1 citations · 1 across the 4 of their papers we have counts for
6 papers
Hephaestus: Mixture Generative Modeling with Energy Guidance for Large-scale QoS Degradation
Nguyen Do, Bach Ngo, Youval Kashuv +3
We study the Quality of Service Degradation (QoSD) problem, in which an adversary perturbs edge weights to degrade network performance. This setting arises in both network infrastr…
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…
Groups Influence with Minimum Cost in Social Networks
Phuong N. H. Pham, Canh V. Pham, Hieu V. Duong +2
This paper studies a Group Influence with Minimum cost which aims to find a seed set with smallest cost that can influence all target groups, where each user is associated with a c…
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…