Communications in Computer & Information ScienceB.H.Sheng, P.X.Ye, "Fully online regularized classification algorithm with strongly convex loss," High Performance Networking, Computing, and Communication Systems Communications in Computer and Information Science, vol.163, pp.223-228, 2011.
especially when data is polluted with noisy labels. To date, various data stream mining algorithms have been proposed and extensively used in many real-world applications. Considering the functional complementation of classical online learning algorithms and with the goal...
We also train with several compute-efficient algorithms common to continual learning: online elastic weight consolidation (EWC++)53, which is a kind of regularized SGD, and episodic recall (ER)40, which uses a small buffer to store a mini-batch of previously observed data points and SGD to ...
Subsequently, the most imperative features over all sub-bands are selected and un-regularized linear discriminant analysis is employed for classification of multiple motor imagery tasks. Results Publicly available dataset (BCI Competition IV Dataset I) is used to validate the proposed method i.e. FB...
[Tsuruoka, Y., Tsujii, J., and Ananiadou, S., 2009] Stochastic gradient descent training for l1-regularized log-linear models with cumulative penalty. In Proceedings of the AFNLP/ACL '09. [Zhang, T., 2004] Solving large scale linear prediction problems using stochastic gradient descent algori...
Learning spatial-temporal regularized correlation filters for visual tracking. in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 4904–4913. https://doi.org/10.1109/CVPR.2018. 00515 (2018). 21. Hu, Z., Zou, M., Chen, C. & Wu, ...
The distillation loss function is fed back to the student network to optimize its parameters, enabling the student network to learn knowledge from the teacher network through regularized training, ultimately enhancing the performance of the student network. ...
Classification Baseline methods BAH (Buy And Hold) Best (Best stock strategy) CRP (Constant Rebalanced Portfolio) Follow the winner UP (Universal Portfolios) EG (Exponentiated Gradient) Follow the leader Follow the regularized leader AA (Aggregating-type Algorithms) Follow the loser ANTICOR (Anti-Co...
Learning spatial-temporal regularized correlation filters for visual tracking. in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 4904–4913. https://doi.org/10.1109/CVPR.2018. 00515 (2018). 21. Hu, Z., Zou, M., Chen, C. & Wu, ...
Finally, all the feature nodes and enhancement nodes, collectively known as the broad feature matrix, are connected to the output layer, with the connection weights usually determined by solving a regularized least squares problem. Compared to conventional deep learning models, BLS presents notable ...