157 citations · 1.3k across the 97 of their papers we have counts for
10 papers · 1 filter
Neural Dependencies Emerging from Learning Massive Categories
Ruili Feng, Kecheng Zheng, Kai Zhu +7
This work presents two astonishing findings on neural networks learned for large-scale image classification. 1) Given a well-trained model, the logits predicted for some category c…
Rank Diminishing in Deep Neural Networks
Ruili Feng, Kecheng Zheng, Yukun Huang +3
The rank of neural networks measures information flowing across layers. It is an instance of a key structural condition that applies across broad domains of machine learning. In pa…
Automatic Relation-aware Graph Network Proliferation
Shaofei Cai, Liang Li, Xinzhe Han +3
Graph neural architecture search has sparked much attention as Graph Neural Networks (GNNs) have shown powerful reasoning capability in many relational tasks. However, the currentl…
Principled Knowledge Extrapolation with GANs
Ruili Feng, Jie Xiao, Kecheng Zheng +4
Human can extrapolate well, generalize daily knowledge into unseen scenarios, raise and answer counterfactual questions. To imitate this ability via generative models, previous wor…
Edge-featured Graph Neural Architecture Search
Shaofei Cai, Liang Li, Xinzhe Han +2
Graph neural networks (GNNs) have been successfully applied to learning representation on graphs in many relational tasks. Recently, researchers study neural architecture search (N…
Rethinking Graph Neural Architecture Search from Message-passing
Shaofei Cai, Liang Li, Jincan Deng +4
Graph neural networks (GNNs) emerged recently as a standard toolkit for learning from data on graphs. Current GNN designing works depend on immense human expertise to explore diffe…
On Noise Injection in Generative Adversarial Networks
Ruili Feng, Deli Zhao, Zhengjun Zha
Noise injection has been proved to be one of the key technique advances in generating high-fidelity images. Despite its successful usage in GANs, the mechanism of its validity is s…
Deep Self-representative Concept Factorization Network for Representation Learning
Yan Zhang, Zhao Zhang, Zheng Zhang +4
In this paper, we investigate the unsupervised deep representation learning issue and technically propose a novel framework called Deep Self-representative Concept Factorization Ne…
Posterior-Guided Neural Architecture Search
Yizhou Zhou, Xiaoyan Sun, Chong Luo +2
The emergence of neural architecture search (NAS) has greatly advanced the research on network design. Recent proposals such as gradient-based methods or one-shot approaches signif…
Multi-Level Deep Cascade Trees for Conversion Rate Prediction in Recommendation System
Hong Wen, Jing Zhang, Quan Lin +2
Developing effective and efficient recommendation methods is very challenging for modern e-commerce platforms. Generally speaking, two essential modules named "Click-Through Rate P…