IEEE TNNLS

Compete to Win: Enhancing Pseudo Labels for Barely-supervised Medical Image Segmentation

Huimin Wu, Xiaomeng Li, Yiqun Lin, Kwang-Ting Cheng

Comments Accepted by TMI (in IEEE Transactions on Neural Networks and Learning Systems). Code available at https://github.com/Huiimin5/comwin

PSAQ-ViT V2: Towards Accurate and General Data-Free Quantization for Vision Transformers

Zhikai Li, Mengjuan Chen, Junrui Xiao, Qingyi Gu

Comments Accepted by TNNLS 2023

Exploring Feature Representation Learning for Semi-supervised Medical Image Segmentation

Huimin Wu, Xiaomeng Li, Kwang-Ting Cheng

Comments Accepted by TNNLS (IEEE Transactions on Neural Networks and Learning Systems). Code available at: https://github.com/Huiimin5/AUA

XTQA: Span-Level Explanations of the Textbook Question Answering

Jie Ma, Qi Chai, Jun Liu, Qingyu Yin, Pinghui Wang, Qinghua Zheng

Comments Accepted by IEEE TNNLS

Perceptron Theory Can Predict the Accuracy of Neural Networks

Denis Kleyko, Antonello Rosato, E. Paxon Frady, Massimo Panella, Friedrich T. Sommer

Comments 16 pages, 14 figures

Journal ref IEEE Transactions on Neural Networks and Learning Systems (2023)

Boosting Zero-shot Learning via Contrastive Optimization of Attribute Representations

Yu Du, Miaojing Shi, Fangyun Wei, Guoqi Li

Comments Accepted to TNNLS

A Practical Contrastive Learning Framework for Single-Image Super-Resolution

Gang Wu, Junjun Jiang, Xianming Liu

Comments Accepted by IEEE Transactions on Neural Networks and Learning Systems

Efficient Bayesian Policy Reuse with a Scalable Observation Model in Deep Reinforcement Learning

Jinmei Liu, Zhi Wang, Chunlin Chen, Daoyi Dong

Comments Published in IEEE Transactions on Neural Networks and Learning Systems, 2023, DOI: 10.1109/TNNLS.2023.3281604

MetaFed: Federated Learning among Federations with Cyclic Knowledge Distillation for Personalized Healthcare

Yiqiang Chen, Wang Lu, Xin Qin, Jindong Wang, Xing Xie

Comments Accepted by IEEE Trans. on Neural Networks and Learning Systems (TNNLS); IJCAI'22 FTL workshop innovation award; code at https://github.com/microsoft/PersonalizedFL

Self-Supervised Time Series Representation Learning via Cross Reconstruction Transformer

Wenrui Zhang, Ling Yang, Shijia Geng, Shenda Hong

Comments Accepted by IEEE Transactions on Neural Networks and Learning Systems (TNNLS)

A Survey on Hyperlink Prediction

Can Chen, Yang-Yu Liu

Comments 15 pages, 4 figures, 6 tables

Journal ref IEEE Transactions on Neural Networks and Learning Systems, 2023

Graph-Ensemble Learning Model for Multi-label Skin Lesion Classification using Dermoscopy and Clinical Images

Peng Tang, Yang Nan, Tobias Lasser

Comments Submitted to TNNLS in 1st July 2023

SALR: Sharpness-aware Learning Rate Scheduler for Improved Generalization

Xubo Yue, Maher Nouiehed, Raed Al Kontar

Journal ref IEEE Transactions on Neural Networks and Learning Systems, 2023

Advancing Adversarial Training by Injecting Booster Signal

Hong Joo Lee, Youngjoon Yu, Yong Man Ro

Comments Accepted at IEEE Transactions on Neural Networks and Learning Systems

The Double Helix inside the NLP Transformer

Jason H. J. Lu, Qingzhen Guo

Comments Submitted to IEEE Transactions on Neural Networks and Learning Systems 21-Jun-2023. 12 pages, 14 figures

Hyperparameter Learning under Data Poisoning: Analysis of the Influence of Regularization via Multiobjective Bilevel Optimization

