3 papers
cs.LG2026
RETENTION: Resource-Efficient Tree-Based Ensemble Model Acceleration with Content-Addressable Memory
Yi-Chun Liao, Chieh-Lin Tsai, Yuan-Hao Chang +3
Although deep learning has demonstrated remarkable capability in learning from unstructured data, modern tree-based ensemble models remain superior in extracting relevant informati…
cs.AR2025
Sensitivity-Aware Mixed-Precision Quantization for ReRAM-based Computing-in-Memory
Guan-Cheng Chen, Chieh-Lin Tsai, Pei-Hsuan Tsai +1
Compute-In-Memory (CIM) systems, particularly those utilizing ReRAM and memristive technologies, offer a promising path toward energy-efficient neural network computation. However,…
cs.AR2025
ReCross: Efficient Embedding Reduction Scheme for In-Memory Computing using ReRAM-Based Crossbar
Yu-Hong Lai, Chieh-Lin Tsai, Wen Sheng Lim +3
Deep learning-based recommendation models (DLRMs) are widely deployed in commercial applications to enhance user experience. However, the large and sparse embedding layers in these…