Regression is typically treated as a curve-fitting process where the goal is to fit a prediction function to data.With the help of conditional generative adversarial networks, we propose to solve this age-old p
Learning curves of Gaussian process regression with power-law priors and targets 2923 21:00 Backdoor Defense via Decoupling the Training Process 2850 08:00 Table Pre-training via Learning a Neural SQL EXecutor 2833 17:00 Better Supervisory Signals by Observing Learning Paths -- 标签越好,泛化越好 ...
Pleiss, G., Souza, A., Kim, J., Li, B., & Weinberger, K. Q. (2019).Neural network out-of-distribution detection for regression tasks. Polatkan, G., Jafarpour, S., Brasoveanu, A., Hughes, S., & Daubechies, I. (2009). Detection of forgery in paintings using supervised learning...
Ridge regression, hubness, and zero-shot learning. In Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases, Porto, Portugal, 7–11 September 2015; Springer: Cham, Switzerland, 2015; pp. 135–151. [Google Scholar] Zhang, L.; Xiang, T.; Gong...