Unverified50% confidenceFactExact time
Under the assumption that the true mapping is uniformly random, the paper proves a lower bound on the error rate of E ≥ (M/N)δ*(B/M) + (1-M/N)(1-1/K).
1
Sources
50%
Confidence
Long-term
Relevance
9/14/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedThe relationship between the standard error of Monte Carlo estimation and the number of simulations N is that the standard error is proportional to 1/√N.72% similarUnverifiedLLM每次调用可建模为伯努利试验，N次调用通过次数服从二项分布B(N, p)，通过率95%置信区间约为p̂ ± 1.96×√(p̂(1-p̂)/N)70% similarUnverifiedThe error introduced by uniform quantization approximately follows a uniform distribution, with a variance of Δ²/12 (where Δ is the quantization step size).70% similarUnverifiedThe calculation of the margin of error derives from the central limit theorem, with the formula MOE = z × √(p(1-p)/n), where z is approximately 1.96 at the 95% confidence level.70% similarUnverifiedThe phrase "with probability at least 1-δ" in papers is standard language from PAC (Probably Approximately Correct) learning theory, meaning the error upper bound holds with probability at least 1-δ69% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/919747API
curl https://kongchang.com/api/v1/knowledge/claims/919747MCP
get_claim(id=919747)