Unverified50% confidenceFactExact time
Even under exactly the same smoothness assumptions on the treatment effect function and the nuisance function, a rough covariate design leads to slower pointwise convergence rates for CATE estimation than a uniform design.
1
Sources
50%
Confidence
Long-term
Relevance
10/14/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedThe core conclusion of this study is: the covariate distribution alone being insufficiently smooth is enough to slow down the convergence rate of pointwise CATE estimation, without the treatment effect function or the nuisance function needing to become rougher.79% similarUnverifiedThe magnitude of the spectral truncation error is jointly determined by the Sobolev smoothness of the function and the truncation order; the smoother the function, the faster the high-frequency decay and the smaller the truncation error.76% similarUnverifiedWhen prior knowledge about possible fault patterns is available, selecting a sparse penalty structure that matches them often yields significant performance gains over general-purpose algorithms75% similarUnverifiedNumerical experiments show that when handling non-smooth and heavy-tailed target distributions, the non-reversible versions exhibit faster sampling efficiency compared to their reversible counterparts.75% similarUnverifiedThe choice of rank r is a trade-off between accuracy and efficiency: the smaller the r, the higher the compression ratio but the larger the approximation error.73% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1026620API
curl https://kongchang.com/api/v1/knowledge/claims/1026620MCP
get_claim(id=1026620)