9 papers
Goal-Oriented Multi-Agent Reinforcement Learning for Decentralized Agent Teams
Hung Du, Hy Nguyen, Srikanth Thudumu +2
Connected and autonomous vehicles across land, water, and air must often operate in dynamic, unpredictable environments with limited communication, no centralized control, and part…
Supervised Quantum Machine Learning: A Future Outlook from Qubits to Enterprise Applications
Srikanth Thudumu, Jason Fisher, Hung Du
Supervised Quantum Machine Learning (QML) represents an intersection of quantum computing and classical machine learning, aiming to use quantum resources to support model training…
Local Control Networks (LCNs): Optimizing Flexibility in Neural Network Data Pattern Capture
Hy Nguyen, Duy Khoa Pham, Srikanth Thudumu +3
The widespread use of Multi-layer perceptrons (MLPs) often relies on a fixed activation function (e.g., ReLU, Sigmoid, Tanh) for all nodes within the hidden layers. While effective…
Dual-Branch HNSW Approach with Skip Bridges and LID-Driven Optimization
Hy Nguyen, Nguyen Hung Nguyen, Nguyen Linh Bao Nguyen +4
The Hierarchical Navigable Small World (HNSW) algorithm is widely used for approximate nearest neighbor (ANN) search, leveraging the principles of navigable small-world graphs. How…
The M-factor: A Novel Metric for Evaluating Neural Architecture Search in Resource-Constrained Environments
Srikanth Thudumu, Hy Nguyen, Hung Du +6
Neural Architecture Search (NAS) aims to automate the design of deep neural networks. However, existing NAS techniques often focus on maximising accuracy, neglecting model efficien…
A Survey on Context-Aware Multi-Agent Systems: Techniques, Challenges and Future Directions
Hung Du, Srikanth Thudumu, Rajesh Vasa +1
Research interest in autonomous agents is on the rise as an emerging topic. The notable achievements of Large Language Models (LLMs) have demonstrated the considerable potential to…