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Seowon Ji

2 accepted papers

2025

FedWSQ: Efficient Federated Learning with Weight Standardization and Distribution-Aware Non-Uniform Quantization

ICCV 2025poster

Federated learning (FL) often suffers from performance degradation due to key challenges such as data heterogeneity and communication constraints. To address these limitations, we present a novel FL framework called FedWSQ, which integrates weight standardization (WS) and the proposed distribution-a…

2025

Predicting High-precision Depth on Low-Precision Devices Using 2D Hilbert Curves

ICML 2025poster

Dense depth prediction deep neural networks (DNN) have achieved impressive results for both monocular and binocular data but they are limited by high computational complexity, restricting their use on low-end devices. For better on-device efficiency and hardware utilization, weights and activations…

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