Quantum Machine Learning

Research Areas: Artificial Intelligence and Machine Learning

Principal Investigator: Vaneet Aggarwal

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Quantum Machine Learning (QML) is an emerging research area advocating the use of quantum computing for advancement in machine learning. In this project, we aim to demonstrate the speedup in machine learning tasks due to the use of quantum computing

Some representative publications are:

Bhargav Ganguly, Yulian Wu, Di Wang, and Vaneet Aggarwal, "Quantum Computing Provides Exponential Regret Improvement in Episodic Reinforcement Learning," Feb 2023.
Dheeraj Peddireddy, Utkarsh Priyam, and Vaneet Aggarwal, "Noisy Tensor Ring approximation for computing gradients of Variational Quantum Eigensolver for Combinatorial Optimization," Feb 2023
Yulian Wu, Chaowen Guan, Vaneet Aggarwal, and Di Wang, "Quantum Heavy-tailed Bandits," Jan 2023.
Dheeraj Peddireddy, Vipul Bansal, and Vaneet Aggarwal, "Classical simulation of variational quantum classifiers using tensor rings," Applied Soft Computing, Volume 141, 110308, July 2023.
Debanjan Konar, Aditya Das Sarma, Soham Bhandary, Siddhartha Bhattacharyya, Attila Cangia, and Vaneet Aggarwal, "A Shallow Hybrid Classical-Quantum Spiking Feedforward Neural Network for Noise-Robust Image Classification," Applied Soft Computing, vol. 136, paper 110099, Mar 2023
Mohammad Ali Javidian, Vaneet Aggarwal, and Zubin Jacob, "Quantum Causal Inference in the Presence of Hidden Common Causes: an Entropic Approach," Physical Review A, 106, 062425, Dec 2022.
Mohammad Ali Javidian, Vaneet Aggarwal, and Zubin Jacob, "Learning Circular Hidden Quantum Markov Models: A Tensor Network Approach," arXiv, Oct 2021
Dheeraj Peddireddy, Vipul Bansal, Zubin Jacob, and Vaneet Aggarwal, "Tensor Ring Parametrized Variational Quantum Circuits for Large Scale Quantum Machine Learning," in Proc. Neurips Workshop on Quantum Tensor Networks in Machine Learning, Dec. 2021.
Mohammad Ali Javidian, Vaneet Aggarwal, and Zubin Jacob, "Tensor Rings for Learning Circular Hidden Markov Models," in Proc. Neurips Workshop on Quantum Tensor Networks in Machine Learning, Dec. 2021.