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4 papers · 1 filter
Recovery of Future Data via Convolution Nuclear Norm Minimization
Guangcan Liu, Wayne Zhang
This paper studies the problem of time series forecasting (TSF) from the perspective of compressed sensing. First of all, we convert TSF into a more inclusive problem called tensor…
Learning to Auto Weight: Entirely Data-driven and Highly Efficient Weighting Framework
Zhenmao Li, Yichao Wu, Ken Chen +4
Example weighting algorithm is an effective solution to the training bias problem, however, most previous typical methods are usually limited to human knowledge and require laborio…
Towards Understanding Regularization in Batch Normalization
Ping Luo, Xinjiang Wang, Wenqi Shao +1
Batch Normalization (BN) improves both convergence and generalization in training neural networks. This work understands these phenomena theoretically. We analyze BN by using a bas…
Deep Cocktail Network: Multi-source Unsupervised Domain Adaptation with Category Shift
Ruijia Xu, Ziliang Chen, Wangmeng Zuo +2
Unsupervised domain adaptation (UDA) conventionally assumes labeled source samples coming from a single underlying source distribution. Whereas in practical scenario, labeled data…