1 citations · 5 across the 12 of their papers we have counts for
12 papers
Reinforcement Learning Policy as Macro Regulator Rather than Macro Placer
Ke Xue, Ruo-Tong Chen, Xi Lin +4
In modern chip design, placement aims at placing millions of circuit modules, which is an essential step that significantly influences power, performance, and area (PPA) metrics. R…
An Automated Approach to Collecting and Labeling Time Series Data for Event Detection Using Elastic Node Hardware
Tianheng Ling, Islam Mansour, Chao Qian +1
Recent advancements in IoT technologies have underscored the importance of using sensor data to understand environmental contexts effectively. This paper introduces a novel embedde…
Detection-Rate-Emphasized Multi-objective Evolutionary Feature Selection for Network Intrusion Detection
Zi-Hang Cheng, Haopu Shang, Chao Qian
Network intrusion detection is one of the most important issues in the field of cyber security, and various machine learning techniques have been applied to build intrusion detecti…
Confidence-aware Contrastive Learning for Selective Classification
Yu-Chang Wu, Shen-Huan Lyu, Haopu Shang +2
Selective classification enables models to make predictions only when they are sufficiently confident, aiming to enhance safety and reliability, which is important in high-stakes s…
Quality-Diversity with Limited Resources
Ren-Jian Wang, Ke Xue, Cong Guan +1
Quality-Diversity (QD) algorithms have emerged as a powerful optimization paradigm with the aim of generating a set of high-quality and diverse solutions. To achieve such a challen…
Maintaining Diversity Provably Helps in Evolutionary Multimodal Optimization
Shengjie Ren, Zhijia Qiu, Chao Bian +2
In the real world, there exist a class of optimization problems that multiple (local) optimal solutions in the solution space correspond to a single point in the objective space. I…