Y Li, J Guo, R Wang, J Yan - Advances in Neural …, 2024 - proceedings.neurips.cc
Extensive experiments have gradually revealed the potential performance bottleneck of modeling Combinatorial Optimization (CO) solving as neural solution prediction tasks. The …
Z Geng, J Wang, Z Liu, S Xu, Z Tang… - … on Machine Learning, 2024 - openreview.net
Macro placement is a crucial step in modern chip design, and reinforcement learning (RL) has recently emerged as a promising technique for improving the placement quality …
X Chen, Y Li, R Wang, J Yan - The Twelfth International Conference …, 2024 - openreview.net
The Boolean satisfiability problem (SAT) stands as a canonical NP-complete task. In particular, the scarcity of real-world SAT instances and their usefulness for tuning SAT …
X Li, F Zhu, HL Zhen, W Luo, M Lu, Y Huang… - arXiv preprint arXiv …, 2024 - arxiv.org
In an era of digital ubiquity, efficient resource management and decision-making are paramount across numerous industries. To this end, we present a comprehensive study on …
Learning neural operators for solving partial differential equations (PDEs) has attracted great attention due to its high inference efficiency. However, training such operators requires …
Logic Synthesis (LS) plays a vital role in chip design--a cornerstone of the semiconductor industry. A key task in LS is to transform circuits--modeled by directed acyclic graphs (DAGs) …
A Xu, Z Hu, X Li, R Tian, X Zhang… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
In recent years, since edge computing has improved the performance of transportation systems, research on edge computing-enabled transportation systems has received …
T Yang, H Ye, H Xu - Proceedings of the Genetic and Evolutionary …, 2024 - dl.acm.org
Large-scale Mixed-Integer Linear Programming (MILP) problems have been efficiently addressed using Machine Learning (ML)-based frameworks, especially ML-based …
Z Guo, Y Li, C Liu, W Ouyang, J Yan - Forty-first International Conference … - openreview.net
Data plays a pivotal role in the development of both classic and learning-based methods for Mixed-Integer Linear Programming (MILP). However, the scarcity of data in real-world …