43 citations · 60 across the 16 of their papers we have counts for
16 papers
DFRD: Data-Free Robustness Distillation for Heterogeneous Federated Learning
Kangyang Luo, Shuai Wang, Yexuan Fu +3
Federated Learning (FL) is a privacy-constrained decentralized machine learning paradigm in which clients enable collaborative training without compromising private data. However,…
Shapley Value on Probabilistic Classifiers
Xiang Li, Haocheng Xia, Jinfei Liu
Data valuation has become an increasingly significant discipline in data science due to the economic value of data. In the context of machine learning (ML), data valuation methods…
Statistical Analysis of Karcher Means for Random Restricted PSD Matrices
Hengchao Chen, Xiang Li, Qiang Sun
Non-asymptotic statistical analysis is often missing for modern geometry-aware machine learning algorithms due to the possibly intricate non-linear manifold structure. This paper s…
Meta-Learning Siamese Network for Few-Shot Text Classification
Chengcheng Han, Yuhe Wang, Yingnan Fu +4
Few-shot learning has been used to tackle the problem of label scarcity in text classification, of which meta-learning based methods have shown to be effective, such as the prototy…
GradMA: A Gradient-Memory-based Accelerated Federated Learning with Alleviated Catastrophic Forgetting
Kangyang Luo, Xiang Li, Yunshi Lan +1
Federated Learning (FL) has emerged as a de facto machine learning area and received rapid increasing research interests from the community. However, catastrophic forgetting caused…
Digital staining in optical microscopy using deep learning -- a review
Lucas Kreiss, Shaowei Jiang, Xiang Li +13
Until recently, conventional biochemical staining had the undisputed status as well-established benchmark for most biomedical problems related to clinical diagnostics, fundamental…
Pushing One Pair of Labels Apart Each Time in Multi-Label Learning: From Single Positive to Full Labels
Xiang Li, Xinrui Wang, Songcan Chen
In Multi-Label Learning (MLL), it is extremely challenging to accurately annotate every appearing object due to expensive costs and limited knowledge. When facing such a challenge,…
MM-SFENet: Multi-scale Multi-task Localization and Classification of Bladder Cancer in MRI with Spatial Feature Encoder Network
Yu Ren, Guoli Wang, Pingping Wang +5
Background and Objective: Bladder cancer is a common malignant urinary carcinoma, with muscle-invasive and non-muscle-invasive as its two major subtypes. This paper aims to achieve…
HopFIR: Hop-wise GraphFormer with Intragroup Joint Refinement for 3D Human Pose Estimation
Kai Zhai, Qiang Nie, Bo Ouyang +2
2D-to-3D human pose lifting is fundamental for 3D human pose estimation (HPE), for which graph convolutional networks (GCNs) have proven inherently suitable for modeling the human…
DINF: Dynamic Instance Noise Filter for Occluded Pedestrian Detection
Li Xiang, He Miao, Luo Haibo +1
Occlusion issue is the biggest challenge in pedestrian detection. RCNN-based detectors extract instance features by cropping rectangle regions of interest in the feature maps. Howe…
Panoramic Video Salient Object Detection with Ambisonic Audio Guidance
Xiang Li, Haoyuan Cao, Shijie Zhao +3
Video salient object detection (VSOD), as a fundamental computer vision problem, has been extensively discussed in the last decade. However, all existing works focus on addressing…
Disentangled and Robust Representation Learning for Bragging Classification in Social Media
Xiang Li, Yucheng Zhou
Researching bragging behavior on social media arouses interest of computational (socio) linguists. However, existing bragging classification datasets suffer from a serious data imb…
Ranking-Enhanced Unsupervised Sentence Representation Learning
Yeon Seonwoo, Guoyin Wang, Changmin Seo +6
Unsupervised sentence representation learning has progressed through contrastive learning and data augmentation methods such as dropout masking. Despite this progress, sentence enc…
AutoFAS: Automatic Feature and Architecture Selection for Pre-Ranking System
Xiang Li, Xiaojiang Zhou, Yao Xiao +4
Industrial search and recommendation systems mostly follow the classic multi-stage information retrieval paradigm: matching, pre-ranking, ranking, and re-ranking stages. To account…
Online Speaker Diarization with Relation Network
Xiang Li, Yucheng Zhao, Chong Luo +1
In this paper, we propose an online speaker diarization system based on Relation Network, named RenoSD. Unlike conventional diariztion systems which consist of several independentl…
Spectral-change enhancement with prior SNR for the hearing impaired
Xiang Li, Xin Tian, Henry Luo +4
A previous signal processing algorithm that aimed to enhance spectral changes (SCE) over time showed benefit for hearing-impaired (HI) listeners to recognize speech in background n…