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Speaker: Mr. Junchi Yang From: ETH Zurich Abstract Machine learning applications have brought about new optimization challenges, particularly in the area of trustworthy machine learning, which requires game-theoretical formulations to seek equilibrium. Furthermore, these large-scale problems demand adaptive methods such as Adam and AdaGrad to adjust step sizes without granular knowledge of the loss functions. In this talk, I will …
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