SketchML: Accelerating Distributed Machine Learning with Data Sketches

Summary: SketchML uses data sketches to compress distributed SGD gradients, targeting sparse gradients. Key ideas: quantile-sketch bucketization, MinMaxSketch collision-resolving hash tables, and delta-binary encoding; shows error bounds and 10x speedups on Tencent. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 5602
Venue: SIGMOD
Year: 2018
Pagerank: 6.9160949e-05
Overall Rank: 4,083 | 71.99%
DOI: 10.1145/3183713.3196894

Incoming Non-self Citations Over Time

Authors

1. Jiawei Jiang (Peking University; Tencent)
2. Fangcheng Fu (Peking University)
3. Tong Yang (Peking University)
4. Bin Cui (Peking University)

BibTeX Citation

@inproceedings{jiang_sigmod18,
        title = {{SketchML: Accelerating Distributed Machine Learning with Data Sketches}},
        author = {Jiang, Jiawei and Fu, Fangcheng and Yang, Tong and Cui, Bin},
        series = {{SIGMOD} '18},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3183713.3196894},
        url = {https://dl.acm.org/doi/10.1145/3183713.3196894},
        year = {2018}
}

Incoming Citations (Sorted by Pagerank)

Showing 14 of 14 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
3,169	Towards Demystifying Serverless Machine Learning Training	2021	SIGMOD	7.6715222e-05
3,221	Camel: Managing Data for Efficient Stream Learning	2022	SIGMOD	7.6271601e-05
3,237	BlindFL: Vertical Federated Machine Learning without Peeking into Your Data	2022	SIGMOD	7.6089416e-05
3,898	BurstSketch: Finding Bursts in Data Streams	2021	SIGMOD	7.0367583e-05
4,956	Heterogeneity-Aware Distributed Machine Learning Training via Partial Reduce	2021	SIGMOD	6.4290135e-05
6,633	Agile and Accurate CTR Prediction Model Training for Massive-Scale Online Advertising Systems	2021	SIGMOD	5.8185371e-05
8,034	Angel-PTM: A Scalable and Economical Large-scale Pre-training System in Tencent	2023	VLDB	5.502946e-05
8,310	TreeSensing: Linearly Compressing Sketches with Flexibility	2023	SIGMOD	5.4556836e-05
8,794	AWARE: Workload-aware, Redundancy-exploiting Linear Algebra	2023	SIGMOD	5.370464e-05
8,869	A Distributed System for Large-scale n-gram Language Models at Tencent	2019	VLDB	5.3543688e-05
10,114	Towards Communication-efficient Vertical Federated Learning Training via Cache-enabled Local Updates	2022	VLDB	5.1319012e-05
10,613	CounterSnake: A lossless and generalized compression framework for diverse sketches	2026	VLDB	5.093636e-05
10,769	Malleus: Straggler-Resilient Hybrid Parallel Training of Large-scale Models via Malleable Data and Model Parallelization	2025	SIGMOD	5.093636e-05
11,562	MinMax Sampling: A Near-optimal Global Summary for Aggregation in the Wide Area	2022	SIGMOD	5.093636e-05

Outgoing Citations (Sorted by Pagerank)

Showing 5 of 5 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
82	Space-Efficient Online Computation of Quantile Summaries	2001	SIGMOD	0.00036378991
1,150	DimmWitted: A Study of Main-Memory Statistical Analytics	2014	VLDB	0.00011943462
2,162	Heterogeneity-aware Distributed Parameter Servers	2017	SIGMOD	9.0581831e-05
4,529	TencentRec: Real-time Stream Recommendation in Practice	2015	SIGMOD	6.6446748e-05
11,999	LDA*: A Robust and Large-scale Topic Modeling System	2017	VLDB	5.093636e-05

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10	8,310	TreeSensing: Linearly Compressing Sketches with Flexibility	2023	SIGMOD