The success of a learning algorithm depends on its ability to balance between fitting the data and avoiding overfitting.
学习算法的成功取决于其在拟合数据和避免过拟合之间取得平衡的能力。
自守表示的研究是进入对称性核心的旅程。
"Every setback is a setup for a comeback."
我们相信创新的力量能够驱动可持续增长。