activity
20242026
collaborators

12 papers

math.PR2026

The Berry--Esseen Bound is Sharp for All Sufficiently Large Sample Sizes

Hengzhi He, Guang Cheng

We prove that the Esseen's constant is sharp in the iid Berry--Esseen inequality as long as the sample sizes . The threshold is universal over all real summ…

math.ST2026

Tensor-normal maximum likelihood estimation at the operator-norm sample threshold

Hengzhi He, Guang Cheng

Let be independent Gaussian tensors in with a common covariance matrix given by the Kronecker product of

math.ST2026

Sharp proper estimation of fixed-component Gaussian location mixtures in polynomial time

Hengzhi He, Guang Cheng

We consider a mixture of at most unit-covariance Gaussians in whose means belong to a fixed-radius ball, with no separation or minimum-weight condition. Doss, Wu…

cs.LG2026

Let the Target Select for Itself: Data Selection via Target-Aligned Paths

Huitao Yang, Hengzhi He, Guang Cheng

Targeted data selection aims to identify training samples from a large candidate pool that improve performance on a specific downstream task. Many recent methods estimate candidate…

cs.CR2026

Authenticated Contradictions from Desynchronized Provenance and Watermarking

Alexander Nemecek, Hengzhi He, Guang Cheng +1

Cryptographic provenance standards such as C2PA and invisible watermarking are positioned as complementary defenses for content authentication, yet the two verification layers are…

cs.AI2026

Enhancing Table Reasoning with Deterministic Table-State Rewards

Tung Sum Thomas Kwok, Xinyu Wang, Hengzhi He +9

Large Language Models (LLMs) struggle with multi-step reasoning over structured tables. The primary reason is the lack of explicit supervision for intermediate reasoning states. Ex…