Moe Kayali

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 10

Top Topics

Relational Data

Top Venues

Proc. VLDB Endow.

SIGMOD Conference

Publications

Kyle Deeds, Diandre Sabale, Moe Kayali, Dan Suciu
Color: A Framework for Applying Graph Coloring to Subgraph Cardinality Estimation. CoRR (2024)
Çagatay Demiralp, Fabian Wenz, Peter Baile Chen, Moe Kayali, Nesime Tatbul, Michael Stonebraker
Making LLMs Work for Enterprise Data Tasks. CoRR (2024)
Moe Kayali, Anton Lykov, Ilias Fountalis, Nikolaos Vasiloglou, Dan Olteanu, Dan Suciu
CHORUS: Foundation Models for Unified Data Discovery and Exploration. Proc. VLDB Endow. 17 (8) (2024)
Moe Kayali, Anton Lykov, Ilias Fountalis, Nikolaos Vasiloglou, Dan Olteanu, Dan Suciu
CHORUS: Foundation Models for Unified Data Discovery and Exploration. CoRR (2023)
Moe Kayali, Chi Wang
Mining Robust Default Configurations for Resource-constrained AutoML. CoRR (2022)
Moe Kayali, Dan Suciu
Quasi-stable Coloring for Graph Compression: Approximating Max-Flow, Linear Programs, and Centrality. CoRR (2022)
Moe Kayali, Dan Suciu
Quasi-stable Coloring for Graph Compression: Approximating Max-Flow, Linear Programs, and Centrality. Proc. VLDB Endow. 16 (4) (2022)
Babak Salimi, Harsh Parikh, Moe Kayali, Sudeepa Roy, Lise Getoor, Dan Suciu
Causal Relational Learning. CoRR (2020)
Moe Kayali, Babak Salimi, Dan Suciu
Demonstration of Inferring Causality from Relational Databases with CaRL. Proc. VLDB Endow. 13 (12) (2020)
Babak Salimi, Harsh Parikh, Moe Kayali, Lise Getoor, Sudeepa Roy, Dan Suciu
Causal Relational Learning. SIGMOD Conference (2020)