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cs.LG2024
PikeLPN: Mitigating Overlooked Inefficiencies of Low-Precision Neural Networks
Marina Neseem, Conor McCullough, Randy Hsin +8
Low-precision quantization is recognized for its efficacy in neural network optimization. Our analysis reveals that non-quantized elementwise operations which are prevalent in laye…
cs.CV2024★ 1 cited
MTLoRA: A Low-Rank Adaptation Approach for Efficient Multi-Task Learning
Ahmed Agiza, Marina Neseem, Sherief Reda
Adapting models pre-trained on large-scale datasets to a variety of downstream tasks is a common strategy in deep learning. Consequently, parameter-efficient fine-tuning methods ha…