1 citations · 1 across the 17 of their papers we have counts for
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OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving
Chenyi Li, Yanchen Nie, Zhenyu Ming +3
Recent advances in formal theorem proving have focused on Olympiad-level mathematics, leaving undergraduate domains largely unexplored. Optimization, fundamental to machine learnin…
Learning to Solve the Quadratic Assignment Problem with Warm-Started MCMC Finetuning
Yicheng Pan, Ruisong Zhou, Haijun Zou +2
The quadratic assignment problem (QAP) is a fundamental NP-hard task that poses significant challenges for both traditional heuristics and modern learning-based solvers. Existing Q…
A Learning Method with Gap-Aware Generation for Heterogeneous DAG Scheduling
Ruisong Zhou, Haijun Zou, Li Zhou +2
Efficient scheduling of directed acyclic graphs (DAGs) is a core problem in large-scale data-intensive computing systems, where query plans, data-processing workloads, and computat…
Accelerating Optimization via Differentiable Stopping Time
Zhonglin Xie, Yiman Fong, Haoran Yuan +1
Optimization is an important module of modern machine learning applications. Tremendous efforts have been made to accelerate optimization algorithms. A common formulation is achiev…