69 citations · 179 across the 18 of their papers we have counts for
19 papers
Towards a Unified Theoretical Understanding of Non-contrastive Learning via Rank Differential Mechanism
Zhijian Zhuo, Yifei Wang, Jinwen Ma +1
Recently, a variety of methods under the name of non-contrastive learning (like BYOL, SimSiam, SwAV, DINO) show that when equipped with some asymmetric architectural designs, align…
PDO-s3DCNNs: Partial Differential Operator Based Steerable 3D CNNs
Zhengyang Shen, Tao Hong, Qi She +2
Steerable models can provide very general and flexible equivariance by formulating equivariance requirements in the language of representation theory and feature fields, which has…
Automatic Text Extractive Summarization Based on Graph and Pre-trained Language Model Attention
Yuan-Ching Lin, Jinwen Ma
Representing a text as a graph for obtaining automatic text summarization has been investigated for over ten years. With the development of attention or Transformer on natural lang…
ARGO: Modeling Heterogeneity in E-commerce Recommendation
Daqing Wu, Xiao Luo, Zeyu Ma +3
Nowadays, E-commerce is increasingly integrated into our daily lives. Meanwhile, shopping process has also changed incrementally from one behavior (purchase) to multiple behaviors…
Deep Unsupervised Hashing by Distilled Smooth Guidance
Xiao Luo, Zeyu Ma, Daqing Wu +4
Hashing has been widely used in approximate nearest neighbor search for its storage and computational efficiency. Deep supervised hashing methods are not widely used because of the…
Criterion-based Heterogeneous Collaborative Filtering for Multi-behavior Implicit Recommendation
Xiao Luo, Daqing Wu, Yiyang Gu +7
Recent years have witnessed the explosive growth of interaction behaviors in multimedia information systems, where multi-behavior recommender systems have received increasing atten…
PDO-eS2CNNs: Partial Differential Operator Based Equivariant Spherical CNNs
Zhengyang Shen, Tiancheng Shen, Zhouchen Lin +1
Spherical signals exist in many applications, e.g., planetary data, LiDAR scans and digitalization of 3D objects, calling for models that can process spherical data effectively. It…
PDO-eConvs: Partial Differential Operator Based Equivariant Convolutions
Zhengyang Shen, Lingshen He, Zhouchen Lin +1
Recent research has shown that incorporating equivariance into neural network architectures is very helpful, and there have been some works investigating the equivariance of networ…
Real-time Universal Style Transfer on High-resolution Images via Zero-channel Pruning
Jie An, Tao Li, Haozhi Huang +6
Extracting effective deep features to represent content and style information is the key to universal style transfer. Most existing algorithms use VGG19 as the feature extractor, w…
DefenseVGAE: Defending against Adversarial Attacks on Graph Data via a Variational Graph Autoencoder
Ao Zhang, Jinwen Ma
Graph neural networks (GNNs) achieve remarkable performance for tasks on graph data. However, recent works show they are extremely vulnerable to adversarial structural perturbation…
Multi-Label Classification with Label Graph Superimposing
Ya Wang, Dongliang He, Fu Li +4
Images or videos always contain multiple objects or actions. Multi-label recognition has been witnessed to achieve pretty performance attribute to the rapid development of deep lea…
Transformation of Dense and Sparse Text Representations
Wenpeng Hu, Mengyu Wang, Bing Liu +5
Sparsity is regarded as a desirable property of representations, especially in terms of explanation. However, its usage has been limited due to the gap with dense representations.…
Fast Universal Style Transfer for Artistic and Photorealistic Rendering
Jie An, Haoyi Xiong, Jiebo Luo +2
Universal style transfer is an image editing task that renders an input content image using the visual style of arbitrary reference images, including both artistic and photorealist…
StyleNAS: An Empirical Study of Neural Architecture Search to Uncover Surprisingly Fast End-to-End Universal Style Transfer Networks
Jie An, Haoyi Xiong, Jinwen Ma +2
Neural Architecture Search (NAS) has been widely studied for designing discriminative deep learning models such as image classification, object detection, and semantic segmentation…
GSN: A Graph-Structured Network for Multi-Party Dialogues
Wenpeng Hu, Zhangming Chan, Bing Liu +3
Existing neural models for dialogue response generation assume that utterances are sequentially organized. However, many real-world dialogues involve multiple interlocutors (i.e.,…
T-SVD Based Non-convex Tensor Completion and Robust Principal Component Analysis
Tao Li, Jinwen Ma
Tensor completion and robust principal component analysis have been widely used in machine learning while the key problem relies on the minimization of a tensor rank that is very c…
Spatial-Aware Non-Local Attention for Fashion Landmark Detection
Yixin Li, Shengqin Tang, Yun Ye +1
Fashion landmark detection is a challenging task even using the current deep learning techniques, due to the large variation and non-rigid deformation of clothes. In order to tackl…
ELEGANT: Exchanging Latent Encodings with GAN for Transferring Multiple Face Attributes
Taihong Xiao, Jiapeng Hong, Jinwen Ma
Recent studies on face attribute transfer have achieved great success. A lot of models are able to transfer face attributes with an input image. However, they suffer from three lim…
DNA-GAN: Learning Disentangled Representations from Multi-Attribute Images
Taihong Xiao, Jiapeng Hong, Jinwen Ma
Disentangling factors of variation has become a very challenging problem on representation learning. Existing algorithms suffer from many limitations, such as unpredictable disenta…