159 citations · 739 across the 19 of their papers we have counts for
19 papers
Transition Role of Entangled Data in Quantum Machine Learning
Xinbiao Wang, Yuxuan Du, Zhuozhuo Tu +3
Entanglement serves as the resource to empower quantum computing. Recent progress has highlighted its positive impact on learning quantum dynamics, wherein the integration of entan…
Not All Instances Contribute Equally: Instance-adaptive Class Representation Learning for Few-Shot Visual Recognition
Mengya Han, Yibing Zhan, Yong Luo +4
Few-shot visual recognition refers to recognize novel visual concepts from a few labeled instances. Many few-shot visual recognition methods adopt the metric-based meta-learning pa…
Symmetric Pruning in Quantum Neural Networks
Xinbiao Wang, Junyu Liu, Tongliang Liu +3
Many fundamental properties of a quantum system are captured by its Hamiltonian and ground state. Despite the significance of ground states preparation (GSP), this task is classica…
ModelPS: An Interactive and Collaborative Platform for Editing Pre-trained Models at Scale
Yuanming Li, Huaizheng Zhang, Shanshan Jiang +3
AI engineering has emerged as a crucial discipline to democratize deep neural network (DNN) models among software developers with a diverse background. In particular, altering thes…
Towards understanding the power of quantum kernels in the NISQ era
Xinbiao Wang, Yuxuan Du, Yong Luo +1
A key problem in the field of quantum computing is understanding whether quantum machine learning (QML) models implemented on noisy intermediate-scale quantum (NISQ) machines can a…
A Serverless Cloud-Fog Platform for DNN-Based Video Analytics with Incremental Learning
Huaizheng Zhang, Meng Shen, Yizheng Huang +4
DNN-based video analytics have empowered many new applications (e.g., automated retail). Meanwhile, the proliferation of fog devices provides developers with more design options to…
Hysia: Serving DNN-Based Video-to-Retail Applications in Cloud
Huaizheng Zhang, Yuanming Li, Qiming Ai +4
Combining \underline{v}ideo streaming and online \underline{r}etailing (V2R) has been a growing trend recently. In this paper, we provide practitioners and researchers in multimedi…
Look, Read and Feel: Benchmarking Ads Understanding with Multimodal Multitask Learning
Huaizheng Zhang, Yong Luo, Qiming Ai +1
Given the massive market of advertising and the sharply increasing online multimedia content (such as videos), it is now fashionable to promote advertisements (ads) together with t…
Towards Digital Retina in Smart Cities: A Model Generation, Utilization and Communication Paradigm
Yihang Lou, Ling-Yu Duan, Yong Luo +4
The digital retina in smart cities is to select what the City Eye tells the City Brain, and convert the acquired visual data from front-end visual sensors to features in an intelli…
Large Margin Multi-modal Multi-task Feature Extraction for Image Classification
Yong Luo, Yonggang Wen, Dacheng Tao +2
The features used in many image analysis-based applications are frequently of very high dimension. Feature extraction offers several advantages in high-dimensional cases, and many…
Heterogeneous Multi-task Metric Learning across Multiple Domains
Yong Luo, Yonggang Wen, Dacheng Tao
Distance metric learning (DML) plays a crucial role in diverse machine learning algorithms and applications. When the labeled information in target domain is limited, transfer metr…
Transferring Knowledge Fragments for Learning Distance Metric from A Heterogeneous Domain
Yong Luo, Yonggang Wen, Tongliang Liu +1
The goal of transfer learning is to improve the performance of target learning task by leveraging information (or transferring knowledge) from other related tasks. In this paper, w…
Multi-view Vector-valued Manifold Regularization for Multi-label Image Classification
Yong Luo, Dacheng Tao, Chang Xu +3
In computer vision, image datasets used for classification are naturally associated with multiple labels and comprised of multiple views, because each image may contain several obj…
Multi-View Matrix Completion for Multi-Label Image Classification
Yong Luo, Tongliang Liu, Dacheng Tao +1
There is growing interest in multi-label image classification due to its critical role in web-based image analytics-based applications, such as large-scale image retrieval and brow…
Decomposition-Based Transfer Distance Metric Learning for Image Classification
Yong Luo, Tongliang Liu, Dacheng Tao +1
Distance metric learning (DML) is a critical factor for image analysis and pattern recognition. To learn a robust distance metric for a target task, we need abundant side informati…
Cost-Sensitive Feature Selection by Optimizing F-Measures
Meng Liu, Chang Xu, Yong Luo +3
Feature selection is beneficial for improving the performance of general machine learning tasks by extracting an informative subset from the high-dimensional features. Conventional…
Transfer Metric Learning: Algorithms, Applications and Outlooks
Yong Luo, Yonggang Wen, Ling-Yu Duan +1
Distance metric learning (DML) aims to find an appropriate way to reveal the underlying data relationship. It is critical in many machine learning, pattern recognition and data min…
ResumeNet: A Learning-based Framework for Automatic Resume Quality Assessment
Yong Luo, Huaizheng Zhang, Yongjie Wang +2
Recruitment of appropriate people for certain positions is critical for any companies or organizations. Manually screening to select appropriate candidates from large amounts of re…
Tensor Canonical Correlation Analysis for Multi-view Dimension Reduction
Yong Luo, Dacheng Tao, Yonggang Wen +2
Canonical correlation analysis (CCA) has proven an effective tool for two-view dimension reduction due to its profound theoretical foundation and success in practical applications.…