Multicoated and Folded Graph Neural Networks With Strong Lottery Tickets. - Jiale Yan; Hiroaki Ito; Ángel López García-Arias; Yasuyuki Okoshi; Hikari Otsuka; Kazushi Kawamura; Thiem Van Chu; Masato Motomura (LoG, 2023)

WhiteDwarf: 12.24 TFLOPS/W 40 nm Versatile Neural Inference Engine for Ultra-Compact Execution of CNNs and MLPs Through Triple Unstructured Sparsity Exploitation and Triple Model Compression. - Yasuyuki Okoshi; Ángel López García-Arias; Jaehoon Yu; Junnosuke Suzuki; Hikari Otsuka; Thiem Van Chu; Kazushi Kawamura; Daichi Fujiki; Masato Motomura (A-SSCC, 2024)

Exploiting N:M Sparsity in Quantized-Folded ResNets: Signed Multicoat Supermasks and Iterative Pruning-Quantization. - Akihiro Shioda; Ángel López García-Arias; Hikari Otsuka; Yuki Ichikawa; Yasuyuki Okoshi; Kazushi Kawamura; Thiem Van Chu; Daichi Fujiki; Masato Motomura (CANDAR, 2024)

Partial Search in a Frozen Network is Enough to Find a Strong Lottery Ticket. - Hikari Otsuka; Daiki Chijiwa; Ángel López García-Arias; Yasuyuki Okoshi; Kazushi Kawamura; Thiem Van Chu; Daichi Fujiki; Susumu Takeuchi; Masato Motomura (CoRR, 2024)

Restricted Random Pruning at Initialization for High Compression Range. - Hikari Otsuka; Yasuyuki Okoshi; Ángel López García-Arias; Kazushi Kawamura; Thiem Van Chu; Daichi Fujiki; Masato Motomura (Trans. Mach. Learn. Res., 2024)

WhiteDwarf: A Holistic Co-Design Approach to Ultra-Compact Neural Inference Acceleration. - Ángel López García-Arias; Yasuyuki Okoshi; Jaehoon Yu; Junnosuke Suzuki; Hikari Otsuka; Kazushi Kawamura; Thiem Van Chu; Daichi Fujiki; Masato Motomura (IEEE Access, 2025)

Uncovering Strong Lottery Tickets in Graph Transformers: A Path to Memory Efficient and Robust Graph Learning. - Hiroaki Ito; Jiale Yan; Hikari Otsuka; Kazushi Kawamura; Masato Motomura; Thiem Van Chu; Daichi Fujiki (Trans. Mach. Learn. Res., 2025)

Partially Frozen Random Networks Contain Compact Strong Lottery Tickets. - Hikari Otsuka; Daiki Chijiwa; Ángel López García-Arias; Yasuyuki Okoshi; Kazushi Kawamura; Thiem Van Chu; Daichi Fujiki; Susumu Takeuchi; Masato Motomura (Trans. Mach. Learn. Res., 2025)