The Research and Optimization of Parallel Finite Element Algorithm based on MiniFE. - Meng Wu; Can Yang; Taoran Xiang; Daning Cheng (CoRR, 2015)

Weighted parallel SGD for distributed unbalanced-workload training system. - Daning Cheng; Shigang Li 002; Yunquan Zhang (CoRR, 2017)

Asynchronous COMID: the theoretic basis for transmitted data sparsification tricks on Parameter Server. - Daning Cheng; Shigang Li 002; Yunquan Zhang (CoRR, 2017)

Asynchronous Parallel Sampling Gradient Boosting Decision Tree. - Daning Cheng; Fen Xia; Shigang Li 002; Yunquan Zhang (CoRR, 2018)

Using Known Information to Accelerate HyperParameters Optimization Based on SMBO. - Daning Cheng; Hanping Zhang; Fen Xia; Shigang Li 002; Yunquan Zhang (CoRR, 2018)

Using Gradient Based Multikernel Gaussian Process and Meta-Acquisition Function to Accelerate SMBO. - Daning Cheng; Hanping Zhang; Fen Xia; Shigang Li 002; Yunquan Zhang (ICTAI, 2019)

The Scalability for Parallel Machine Learning Training Algorithm: Dataset Matters. - Daning Cheng; Hanping Zhang; Fen Xia; Shigang Li 002; Yunquan Zhang (CoRR, 2019)

WP-SGD: Weighted parallel SGD for distributed unbalanced-workload training system. - Daning Cheng; Shigang Li 002; Yunquan Zhang (J. Parallel Distributed Comput., 2020)

Why Dataset Properties Bound the Scalability of Parallel Machine Learning Training Algorithms. - Daning Cheng; Shigang Li 002; Hanping Zhang; Fen Xia; Yunquan Zhang (IEEE Trans. Parallel Distributed Syst., 2021)

Quantization in Layer's Input is Matter. - Daning Cheng; Wenguang Chen (CoRR, 2022)

Mixed-Precision Inference Quantization: Radically Towards Faster inference speed, Lower Storage requirement, and Lower Loss. - Daning Cheng; Wenguang Chen (CoRR, 2022)

Asynch-SGBDT: Train Stochastic Gradient Boosting Decision Trees in an Asynchronous Parallel Manner. - Daning Cheng; Shigang Li 002; Yunquan Zhang (IPDPS, 2023)

FP=xINT:A Low-Bit Series Expansion Algorithm for Post-Training Quantization. - Boyang Zhang; Daning Cheng; Yunquan Zhang; Fangmin Liu (CoRR, 2024)

Lossless Model Compression via Joint Low-Rank Factorization Optimization. - Boyang Zhang; Daning Cheng; Yunquan Zhang; Fangmin Liu; Jiake Tian (CoRR, 2024)

Compression for Better: A General and Stable Lossless Compression Framework. - Boyang Zhang; Daning Cheng; Yunquan Zhang; Fangmin Liu; Wenguang Chen (CoRR, 2024)

A General Error-Theoretical Analysis Framework for Constructing Compression Strategies. - Boyang Zhang; Daning Cheng; Yunquan Zhang; Meiqi Tu; Fangmin Liu; Jiake Tian (CoRR, 2025)

Can the capability of Large Language Models be described by human ability? A Meta Study. - Mingrui Zan; Yunquan Zhang; Boyang Zhang; Fangming Liu; Daning Cheng (CoRR, 2025)

How to Train a Model on a Cheap Cluster with Low Cost using Block Coordinate Descent. - Zeyu Liu; Yunquan Zhang; Boyang Zhang; Guoyong Jiang; Daning Cheng (CoRR, 2025)

MoQE: Improve Quantization Model performance via Mixture of Quantization Experts. - Jinhao Zhang; Yunquan Zhang; Boyang Zhang; Zeyu Liu; Daning Cheng (CoRR, 2025)