Javier Carnerero-Cano, Luis Muñoz-González, Phillippa Spencer, Emil C. Lupu

Comments Accepted to IEEE Transactions on Neural Networks and Learning Systems. arXiv admin note: text overlap with arXiv:2003.00040

Structure-Aware DropEdge Towards Deep Graph Convolutional Networks

Jiaqi Han, Wenbing Huang, Yu Rong, Tingyang Xu, Fuchun Sun, Junzhou Huang

Comments IEEE Transactions on Neural Networks and Learning Systems, 2023

A New Simple Stochastic Gradient Descent Type Algorithm With Lower Computational Complexity for Bilevel Optimization

Haimei Huo, Risheng Liu, Zhixun Su

Comments submitted to TNNLS; in the second round of review

Kernel Proposal Network for Arbitrary Shape Text Detection

Shi-Xue Zhang, Xiaobin Zhu, Jie-Bo Hou, Chun Yang, Xu-Cheng Yin

Comments This paper was completed in 2020-11.It was first submitted to CVPR 2021 and then ICCV 2021. Finally, it has been accepted by TNNLS in 2022-02 after major revision. Here, I thank Dr.Hou for his important contributions

Visually-Guided Sound Source Separation with Audio-Visual Predictive Coding

Zengjie Song, Zhaoxiang Zhang

Comments Accepted to IEEE Transactions on Neural Networks and Learning Systems (T-NNLS)

Description-Enhanced Label Embedding Contrastive Learning for Text Classification

Kun Zhang, Le Wu, Guangyi Lv, Enhong Chen, Shulan Ruan, Jing Liu, Zhiqiang Zhang, Jun Zhou, Meng Wang

Comments This paper has been accepted by IEEE Transactions on Neural Networks and Learning Systems

A Survey on Reinforcement Learning for Recommender Systems

Yuanguo Lin, Yong Liu, Fan Lin, Lixin Zou, Pengcheng Wu, Wenhua Zeng, Huanhuan Chen, Chunyan Miao

Comments 21 pages, 4 figures, Accepted by TNNLS 2023

Deep Active Learning with Structured Neural Depth Search

Xiaoyun Zhang, Xieyi Ping, Jianwei Zhang

Comments 10 pages, 8 figures, prepare for TNNLS

Learning Constrained Dynamic Correlations in Spatiotemporal Graphs for Motion Prediction

Jiajun Fu, Fuxing Yang, Yonghao Dang, Xiaoli Liu, Jianqin Yin

Comments Accepted by TNNLS. Codes are available at https://github.com/Jaakk0F/DSTD-GCN

Taming Self-Supervised Learning for Presentation Attack Detection: De-Folding and De-Mixing

Zhe Kong, Wentian Zhang, Feng Liu, Wenhan Luo, Haozhe Liu, Linlin Shen, Raghavendra Ramachandra

Comments Accepted by IEEE Transactions on Neural Networks and Learning Systems (TNNLS)

Fast Yet Effective Machine Unlearning

Ayush K Tarun, Vikram S Chundawat, Murari Mandal, Mohan Kankanhalli

Comments Accepted in IEEE Transactions on Neural Networks and Learning Systems

AD-NEV: A Scalable Multi-level Neuroevolution Framework for Multivariate Anomaly Detection

Marcin Pietron, Dominik Zurek, Kamil Faber, Roberto Corizzo

Comments submitted to IEEE TNNLS

Dynamics-Adaptive Continual Reinforcement Learning via Progressive Contextualization

Tiantian Zhang, Zichuan Lin, Yuxing Wang, Deheng Ye, Qiang Fu, Wei Yang, Xueqian Wang, Bin Liang, Bo Yuan, Xiu Li

Comments Accepted by IEEE Transactions on Neural Networks and Learning Systems, 2023

Lightweight Self-Knowledge Distillation with Multi-source Information Fusion

Xucong Wang, Pengchao Han, Lei Guo

Comments Submitted to IEEE TNNLS

On Low Rank Directed Acyclic Graphs and Causal Structure Learning

Zhuangyan Fang, Shengyu Zhu, Jiji Zhang, Yue Liu, Zhitang Chen, Yangbo He

Comments This paper has been accepted by the IEEE Transactions on Neural Networks and Learning Systems