-
Complete the Missing Half: Augmenting Aggregation Filtering with Diversification for Graph Convolutional Networks
The core operation of Graph Neural Networks (GNNs) is the aggregation en...
08/20/2020 ∙ by Sitao Luan, et al. ∙
3
∙
share
read it
-
Training Matters: Unlocking Potentials of Deeper Graph Convolutional Neural Networks
The performance limit of Graph Convolutional Networks (GCNs) and the fac...
08/20/2020 ∙ by Sitao Luan, et al. ∙
6
∙
share
read it
-
META-Learning Eligibility Traces for More Sample Efficient Temporal Difference Learning
Temporal-Difference (TD) learning is a standard and very successful rein...
06/16/2020 ∙ by Mingde Zhao, et al. ∙
0
∙
share
read it
-
Exploring Overall Contextual Information for Image Captioning in Human-Like Cognitive Style
Image captioning is a research hotspot where encoder-decoder models comb...
10/15/2019 ∙ by Hongwei Ge, et al. ∙
0
∙
share
read it
-
Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks
Recently, neural network based approaches have achieved significant impr...
06/05/2019 ∙ by Sitao Luan, et al. ∙
2
∙
share
read it
-
Faster and More Accurate Learning with Meta Trace Adaptation
Learning speed and accuracy are of universal interest for reinforcement ...
04/25/2019 ∙ by Mingde Zhao, et al. ∙
0
∙
share
read it
-
A Reference Vector based Many-Objective Evolutionary Algorithm with Feasibility-aware Adaptation
The infeasible parts of the objective space in difficult many-objective ...
04/12/2019 ∙ by Mingde Zhao, et al. ∙
15
∙
share
read it
-
Online Decisioning Meta-Heuristic Framework for Large Scale Black-Box Optimization
Out of practical concerns and with the expectation to achieve high overa...
12/17/2018 ∙ by Mingde Zhao, et al. ∙
0
∙
share
read it
-
An Interactive Many Objective Evolutionary Algorithm with Cascade Clustering and Reference Point Incremental Learning
Researches have shown difficulties in obtaining proximity while maintain...
03/03/2018 ∙ by Hongwei Ge, et al. ∙
0
∙
share
read it
