Upcoming Events
Over 2X Circuit Compression without Accuracy Loss for Quantum Machine Learning
Oct 11, 2022, 12:30 - 1:30 PM
Exploratory Hall, room 3301
Speaker: Dr. Weiwen Jiang, Assistant Professor, Electrical and Computer Engineering, George Mason University
Title: Over 2X Circuit Compression without Accuracy Loss for Quantum Machine Learning
Abstract:
Model compression, such as pruning and quantization, has been widely applied to optimize neural networks on resource-limited classical devices. Recently, there are growing interest in variational quantum circuits (VQC), that is, a type of neural network on quantum computers (a.k.a., quantum neural networks). It is well known that the near-term quantum devices have high noise and limited resources (i.e., quantum bits, qubits); yet, how to compress quantum neural networks has not been thoroughly studied. One might think it is straightforward to apply the classical compression techniques to quantum scenarios. However, this paper reveals that there exist differences between the compression of quantum and classical neural networks.
Time: Tuesday, October 11, 2022, 12:30pm – 1:30pm
Place: Exploratory Hall, room 3301
Zoom and In-person
