Such a weak generalization capability hinders the applicability of current deepfake detectors.

Meanwhile, we show that to achieve OppolypS,A,Hq?

Deep neural networks have achieved impressive performance in many areas. Designing a fast and provable method for training neural networks is a fundamental question in machine learning. The classical training method requires paying Ω(mnd) cost for both forward computation and backward computation, where m is the width of the neural network, and we are given n training points in d-dimensional space.

Perhaps surprisingly, when the stepsizes are constant, simply averaging over the local iterates via the mixing matrix only converges to a neighborhood of the optimum [47,58].

MIRcontains25uniquelabels,andweremoved the label "night" as it is not in the label set of any MLAPIs. For each instance in those datasets, we have evaluated the prediction from the mainstream ML APIs from 2020 to 2022. HAPI was collected from 2020 to 2022. For classification tasks, the predictions/annotations of each API were collected in the spring of 2020, 2021, and 2022. Theoriginal IMDB dataset hasbeenpartitioned into training and testing splits, and thus we used its testing split, including 25,000 textparagraphs.