activity
20152026
most citedBalance and Frustration in Signed Networks

60 citations · 290 across the 27 of their papers we have counts for

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Showing 2025Show all

6 papers · 1 filter

cs.SI2025★ 1 cited

Evaluating Global Measures of Network Centralization: Axiomatic and Numerical Assessments

Majid Saberi, Samin Aref

Network centralization, driven by hub nodes, impacts communication efficiency, structural integration, and dynamic processes such as diffusion and synchronization. Although numerou…

cs.AI2025

Discrete Optimization of Min-Max Violation and its Applications Across Computational Sciences

Cheikh Ahmed, Mahdi Mostajabdaveh, Samin Aref +1

We introduce the Discrete Min-Max Violation (DMMV) as a general optimization problem which seeks an assignment of discrete values to variables that minimizes the largest constraint…

cs.AI2025

LLM-Guided Evolution of Symbolic Acceleration Inequality Families for MILP

Milad Yazdani, Mahdi Mostajabdaveh, Samin Aref +1

Integer programming (IP) is central to many combinatorial optimization tasks but remains challenging due to its NP-hard nature. A practical way to improve IP solvers is to manually…

cs.SI2025

Troika algorithm: approximate optimization for accurate clique partitioning and clustering of weighted networks

Samin Aref, Boris Ng

Clique partitioning is a fundamental network clustering task, with applications in a wide range of computational sciences. It involves identifying an optimal partition of the nodes…

cs.SI2025

Robust Markov stability for community detection at a scale learned based on the structure

Samin Aref, Sanchaai Mathiyarasan

Community detection, the unsupervised task of clustering nodes of a graph, finds applications across various fields. The common approaches for community detection involve optimizin…

cs.LG2025★ 1 cited

Enhancing Ultra-Low-Bit Quantization of Large Language Models Through Saliency-Aware Partial Retraining

Deyu Cao, Samin Aref

The growing use of large language models has raised environmental and economic concerns about their intensity of resource usage during inference. Serving these models to each user…