Unverified50% confidenceFactExact time
The tail decay of a Gaussian distribution is exponential, so extreme values are almost entirely unexpected.
1
Sources
50%
Confidence
Long-term
Relevance
8/31/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedResearch by Gunasekar et al. in 2017 proved that for linear models, gradient descent is equivalent to minimum-norm interpolation.65% similarUnverified当预测的前景像素数量很少或几乎为零时，Dice损失分母接近于零，导致损失值和梯度都可能出现剧烈震荡61% similarUnverified自回归缩放定律的边际收益正在递减，单纯增加模型规模和数据量带来的提升已微乎其微61% similarUnverified线性回归的最小二乘损失与逻辑回归的交叉熵损失分别对应高斯噪声假设与伯努利分布假设下的最大似然估计61% similarUnverifiedSigmoid函数的导数最大值仅为0.25，经过数十层连乘后梯度会指数级衰减61% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/827863API
curl https://kongchang.com/api/v1/knowledge/claims/827863MCP
get_claim(id=827863)