The BUDS Language for Distributed Bayesian Machine Learning
Summary: Declarative language for specifying distributed Bayesian ML algorithms; BUDS uses logical types (vectors, arrays) decoupled from their physical layout. The compiler co-optimizes data representation and concrete operation implementations (matmul, transpose, Hadamard), generating efficient, platform-aware code. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Zekai J. Gao
- 2. Shangyu Luo
- 3. Luis L. Perez
- 4. Chris Jermaine
Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,532 | Data Management in Machine Learning: Challenges, Techniques, and Systems | 2017 | SIGMOD | 0.00011472681 |
| 3,277 | A Layered Aggregate Engine for Analytics Workloads | 2019 | SIGMOD | 7.2871625e-05 |
| 6,745 | DistME: A Fast and Elastic Distributed Matrix Computation Engine using GPUs | 2019 | SIGMOD | 4.9417155e-05 |
| 10,571 | Quantum Data Management in the NISQ Era | 2025 | VLDB | 4.1945683e-05 |
| 10,976 | StarfishDB: a Query Execution Engine for Relational Probabilistic Programming | 2024 | SIGMOD | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 13 of 13 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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