Daning Cheng - RankMe

23 papers A* 1A 1B 1Journal 20

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	FP=XINT: Representing Neural Networks via Low-Bit Series Basis Functions. AAAI Boyang Zhang, Daning Cheng, Yunquan Zhang, Jiake Tian, Jing Li, Fangming Liu
2026	J	`jnl`	HeRo-Q: A General Framework for Stable Low Bit Quantization via Hessian Conditioning. CoRR Jinhao Zhang, Yunquan Zhang, Zicheng Yan, Boyang Zhang, Jun Sun, Daning Cheng
2026	J	`jnl`	MoE-DisCo:Low Economy Cost Training Mixture-of-Experts Models. CoRR Xin Ye, Daning Cheng, Boyang Zhang, Yunquan Zhang
2025	J	`jnl`	A General Error-Theoretical Analysis Framework for Constructing Compression Strategies. CoRR Boyang Zhang, Daning Cheng, Yunquan Zhang, Meiqi Tu, Fangmin Liu, Jiake Tian
2025	J	`jnl`	Can the capability of Large Language Models be described by human ability? A Meta Study. CoRR Mingrui Zan, Yunquan Zhang, Boyang Zhang, Fangming Liu, Daning Cheng
2025	J	`jnl`	How to Train a Model on a Cheap Cluster with Low Cost using Block Coordinate Descent. CoRR Zeyu Liu, Yunquan Zhang, Boyang Zhang, Guoyong Jiang, Daning Cheng
2025	J	`jnl`	MoQE: Improve Quantization Model performance via Mixture of Quantization Experts. CoRR Jinhao Zhang, Yunquan Zhang, Boyang Zhang, Zeyu Liu, Daning Cheng
2025	J	`jnl`	Rethinking Parameter Sharing as Graph Coloring for Structured Compression. CoRR Boyang Zhang, Daning Cheng, Yunquan Zhang
2024	J	`jnl`	Compression for Better: A General and Stable Lossless Compression Framework. CoRR Boyang Zhang, Daning Cheng, Yunquan Zhang, Fangmin Liu, Wenguang Chen
2024	J	`jnl`	FP=xINT:A Low-Bit Series Expansion Algorithm for Post-Training Quantization. CoRR Boyang Zhang, Daning Cheng, Yunquan Zhang, Fangmin Liu
2024	J	`jnl`	Lossless Model Compression via Joint Low-Rank Factorization Optimization. CoRR Boyang Zhang, Daning Cheng, Yunquan Zhang, Fangmin Liu, Jiake Tian
2023	A	`conf`	Asynch-SGBDT: Train Stochastic Gradient Boosting Decision Trees in an Asynchronous Parallel Manner. IPDPS Daning Cheng, Shigang Li, Yunquan Zhang
2022	J	`jnl`	Mixed-Precision Inference Quantization: Radically Towards Faster inference speed, Lower Storage requirement, and Lower Loss. CoRR Daning Cheng, Wenguang Chen
2022	J	`jnl`	Quantization in Layer's Input is Matter. CoRR Daning Cheng, Wenguang Chen
2021	J	`jnl`	Why Dataset Properties Bound the Scalability of Parallel Machine Learning Training Algorithms. IEEE Trans. Parallel Distributed Syst. Daning Cheng, Shigang Li, Hanping Zhang, Fen Xia, Yunquan Zhang
2020	J	`jnl`	WP-SGD: Weighted parallel SGD for distributed unbalanced-workload training system. J. Parallel Distributed Comput. Daning Cheng, Shigang Li, Yunquan Zhang
2019	J	`jnl`	The Scalability for Parallel Machine Learning Training Algorithm: Dataset Matters. CoRR Daning Cheng, Hanping Zhang, Fen Xia, Shigang Li, Yunquan Zhang
2019	B	`conf`	Using Gradient Based Multikernel Gaussian Process and Meta-Acquisition Function to Accelerate SMBO. ICTAI Daning Cheng, Hanping Zhang, Fen Xia, Shigang Li, Yunquan Zhang
2018	J	`jnl`	Asynchronous Parallel Sampling Gradient Boosting Decision Tree. CoRR Daning Cheng, Fen Xia, Shigang Li, Yunquan Zhang
2018	J	`jnl`	Using Known Information to Accelerate HyperParameters Optimization Based on SMBO. CoRR Daning Cheng, Hanping Zhang, Fen Xia, Shigang Li, Yunquan Zhang
2017	J	`jnl`	Asynchronous COMID: the theoretic basis for transmitted data sparsification tricks on Parameter Server. CoRR Daning Cheng, Shigang Li, Yunquan Zhang
2017	J	`jnl`	Weighted parallel SGD for distributed unbalanced-workload training system. CoRR Daning Cheng, Shigang Li, Yunquan Zhang
2015	J	`jnl`	The Research and Optimization of Parallel Finite Element Algorithm based on MiniFE. CoRR Meng Wu, Can Yang, Taoran Xiang, Daning Cheng