41 citations · 180 across the 15 of their papers we have counts for
5 papers · 1 filter
Revisiting Diffusion Model Predictions Through Dimensionality
Qing Jin, Chaoyang Wang
Recent advances in diffusion and flow matching models have highlighted a shift in the preferred prediction target -- moving from noise () and velocity (v) to direct da…
PIM-QAT: Neural Network Quantization for Processing-In-Memory (PIM) Systems
Qing Jin, Zhiyu Chen, Jian Ren +3
Processing-in-memory (PIM), an increasingly studied neuromorphic hardware, promises orders of energy and throughput improvements for deep learning inference. Leveraging the massive…
MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge
Geng Yuan, Xiaolong Ma, Wei Niu +13
Recently, a new trend of exploring sparsity for accelerating neural network training has emerged, embracing the paradigm of training on the edge. This paper proposes a novel Memory…
Lottery Ticket Preserves Weight Correlation: Is It Desirable or Not?
Ning Liu, Geng Yuan, Zhengping Che +7
In deep model compression, the recent finding "Lottery Ticket Hypothesis" (LTH) (Frankle & Carbin, 2018) pointed out that there could exist a winning ticket (i.e., a properly prune…
NPAS: A Compiler-aware Framework of Unified Network Pruning and Architecture Search for Beyond Real-Time Mobile Acceleration
Zhengang Li, Geng Yuan, Wei Niu +13
With the increasing demand to efficiently deploy DNNs on mobile edge devices, it becomes much more important to reduce unnecessary computation and increase the execution speed. Pri…