Model fairness (a.k.a., bias) has become one of the most critical proble...
Quantum computing presents a promising approach for machine learning wit...
Security has always been a critical issue in machine learning (ML)
appli...
Visualizations have played a crucial role in helping quantum computing u...
During the deployment of deep neural networks (DNNs) on edge devices, ma...
Among different quantum algorithms, PQC for QML show promises on near-te...
In recent years, graph representation learning has gained significant
po...
Recent advances in quantum computing systems attract tremendous attentio...
As real-world graphs expand in size, larger GNN models with billions of
...
Transformers are considered one of the most important deep learning mode...
Quantum computing has attracted considerable public attention due to its...
Model compression, such as pruning and quantization, has been widely app...
Along with the progress of AI democratization, neural networks are being...
This paper represents the first effort to explore an automated architect...
Convolutional neural networks (CNNs) are used in numerous real-world
app...
This work proposes a novel Deep Neural Network (DNN) quantization framew...
In this paper, we propose a novel gender bias detection method by utiliz...
Molecular similarity search has been widely used in drug discovery to
id...
Differentiable neural architecture search (DNAS) is known for its capaci...
With the constant increase of the number of quantum bits (qubits) in the...
In the noisy intermediate-scale quantum (NISQ) era, one of the key quest...
A pruning-based AutoML framework for run-time reconfigurability, namely ...
Along with the development of AI democratization, the machine learning
a...
Powerful yet complex deep neural networks (DNNs) have fueled a booming d...
With the tremendous success of deep learning, there exists imminent need...
Real-time cardiac magnetic resonance imaging (MRI) plays an increasingly...
Hardware and neural architecture co-search that automatically generates
...
The strict security requirements placed on medical records by various pr...
The recent breakthroughs of Neural Architecture Search (NAS) have motiva...
Despite the pursuit of quantum supremacy in various applications, the po...
Neural Architecture Search (NAS) has demonstrated its power on various A...
Due to increasing privacy concerns, neural network (NN) based secure
inf...
Co-exploration of neural architectures and hardware design is promising ...
In the recent past, the success of Neural Architecture Search (NAS) has
...
Real-time Deep Neural Network (DNN) inference with low-latency requireme...
We propose a novel hardware and software co-exploration framework for
ef...
A fundamental question lies in almost every application of deep neural
n...