2 citations · 2 across the 6 of their papers we have counts for
7 papers
Unconditional Separation between LL and CLL
Shubham Bhardwaj
Catalytic computation involves the study of Turing machines that are provided an additional catalytic tape (with arbitrary content) that the machine may use while ensuring that the…
Semantic Grading of Written Answers in Low-Resource Language Bangla Using a Fine-Tuned Lightweight Language Model
Meherun Farzana, Aniket Joarder, Mahmudul Hasan +1
Bangla is among the world's most widely spoken languages, yet it remains underserved in educational NLP research. In many remote and rural regions, access to qualified subject teac…
Temporal Sheaf Neural Networks with Dynamic Orthogonal Transport
Md Sadek Hossain Asif, Tanzila Khan, Md. Mosaddek Khan
We introduce Temporal Sheaf Neural Networks (TSNN), a temporal link prediction framework that equips each node with a time-varying orthogonal frame and compares node states only af…
Enhancing Heterogeneous Multi-Agent Cooperation in Decentralized MARL via GNN-driven Intrinsic Rewards
Jahir Sadik Monon, Deeparghya Dutta Barua, Md. Mosaddek Khan
Multi-agent Reinforcement Learning (MARL) is emerging as a key framework for various sequential decision-making and control tasks. Unlike their single-agent counterparts, multi-age…
Adaptive Opponent Policy Detection in Multi-Agent MDPs: Real-Time Strategy Switch Identification Using Running Error Estimation
Mohidul Haque Mridul, Mohammad Foysal Khan, Redwan Ahmed Rizvee +1
In Multi-agent Reinforcement Learning (MARL), accurately perceiving opponents' strategies is essential for both cooperative and adversarial contexts, particularly within dynamic en…
A Graph Neural Network-Based QUBO-Formulated Hamiltonian-Inspired Loss Function for Combinatorial Optimization using Reinforcement Learning
Redwan Ahmed Rizvee, Raheeb Hassan, Md. Mosaddek Khan
Quadratic Unconstrained Binary Optimization (QUBO) is a generic technique to model various NP-hard Combinatorial Optimization problems (CO) in the form of binary variables. Ising H…
A Graph Neural Network-Based QUBO-Formulated Hamiltonian-Inspired Loss Function for Combinatorial Optimization using Reinforcement Learning
Redwan Ahmed Rizvee, Md. Mosaddek Khan
Quadratic Unconstrained Binary Optimization (QUBO) is a generic technique to model various NP-hard combinatorial optimization problems in the form of binary variables. The Hamilton…