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Papers
RCMoE: A Communication-Efficient Random Compression Framework for Resource-Constrained Mixture-of-Experts Training
AAAI 2026
Optimal and Approximate Adaptive Stochastic Quantization
NeurIPS 2024
Invariant Representations with Stochastically Quantized Neural Networks
AAAI 2023
Correlated Quantization for Distributed Mean Estimation and Optimization
ICML 2022
FedNew: A Communication-Efficient and Privacy-Preserving Newton-Type Method for Federated Learning
ICML 2022
SQ-VAE: Variational Bayes on Discrete Representation with Self-annealed Stochastic Quantization
ICML 2022
ZipML: Training Linear Models with End-to-End Low Precision, and a Little Bit of Deep Learning
ICML 2017