Maximilian Schleich

According to our database, Maximilian Schleich authored at least 22 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Optimizing Nested Recursive Queries.

Amir Shaikhha, Dan Suciu, Maximilian Schleich, Hung Q. Ngo

Proc. ACM Manag. Data, February, 2024

2023

Optimizing Tensor Programs on Flexible Storage.

Maximilian Schleich, Amir Shaikhha, Dan Suciu

Proc. ACM Manag. Data, 2023

2022

Computing Rule-Based Explanations by Leveraging Counterfactuals.

Zixuan Geng, Maximilian Schleich, Dan Suciu

Proc. VLDB Endow., 2022

On the Tractability of SHAP Explanations.

Guy Van den Broeck, Anton Lykov, Maximilian Schleich, Dan Suciu

J. Artif. Intell. Res., 2022

2021

An Intermediate Representation for Hybrid Database and Machine Learning Workloads.

Amir Shaikhha, Maximilian Schleich, Dan Olteanu

Proc. VLDB Endow., 2021

GeCo: Quality Counterfactual Explanations in Real Time.

Maximilian Schleich, Zixuan Geng, Yihong Zhang, Dan Suciu

Proc. VLDB Endow., 2021

Structure-Aware Machine Learning over Multi-Relational Databases.

Maximilian Schleich

Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

2020

Structure-aware machine learning over multi-relational databases.

Maximilian-Joel Schleich

PhD thesis, 2020

Learning Models over Relational Data Using Sparse Tensors and Functional Dependencies.

Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich

ACM Trans. Database Syst., 2020

Functional Aggregate Queries with Additive Inequalities.

Mahmoud Abo Khamis, Ryan R. Curtin, Benjamin Moseley, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich

ACM Trans. Database Syst., 2020

LMFAO: An Engine for Batches of Group-By Aggregates.

Maximilian Schleich, Dan Olteanu

Proc. VLDB Endow., 2020

Causality-based Explanation of Classification Outcomes.

Leopoldo E. Bertossi, Jordan Li, Maximilian Schleich, Dan Suciu, Zografoula Vagena

Proceedings of the Fourth Workshop on Data Management for End-To-End Machine Learning, 2020

Multi-layer optimizations for end-to-end data analytics.

Amir Shaikhha, Maximilian Schleich, Alexandru Ghita, Dan Olteanu

Proceedings of the CGO '20: 18th ACM/IEEE International Symposium on Code Generation and Optimization, 2020

Rk-means: Fast Clustering for Relational Data.

Ryan R. Curtin, Benjamin Moseley, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Learning Models over Relational Data: A Brief Tutorial.

Maximilian Schleich, Dan Olteanu, Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen

Proceedings of the Scalable Uncertainty Management - 13th International Conference, 2019

A Layered Aggregate Engine for Analytics Workloads.

Maximilian Schleich, Dan Olteanu, Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen

Proceedings of the 2019 International Conference on Management of Data, 2019

2018

AC/DC: In-Database Learning Thunderstruck.

Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich

Proceedings of the Second Workshop on Data Management for End-To-End Machine Learning, 2018

In-Database Learning with Sparse Tensors.

Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich

Proceedings of the 37th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems, 2018

2017

In-Database Factorized Learning.

Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich

Proceedings of the 11th Alberto Mendelzon International Workshop on Foundations of Data Management and the Web, 2017

2016

Factorized Databases.

Dan Olteanu, Maximilian Schleich

SIGMOD Rec., 2016

F: Regression Models over Factorized Views.

Dan Olteanu, Maximilian Schleich

Proc. VLDB Endow., 2016

Learning Linear Regression Models over Factorized Joins.

Maximilian Schleich, Dan Olteanu, Radu Ciucanu

Proceedings of the 2016 International Conference on Management of Data, 2016