21 citations · 24 across the 6 of their papers we have counts for
6 papers
Copula for Instance-wise Feature Selection and Ranking
Hanyu Peng, Guanhua Fang, Ping Li
Instance-wise feature selection and ranking methods can achieve a good selection of task-friendly features for each sample in the context of neural networks. However, existing appr…
MetaTPTrans: A Meta Learning Approach for Multilingual Code Representation Learning
Weiguo Pian, Hanyu Peng, Xunzhu Tang +5
Representation learning of source code is essential for applying machine learning to software engineering tasks. Learning code representation from a multilingual source code datase…
Dataset Pruning: Reducing Training Data by Examining Generalization Influence
Shuo Yang, Zeke Xie, Hanyu Peng +3
The great success of deep learning heavily relies on increasingly larger training data, which comes at a price of huge computational and infrastructural costs. This poses crucial q…
New Perspective on Progressive GANs Distillation for One-class Novelty Detection
Zhiwei Zhang, Yu Dong, Hanyu Peng +1
One-class novelty detection is conducted to identify anomalous instances, with different distributions from the expected normal instances. In this paper, the Generative Adversarial…
Instance-weighted Central Similarity for Multi-label Image Retrieval
Zhiwei Zhang, Hanyu Peng
Deep hashing has been widely applied to large-scale image retrieval by encoding high-dimensional data points into binary codes for efficient retrieval. Compared with pairwise/tripl…
Adversarial training for predictive tasks: theoretical analysis and limitations in the deterministic case
Thibault Lesieur, Jérémie Messud, Issa Hammoud +3
To train a deep neural network to mimic the outcomes of processing sequences, a version of Conditional Generalized Adversarial Network (CGAN) can be used. It has been observed by o…