Learning Linear Regression Models over Factorized Joins. - Maximilian Schleich; Dan Olteanu; Radu Ciucanu (SIGMOD Conference, 2016)

F: Regression Models over Factorized Views. - Dan Olteanu; Maximilian Schleich (Proc. VLDB Endow., 2016)

Factorized Databases. - Dan Olteanu; Maximilian Schleich (SIGMOD Rec., 2016)

In-Database Factorized Learning. - Hung Q. Ngo 001; XuanLong Nguyen; Dan Olteanu; Maximilian Schleich (AMW, 2017)

In-Database Learning with Sparse Tensors. - Mahmoud Abo Khamis; Hung Q. Ngo 001; XuanLong Nguyen; Dan Olteanu; Maximilian Schleich (PODS, 2018)

AC/DC: In-Database Learning Thunderstruck. - Mahmoud Abo Khamis; Hung Q. Ngo 001; XuanLong Nguyen; Dan Olteanu; Maximilian Schleich (DEEM@SIGMOD, 2018)

A Layered Aggregate Engine for Analytics Workloads. - Maximilian Schleich; Dan Olteanu; Mahmoud Abo Khamis; Hung Q. Ngo 001; XuanLong Nguyen (SIGMOD Conference, 2019)

Learning Models over Relational Data: A Brief Tutorial. - Maximilian Schleich; Dan Olteanu; Mahmoud Abo Khamis; Hung Q. Ngo 001; XuanLong Nguyen (SUM, 2019)

Rk-means: Fast Clustering for Relational Data. - Ryan R. Curtin; Benjamin Moseley; Hung Q. Ngo 001; XuanLong Nguyen; Dan Olteanu; Maximilian Schleich (AISTATS, 2020)

Multi-layer optimizations for end-to-end data analytics. - Amir Shaikhha; Maximilian Schleich; Alexandru Ghita; Dan Olteanu (CGO, 2020)

Causality-based Explanation of Classification Outcomes. - Leopoldo E. Bertossi; Jordan Li; Maximilian Schleich; Dan Suciu; Zografoula Vagena (DEEM@SIGMOD, 2020)

LMFAO: An Engine for Batches of Group-By Aggregates. - Maximilian Schleich; Dan Olteanu (Proc. VLDB Endow., 2020)

Functional Aggregate Queries with Additive Inequalities. - Mahmoud Abo Khamis; Ryan R. Curtin; Benjamin Moseley; Hung Q. Ngo 001; XuanLong Nguyen; Dan Olteanu; Maximilian Schleich (ACM Trans. Database Syst., 2020)

Learning Models over Relational Data Using Sparse Tensors and Functional Dependencies. - Mahmoud Abo Khamis; Hung Q. Ngo 001; XuanLong Nguyen; Dan Olteanu; Maximilian Schleich (ACM Trans. Database Syst., 2020)

Structure-aware machine learning over multi-relational databases. - Maximilian-Joel Schleich (2020)

Structure-Aware Machine Learning over Multi-Relational Databases. - Maximilian Schleich (SIGMOD Conference, 2021)

GeCo: Quality Counterfactual Explanations in Real Time. - Maximilian Schleich; Zixuan Geng; Yihong Zhang 004; Dan Suciu (Proc. VLDB Endow., 2021)

An Intermediate Representation for Hybrid Database and Machine Learning Workloads. - Amir Shaikhha; Maximilian Schleich; Dan Olteanu (Proc. VLDB Endow., 2021)

On the Tractability of SHAP Explanations. - Guy Van den Broeck; Anton Lykov; Maximilian Schleich; Dan Suciu (J. Artif. Intell. Res., 2022)

Computing Rule-Based Explanations by Leveraging Counterfactuals. - Zixuan Geng; Maximilian Schleich; Dan Suciu (Proc. VLDB Endow., 2022)

Optimizing Tensor Programs on Flexible Storage. - Maximilian Schleich; Amir Shaikhha; Dan Suciu (Proc. ACM Manag. Data, 2023)

Optimizing Nested Recursive Queries. - Amir Shaikhha; Dan Suciu; Maximilian Schleich; Hung Q. Ngo 001 (Proc. ACM Manag. Data, 2024)