Unverified50% confidenceFactExact time
The SelectPFN research team developed Bayesian regret bounds for amortized selection, quantifying the gap between amortized inference and ideal Bayesian inference for the amortized median probability model.
1
Sources
50%
Confidence
Long-term
Relevance
10/16/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedMost existing approaches rely on heuristic criteria to construct preference pairs, such as likelihood-based extremes that pick the samples the model assigns the highest and lowest probability as positive and negative examples.71% similarUnverified优先经验回放（PER）由Schaul等人于2015年提出，采样概率正比于TD误差绝对值加小常数，并用重要性采样权重修正分布偏移68% similarUnverifiedFitting the propensity score in-sample induces dependence among individual contributions, so variance estimators derived under the i.i.d. assumption underestimate the true uncertainty.66% similarUnverifiedThe expected cost of a decision depends not only on the probability that the model makes an incorrect judgment, but also on the actual consequences when an error occurs.66% similarUnverified在8个模型均随机猜测的假设下，单次二元预测中至少有一个押中的概率约99.6%66% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1042164API
curl https://kongchang.com/api/v1/knowledge/claims/1042164MCP
get_claim(id=1042164)