1 citations · 3 across the 9 of their papers we have counts for
5 papers · 1 filter
Logical Resource Estimation for Quantum State Preparation with Compilation
Diyi Liu, Hanyu Wang, Shuchen Zhu +6
Quantum state preparation is a fundamental primitive in quantum algorithms for encoding classical data into quantum amplitudes. We compare the cost of preparing general -qubit s…
UFO: Unlocking Ultra-Efficient Quantized Private Inference with Protocol and Algorithm Co-Optimization
Wenxuan Zeng, Chao Yang, Tianshi Xu +4
Private convolutional neural network (CNN) inference based on secure two-party computation (2PC) suffers from high communication and latency overhead, especially from convolution l…
Quantum LEGO Learning: A Modular Design Principle for Hybrid Artificial Intelligence
Jun Qi, Chao-Han Huck Yang, Pin-Yu Chen +3
Hybrid quantum-classical learning models increasingly integrate neural networks with variational quantum circuits (VQCs) to exploit complementary inductive biases. However, many ex…
Continual Quantum Architecture Search with Tensor-Train Encoding: Theory and Applications to Signal Processing
Jun Qi, Chao-Han Huck Yang, Pin-Yu Chen +3
We introduce CL-QAS, a continual quantum architecture search framework that mitigates the challenges of costly amplitude encoding and catastrophic forgetting in variational quantum…
Random-Matrix-Induced Simplicity Bias in Over-parameterized Variational Quantum Circuits
Jun Qi, Chao-Han Huck Yang, Pin-Yu Chen +1
Over-parameterization is commonly used to increase the expressivity of variational quantum circuits (VQCs), yet deeper and more highly parameterized circuits often exhibit poor tra…