We investigate the link between fine-tuning bq, bk, and bv with downstream performance. We find that fine-tuning bv in low-data regimes is sufficient; bk has no effect on improved expressiveness, whereas bq has a limited effect.
We investigate and compare BP and forward-only algorithms in terms of binarization, finding that PEPITA and FF are more vulnerable to binary activations.
We propose a biologically-plausible forward-only algorithm (Bio-FO), not only addressing the biological-implausibility issues associated with BP, but also outperforming the state-of-the-art forward-only algorithms.
We propose an energy-aware NAS framework for distributed IoT, aiming to search for distributed DNNs to maximize prediction performance subjected to Flash Memory (Flash), Random-access Memory (RAM), and energy constraints.
We propose a lightweight inference scheme specifically designed for DNNs trained using the Forward-Forward algorithm ( Contributor to the Forward-Forward repository ...⭐ ).
We propose the first interpretable self-supervised network for seizure detection without any need for real seizure data in training, which has comparable performance with supervised methods. (Contemporaneous and similar work of peers in AAAI2023)
To improve the adaptability and robustness of the BLE positioning system, we propose making full use of the three separate channels instead of their combination.
Teaching Duty: : 2025: Machine Learning for Internet of Things (IoT) (EITP40): Kaggle Competition, Invited Lecture (Efficient LLMs) 2024: Machine Learning for Internet of Things (IoT) (EITP40): Kaggle Competition (Lab2/ Lab3) 2023: Machine Learning for Internet of Things (IoT) (EITP40): Kaggle Competition 2023-2024: Signal Processing in Multimedia (EITA50) 2022: Machine Learning for Internet of Things (IoT) (EITP40): Kaggle Competition
Supervision: : 2026: Assistant Supervisor: LLM-Based Data Extraction and Machine Learning for CO2e Estimation of Semiconductor Components (Master Thesis, co-supervisor with Volve Cars) 2023: Supervisor: Railway Anomaly Detection System (Course Project)
Patents: :
A high quality precision panoramic imaging system and method based on the DSLR camera
An intelligent inspection robot and intelligent inspection method for underground pipelines