165 citations · 270 across the 16 of their papers we have counts for
17 papers
Spectral Embeddings Leak Graph Topology: Theory, Benchmark, and Adaptive Reconstruction
Thinh Nguyen-Cong, Truong-Son Hy, Thang N. Dinh
Graph Neural Networks (GNNs) excel on relational data, but standard benchmarks unrealistically assume the graph is centrally available. In practice, settings such as Federated Grap…
Blockchain-based Secure Client Selection in Federated Learning
Truc Nguyen, Phuc Thai, Tre' R. Jeter +2
Despite the great potential of Federated Learning (FL) in large-scale distributed learning, the current system is still subject to several privacy issues due to the fact that local…
FastHare: Fast Hamiltonian Reduction for Large-scale Quantum Annealing
Phuc Thai, My T. Thai, Tam Vu +1
Quantum annealing (QA) that encodes optimization problems into Hamiltonians remains the only near-term quantum computing paradigm that provides sufficient many qubits for real-worl…
SaPHyRa: A Learning Theory Approach to Ranking Nodes in Large Networks
Phuc Thai, My T. Thai, Tam Vu +1
Ranking nodes based on their centrality stands a fundamental, yet, challenging problem in large-scale networks. Approximate methods can quickly estimate nodes' centrality and ident…
OptChain: Optimal Transactions Placement for Scalable Blockchain Sharding
Lan N. Nguyen, Truc Nguyen, Thang N. Dinh +1
A major challenge in blockchain sharding protocols is that more than 95% transactions are cross-shard. Not only those cross-shard transactions degrade the system throughput but als…
Approximate k-Cover in Hypergraphs: Efficient Algorithms, and Applications
Hung Nguyen, Phuc Thai, My Thai +2
Given a weighted hypergraph , the approximate -cover problem seeks for a size- subset of that has the maximum weighted cover…
Importance Sketching of Influence Dynamics in Billion-scale Networks
Hung T. Nguyen, Tri P. Nguyen, NhatHai Phan +1
The blooming availability of traces for social, biological, and communication networks opens up unprecedented opportunities in analyzing diffusion processes in networks. However, t…
Outward Influence and Cascade Size Estimation in Billion-scale Networks
Hung T. Nguyen, Tri P. Nguyen, Tam Vu +1
Estimating cascade size and nodes' influence is a fundamental task in social, technological, and biological networks. Yet this task is extremely challenging due to the sheer size a…
Blocking Self-avoiding Walks Stops Cyber-epidemics: A Scalable GPU-based Approach
Hung T. Nguyen, Alberto Cano, Tam Vu +1
Cyber-epidemics, the widespread of fake news or propaganda through social media, can cause devastating economic and political consequences. A common countermeasure against cyber-ep…
Towards Optimal Strategy for Adaptive Probing in Incomplete Networks
Tri P. Nguyen, Hung T. Nguyen, Thang N. Dinh
We investigate a graph probing problem in which an agent has only an incomplete view of the network and wishes to explore the network with least effort. In each s…
Transitivity Demolition and the Falls of Social Networks
Hung T. Nguyen, Nam P. Nguyen, Tam Vu +2
In this paper, we study crucial elements of a complex network, namely its nodes and connections, which play a key role in maintaining the network's structure and function under une…
Vulnerability of Clustering under Node Failure in Complex Networks
Alan Kuhnle, Nam P. Nguyen, Thang N. Dinh +1
Robustness in response to unexpected events is always desirable for real-world networks. To improve the robustness of any networked system, it is important to analyze vulnerability…
TipTop: (Almost) Exact Solutions for Influence Maximization in Billion-scale Networks
Xiang Li, J. David Smith, Thang N. Dinh +1
In this paper, we study the Cost-aware Target Viral Marketing (CTVM) problem, a generalization of Influence Maximization (IM). CTVM asks for the most cost-effective users to influe…
Multiple Infection Sources Identification with Provable Guarantees
Hung T. Nguyen, Preetam Ghosh, Michael L. Mayo +1
Given an aftermath of a cascade in the network, i.e. a set of "infected" nodes after an epidemic outbreak or a propagation of rumors/worms/viruses, how can we infer the sourc…
Stop-and-Stare: Optimal Sampling Algorithms for Viral Marketing in Billion-scale Networks
Hung T. Nguyen, My T. Thai, Thang N. Dinh
Influence Maximization (IM), that seeks a small set of key users who spread the influence widely into the network, is a core problem in multiple domains. It finds applications in v…
Network Clustering via Maximizing Modularity: Approximation Algorithms and Theoretical Limits
Thang N. Dinh, Xiang Li, My T. Thai
Many social networks and complex systems are found to be naturally divided into clusters of densely connected nodes, known as community structure (CS). Finding CS is one of fundame…
Finding Community Structure with Performance Guarantees in Complex Networks
Thang N. Dinh, My T. Thai
Many networks including social networks, computer networks, and biological networks are found to divide naturally into communities of densely connected individuals. Finding communi…