J Liu, Y Liu, WK Ma, M Shao, AMC So - arXiv preprint arXiv:2403.06506, 2024 - arxiv.org
This study develops a framework for a class of constant modulus (CM) optimization problems, which covers binary constraints, discrete phase constraints, semi-orthogonal …
Y Liu, J Liu, WK Ma - ICASSP 2024-2024 IEEE International …, 2024 - ieeexplore.ieee.org
Cardinality-constrained binary quadratic optimization appears in various applications such as finding a densest size-constrained subgraph from a graph. It is a challenging …
We introduce the triangle-densest-K-subgraph problem (TDKS) for undirected graphs: given a size parameter K, compute a subset of K vertices that maximizes the number of induced …
We introduce the triangle-densest-k-subgraph problem (TDkS) for undirected graphs: given a size parameter k, compute a subset of k vertices that maximizes the number of induced …
Dense subgraph discovery (DSD) is a key primitive in graph mining that typically deals with extracting cliques and near-cliques. In this paper, we revisit the optimal quasi-clique (OQC) …
Centrality measures, quantifying the importance of vertices or edges, play a fundamental role in network analysis. To date, triggered by some positive approximability results, a large …
Finding dense subgraphs in large (hyper) graphs is a key primitive in a variety of real-world application domains, encompassing social network analytics, event detection, biology, and …
E Kariotakis, N Sidiropoulos, A Konar - arXiv preprint arXiv:2412.02604, 2024 - arxiv.org
Dense subgraph discovery (DSD) is a key graph mining primitive with myriad applications including finding densely connected communities which are diverse in their vertex …
J Liu, Y Liu, WK Ma, M Shao, AMC So - arXiv preprint arXiv:2403.06513, 2024 - arxiv.org
In the first part of this study, a convex-constrained penalized formulation was studied for a class of constant modulus (CM) problems. In particular, the error bound techniques were …