Author

Pingchuan Ma

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#artificial intelligence Preprint Sep 2026

Demistifying Data and Simulator Assumptions in Supervised Causal Discovery

Supervised causal discovery learns to infer causal structure for a new dataset from training datasets paired with structural labels. These training pairs are typically simulated, making the simulator both a source of supervision and a carrier of assumptions about causal graphs, mechanisms, and noise. Understanding the...

Pingchuan Ma, Rui Ding, Bojun Huang et al. · 0 citations

Book Open access Aug 2026

One Rounding Fits All: Memory-Efficient Approximation Algorithms for Partition-Constrained Influence Maximization

RBwA, a memory-efficient and sample-efficient progressive sampling algorithm for IM-PC and a memory-efficient rounding scheme called BwARound for coverage maximization subroutines, which only requires storing one fractional vector and takes maximal feasible steps rather than tiny ε-increments, are proposed.

Qixin Zhang, Qirun Zeng, Hui Lu et al. · Proceedings of the 32nd ACM... · 0 citations