Unverified50% confidenceFactExact time
UBA (Universal Budget Aware) learning rate decay relies on a fixed offline trajectory, anchored only to the iteration count, and cannot adjust dynamically based on the model's internal state, so it is essentially open-loop control.
1
Sources
50%
Confidence
Long-term
Relevance
10/27/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedStep decay lowers the learning rate by a fixed ratio (e.g., multiplying by 0.1) at preset iteration points; it is simple to implement and predictable in behavior, and is an open-loop, empirically driven schedule.69% similarUnverifiedWith the corrected score, the drift term in the expected gradient is completely cancelled, leaving only the covariance term (the learning signal).67% similarUnverifiedAdaGrad通过累积历史梯度平方实现自适应，但会导致学习率单调递减直至停止更新65% similarUnverifiedUnder a local quadratic model, a larger batch means fewer but longer update steps, with each step incurring a greater loss on curvature, resulting in a critical batch size that depends on the learning rate, beyond which sample efficiency declines.65% similarUnverified梯度下降的权重更新规则为 w = w - lr * gradient，其中lr是学习率65% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1102252API
curl https://kongchang.com/api/v1/knowledge/claims/1102252MCP
get_claim(id=1102252)