1 citations · 1 across the 4 of their papers we have counts for
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Robust Approximation Algorithms for Non-monotone -Submodular Maximization under a Knapsack Constraint
Dung T. K. Ha, Canh V. Pham, Tan D. Tran +1
The problem of non-monotone -submodular maximization under a knapsack constraint ($\kSMK$) over the ground set size has been raised in many applications in machine learning,…
Linear Query Approximation Algorithms for Non-monotone Submodular Maximization under Knapsack Constraint
Canh V. Pham, Tan D. Tran, Dung T. K. Ha +1
This work, for the first time, introduces two constant factor approximation algorithms with linear query complexity for non-monotone submodular maximization over a ground set of si…
Streaming algorithms for Budgeted -Submodular Maximization problem
Canh V. Pham, Quang C. Vu, Dung K. T. Ha +1
Stimulated by practical applications arising from viral marketing. This paper investigates a novel Budgeted -Submodular Maximization problem defined as follows: Given a finite s…
Cost-aware Targeted Viral Marketing: Approximation with Less Samples
Canh V. Pham, Hieu V. Duong, My T. Thai
Cost-aware Targeted Viral Marketing (CTVM), a generalization of Influence Maximization (IM), has received a lot of attentions recently due to its commercial values. Previous approx…