Naigang Wang
11 papers · 2018–2024 · 6 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird π§ Keyword Pioneer πΊοΈ Taxonomy Completionist (16) π Interdisciplinary Bridge π Conference Polyglot (6)
π
Academic Marathon
(6)
π
Cross-Pollinator
(10)
π
Century Club
(11)
π₯
Unstoppable
(5)
Conferences
NIPS (6)
ICLR (1)
ICML (1)
IJCAI (1)
INTERSPEECH (1)
WACV (1)
Top co-authors
Keywords
model compression
(4)
model quantization
(3)
efficient computing
(2)
knowledge distillation
(2)
neural network optimization
(2)
energy efficiency
(1)
distributed training
(1)
gradient computation
(1)
communication efficiency
(1)
proximal gradient descent
(1)
long short-term memory
(1)
deep neural network
(1)
gradient compression
(1)
latency constraint
(1)
weight magnitude reduction
(1)
inference efficiency
(1)
low precision training
(1)
weight quantization
(1)
training acceleration
(1)
model efficiency
(1)
Papers
Improved Techniques for Quantizing Deep Networks With Adaptive Bit-Widths
WACV 2024
MagR: Weight Magnitude Reduction for Enhancing Post-Training Quantization
NIPS 2024
A Provably Effective Method for Pruning Experts in Fine-tuned Sparse Mixture-of-Experts
ICML 2024
Deep Compression of Pre-trained Transformer Models
NIPS 2022
Hardware-Aware Neural Architecture Search: Survey and Taxonomy
IJCAI 2021
4-Bit Quantization of LSTM-Based Speech Recognition Models
INTERSPEECH 2021
ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training
NIPS 2020
Ultra-Low Precision 4-bit Training of Deep Neural Networks
NIPS 2020
Accumulation Bit-Width Scaling For Ultra-Low Precision Training Of Deep Networks
ICLR 2019
Hybrid 8-bit Floating Point (HFP8) Training and Inference for Deep Neural Networks
NIPS 2019
Training Deep Neural Networks with 8-bit Floating Point Numbers
NIPS 2018