Unverified50% confidenceFactExact time
Mini-batch gradient descent is a compromise between batch and stochastic gradient descent, and is also the most commonly used approach in deep learning frameworks.
1
Sources
50%
Confidence
Long-term
Relevance
9/11/2026
First Seen
Sources
Related Entities
Related Claims
VerifiedGradient descent is the most fundamental optimization algorithm in machine learning; a learning rate that is too large causes oscillation, while one that is too small results in slow convergence.79% similarUnverified批量梯度下降使用全部训练数据计算梯度，随机梯度下降每次只用一个样本，小批量梯度下降在两者之间取得平衡76% similarUnverified梯度学习的核心是连续优化，神经网络参数空间是高维实数空间，损失函数近似可微75% similarVerifiedGradient descent has spawned three main variants — batch gradient descent, stochastic gradient descent, and mini-batch gradient descent — and the Adam optimizer is a combined improvement built on momentum and adaptive learning rates.74% similarUnverified梯度下降的收敛条件与学习率和损失函数的Lipschitz常数的关系有关74% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/901609API
curl https://kongchang.com/api/v1/knowledge/claims/901609MCP
get_claim(id=901609)