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左：极速extreme，右：超极速extreme Pro. 除了连续写入速度外，各项分数基本上可以认为一模一样，无论是连续传输速度（第一行）还是4K速度（第二、三行）还是各项得分，基本上没有区别；看写入速度的话，还是Pro（超极速更快一些）。
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29 Αυγ 2018 · We show that this algorithm can fail when the geometries of known and unknown classes differ. To overcome this problem, we propose two new algorithms relying on approximations from extreme value theory. We show the effectiveness of our classifiers in simulations and on the LETTER and MNIST data sets. READ FULL TEXT
24 Οκτ 2018 · 独立GPU：P1是移动工作站定位，因此在独显上会配备NVIDIA Quadro专业作图系列的显卡，X1 Extreme全系列标配NVIDIA GTX1050Ti with Max-Q design的独显，4G显存; 外观：X1 Extreme隶属于X1产品家族序列，因此在A面边角处会印有“X1”的logo，但P1上面没有。
9 Ιαν 2021 · Through these networks, negative labels are sampled dynamically during label ranking part training by feeding with the same text representation. Extensive experiments show that LightXML outperforms state-of-the-art methods in five extreme multi-label datasets with much smaller model size and lower computational complexity.
4 Δεκ 2021 · To this end, we present a new dataset of edges. Second, we propose a novel architecture, termed Dense Extreme Inception Network for Edge Detection (DexiNed), that can be trained from scratch without any pre-trained weights. DexiNed outperforms other algorithms in the presented dataset.
14 Μαΐ 2022 · The framework is effective, but it easily suffers from overfitting noisy data and lacks uncertainty quantification for the solution under noise scenarios.To this end, we develop the Bayesian physics-informed extreme learning machine (BPIELM) to solve both forward and inverse linear PDE problems with noisy data in a unified framework.
30 Ιαν 2022 · We propose a method for extreme quantile regression that combines the flexibility of random forests with the theory of extrapolation. Our extremal random forest (ERF) estimates the parameters of a generalized Pareto distribution, conditional on the predictor vector , by maximizing a local likelihood with weights extracted from a quantile random forest.
