1 citations · 1 across the 5 of their papers we have counts for
5 papers
MPM-LLM4DSE: Reaching the Pareto Frontier in HLS with Multimodal Learning and LLM-Driven Exploration
Lei Xu, Shanshan Wang, Chenglong Xiao
High-Level Synthesis (HLS) design space exploration (DSE) seeks Pareto-optimal designs within expansive pragma configuration spaces. To accelerate HLS DSE, graph neural networks (G…
Instance-Aware Algorithm Selection for Maximum Clique via a Dual-Channel Graph Neural Architecture
Xiang Li, Shanshan Wang, Chenglong Xiao
Although the Maximum Clique Problem (MCP) has been extensively studied and features a rich ecosystem of exact solvers, empirical evidence shows that solver performance varies subst…
An algorithm with a delay of for enumerating connected induced subgraphs of size
Chenglong Xiao, Chengyong Mao, Shanshan Wang
The problem of enumerating connected subgraphs of a given size in a graph has been extensively studied in recent years. In this paper, we propose an algorithm with a delay of $O(kΔ…
Algorithms with improved delay for enumerating connected induced subgraphs of a large cardinality
Shanshan Wang, Chenglong Xiao, Emmanuel Casseau
The problem of enumerating all connected induced subgraphs of a given order from a given graph arises in many practical applications: bioinformatics, information retrieval, pro…
Novel Algorithms for Efficient Mining of Connected Induced Subgraphs of a Given Cardinality
Shanshan Wang, Chenglong Xiao
Mining subgraphs with interesting structural properties from networks (or graphs) is a computationally challenging task. In this paper, we propose two algorithms for enumerating al…