| 416 |
SystemML: Declarative Machine Learning on Spark |
2016 |
VLDB |
65 |
0.00018650998 |
| 1,082 |
Hybrid Parallelization Strategies for Large-Scale Machine Learning in SystemML |
2014 |
VLDB |
36 |
0.00012118261 |
| 1,223 |
Data Management in Machine Learning: Challenges, Techniques, and Systems |
2017 |
SIGMOD |
33 |
0.00011468426 |
| 1,614 |
Compressed Linear Algebra for Large-Scale Machine Learning |
2016 |
VLDB |
31 |
0.00010067153 |
| 1,669 |
SystemDS: A Declarative Machine Learning System for the End-to-End Data Science Lifecycle |
2020 |
CIDR |
32 |
9.9324573e-05 |
| 2,329 |
SliceLine: Fast, Linear-Algebra-based Slice Finding for ML Model Debugging |
2021 |
SIGMOD |
11 |
8.6268411e-05 |
| 3,103 |
On Optimizing Operator Fusion Plans for Large-Scale Machine Learning in SystemML |
2018 |
VLDB |
25 |
7.6456038e-05 |
| 3,331 |
SPOOF: Sum-Product Optimization and Operator Fusion for Large-Scale Machine Learning |
2017 |
CIDR |
15 |
7.4138851e-05 |
| 4,117 |
Resource Elasticity for Large-Scale Machine Learning |
2015 |
SIGMOD |
14 |
6.7929814e-05 |
| 4,330 |
MNC: Structure-Exploiting Sparsity Estimation for Matrix Expressions |
2019 |
SIGMOD |
12 |
6.6564176e-05 |
| 4,334 |
LIMA: Fine-grained Lineage Tracing and Reuse in Machine Learning Systems |
2021 |
SIGMOD |
16 |
6.6537801e-05 |
| 5,574 |
Saga: A Scalable Framework for Optimizing Data Cleaning Pipelines for Machine Learning Applications |
2023 |
SIGMOD |
8 |
6.0773771e-05 |
| 6,666 |
UPLIFT: Parallelization Strategies for Feature Transformations in Machine Learning Workloads |
2022 |
VLDB |
7 |
5.7144587e-05 |
| 6,883 |
DAPHNE: An Open and Extensible System Infrastructure for Integrated Data Analysis Pipelines |
2022 |
CIDR |
6 |
5.6552024e-05 |
| 7,413 |
POLAR: Adaptive and Non-invasive Join Order Selection via Plans of Least Resistance |
2024 |
VLDB |
7 |
5.5316834e-05 |
| 7,843 |
ExDRa: Exploratory Data Science on Federated Raw Data |
2021 |
SIGMOD |
7 |
5.4406331e-05 |
| 8,389 |
AWARE: Workload-aware, Redundancy-exploiting Linear Algebra |
2023 |
SIGMOD |
4 |
5.3396465e-05 |
| 9,545 |
GIO: Generating Efficient Matrix and Frame Readers for Custom Data Formats by Example |
2023 |
SIGMOD |
1 |
5.1600923e-05 |
| 10,312 |
Fast and Scalable Data Transfer Across Data Systems |
2025 |
SIGMOD |
3 |
5.0376863e-05 |
| 10,826 |
FedAugment: Table Augmentation Search over Decentralized Data Repositories |
2026 |
VLDB |
0 |
4.9769913e-05 |
| 10,842 |
ReSequel: Robust LLM-assisted Query Rewriting and Optimization using Templatization and Sampling |
2026 |
VLDB |
0 |
4.9769913e-05 |
| 10,900 |
Matryoshka: Uncovering Relevant Features in Data Lakes to Enhance Machine Learning Applications |
2026 |
VLDB |
0 |
4.9769913e-05 |
| 10,954 |
Morphing-based Compression for Data-centric ML Pipelines |
2026 |
VLDB |
0 |
4.9769913e-05 |
| 11,292 |
CatDB: Data-catalog-guided, LLM-based Generation of Data-centric ML Pipelines |
2025 |
VLDB |
0 |
4.9769913e-05 |
| 11,403 |
Enter the Warp: Fast and Adaptive Data Transfer with XDBC |
2025 |
VLDB |
0 |
4.9769913e-05 |
| 12,695 |
Resiliency-Aware Data Management |
2011 |
VLDB |
1 |
4.9769913e-05 |
| 13,599 |
Demonstrating EarthLake: A Model Lake System for Earth Observation Foundation Model Management |
2026 |
VLDB |
0 |
- |
| 13,631 |
Demonstrating CatDB: LLM-based Generation of Data-centric ML Pipelines |
2025 |
SIGMOD |
0 |
- |
| 13,733 |
DEEM'22: Data Management for End-to-End Machine Learning |
2022 |
SIGMOD |
0 |
- |