47 citations · 61 across the 13 of their papers we have counts for
13 papers
Federated Learning Optimization: A Comparative Study of Data and Model Exchange Strategies in Dynamic Networks
Alka Luqman, Yeow Wei Liang Brandon, Anupam Chattopadhyay
The promise and proliferation of large-scale dynamic federated learning gives rise to a prominent open question - is it prudent to share data or model across nodes, if efficiency o…
A Comprehensive Study of Quantum Arithmetic Circuits
Siyi Wang, Xiufan Li, Wei Jie Bryan Lee +3
In recent decades, the field of quantum computing has experienced remarkable progress. This progress is marked by the superior performance of many quantum algorithms compared to th…
Optimal Toffoli-Depth Quantum Adder
Siyi Wang, Suman Deb, Ankit Mondal +1
Efficient quantum arithmetic circuits are commonly found in numerous quantum algorithms of practical significance. Till date, the logarithmic-depth quantum adders includes a consta…
Efficient Quantum Circuits for Machine Learning Activation Functions including Constant T-depth ReLU
Wei Zi, Siyi Wang, Hyunji Kim +3
In recent years, Quantum Machine Learning (QML) has increasingly captured the interest of researchers. Among the components in this domain, activation functions hold a fundamental…
Adversarial Attacks and Dimensionality in Text Classifiers
Nandish Chattopadhyay, Atreya Goswami, Anupam Chattopadhyay
Adversarial attacks on machine learning algorithms have been a key deterrent to the adoption of AI in many real-world use cases. They significantly undermine the ability of high-pe…
Boosting the Efficiency of Quantum Divider through Effective Design Space Exploration
Siyi Wang, Eugene Lim, Anupam Chattopadhyay
Rapid progress in the design of scalable, robust quantum computing necessitates efficient quantum circuit implementation for algorithms with practical relevance. For several algori…