23 citations · 71 across the 20 of their papers we have counts for
8 papers · 1 filter
A K-variate Time Series Is Worth K Words: Evolution of the Vanilla Transformer Architecture for Long-term Multivariate Time Series Forecasting
Zanwei Zhou, Ruizhe Zhong, Chen Yang +3
Multivariate time series forecasting (MTSF) is a fundamental problem in numerous real-world applications. Recently, Transformer has become the de facto solution for MTSF, especiall…
Adv-Attribute: Inconspicuous and Transferable Adversarial Attack on Face Recognition
Shuai Jia, Bangjie Yin, Taiping Yao +4
Deep learning models have shown their vulnerability when dealing with adversarial attacks. Existing attacks almost perform on low-level instances, such as pixels and super-pixels,…
A Survey on Label-efficient Deep Image Segmentation: Bridging the Gap between Weak Supervision and Dense Prediction
Wei Shen, Zelin Peng, Xuehui Wang +6
The rapid development of deep learning has made a great progress in image segmentation, one of the fundamental tasks of computer vision. However, the current segmentation algorithm…
DOTIN: Dropping Task-Irrelevant Nodes for GNNs
Shaofeng Zhang, Feng Zhu, Junchi Yan +2
Scalability is an important consideration for deep graph neural networks. Inspired by the conventional pooling layers in CNNs, many recent graph learning approaches have introduced…
Continual Predictive Learning from Videos
Geng Chen, Wendong Zhang, Han Lu +4
Predictive learning ideally builds the world model of physical processes in one or more given environments. Typical setups assume that we can collect data from all environments at…
Exploring Frequency Adversarial Attacks for Face Forgery Detection
Shuai Jia, Chao Ma, Taiping Yao +3
Various facial manipulation techniques have drawn serious public concerns in morality, security, and privacy. Although existing face forgery classifiers achieve promising performan…
EAutoDet: Efficient Architecture Search for Object Detection
Xiaoxing Wang, Jiale Lin, Junchi Yan +2
Training CNN for detection is time-consuming due to the large dataset and complex network modules, making it hard to search architectures on detection datasets directly, which usua…
A General Framework for Evaluating Robustness of Combinatorial Optimization Solvers on Graphs
Han Lu, Zenan Li, Runzhong Wang +3
Solving combinatorial optimization (CO) on graphs is among the fundamental tasks for upper-stream applications in data mining, machine learning and operations research. Despite the…