7 citations · 11 across the 4 of their papers we have counts for
5 papers · 1 filter
Benchmarking Neural Decoding Backbones towards Enhanced On-edge iBCI Applications
Zhou Zhou, Guohang He, Zheng Zhang +5
Traditional invasive Brain-Computer Interfaces (iBCIs) typically depend on neural decoding processes conducted on workstations within laboratory settings, which prevents their ever…
FR-NAS: Forward-and-Reverse Graph Predictor for Efficient Neural Architecture Search
Haoming Zhang, Ran Cheng
Neural Architecture Search (NAS) has emerged as a key tool in identifying optimal configurations of deep neural networks tailored to specific tasks. However, training and assessing…
Generalized Population-Based Training for Hyperparameter Optimization in Reinforcement Learning
Hui Bai, Ran Cheng
Hyperparameter optimization plays a key role in the machine learning domain. Its significance is especially pronounced in reinforcement learning (RL), where agents continuously int…
Rethinking Population-assisted Off-policy Reinforcement Learning
Bowen Zheng, Ran Cheng
While off-policy reinforcement learning (RL) algorithms are sample efficient due to gradient-based updates and data reuse in the replay buffer, they struggle with convergence to lo…
Bi-fidelity Evolutionary Multiobjective Search for Adversarially Robust Deep Neural Architectures
Jia Liu, Ran Cheng, Yaochu Jin
Deep neural networks have been found vulnerable to adversarial attacks, thus raising potentially concerns in security-sensitive contexts. To address this problem, recent research h…