search

Peng Ye, Baopu Li, Yikang Li +3

Neural Architecture Search~(NAS) has attracted increasingly more attention in recent years because of its capability to design deep neural networks automatically. Among them, diffe…

cs.LG2020

Improving Auto-Augment via Augmentation-Wise Weight Sharing

Keyu Tian, Chen Lin, Ming Sun +3

The recent progress on automatically searching augmentation policies has boosted the performance substantially for various tasks. A key component of automatic augmentation search i…

cs.LG2020

Adaptive Gradient Method with Resilience and Momentum

Jie Liu, Chen Lin, Chuming Li +4

Several variants of stochastic gradient descent (SGD) have been proposed to improve the learning effectiveness and efficiency when training deep neural networks, among which some r…