Maximilian Schleich

Orcid: 0009-0004-5502-869X

Affiliations:
  • University of Washington, WA, USA


According to our database1, Maximilian Schleich authored at least 22 papers between 2016 and 2024.

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Bibliography

2024
Optimizing Nested Recursive Queries.
Proc. ACM Manag. Data, February, 2024

2023
Optimizing Tensor Programs on Flexible Storage.
Proc. ACM Manag. Data, 2023

2022
Computing Rule-Based Explanations by Leveraging Counterfactuals.
Proc. VLDB Endow., 2022

2021
An Intermediate Representation for Hybrid Database and Machine Learning Workloads.
Proc. VLDB Endow., 2021

GeCo: Quality Counterfactual Explanations in Real Time.
Proc. VLDB Endow., 2021

Structure-Aware Machine Learning over Multi-Relational Databases.
Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

On the Tractability of SHAP Explanations.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Structure-aware machine learning over multi-relational databases.
PhD thesis, 2020

Learning Models over Relational Data Using Sparse Tensors and Functional Dependencies.
ACM Trans. Database Syst., 2020

LMFAO: An Engine for Batches of Group-By Aggregates.
Proc. VLDB Endow., 2020

Causality-based Explanation of Classification Outcomes.
Proceedings of the Fourth Workshop on Data Management for End-To-End Machine Learning, 2020

Multi-layer optimizations for end-to-end data analytics.
Proceedings of the CGO '20: 18th ACM/IEEE International Symposium on Code Generation and Optimization, 2020

Rk-means: Fast Clustering for Relational Data.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Learning Models over Relational Data: A Brief Tutorial.
Proceedings of the Scalable Uncertainty Management - 13th International Conference, 2019

A Layered Aggregate Engine for Analytics Workloads.
Proceedings of the 2019 International Conference on Management of Data, 2019

On Functional Aggregate Queries with Additive Inequalities.
Proceedings of the 38th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems, 2019

2018
AC/DC: In-Database Learning Thunderstruck.
Proceedings of the Second Workshop on Data Management for End-To-End Machine Learning, 2018

In-Database Learning with Sparse Tensors.
Proceedings of the 37th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems, 2018

2017
In-Database Factorized Learning.
Proceedings of the 11th Alberto Mendelzon International Workshop on Foundations of Data Management and the Web, 2017

2016
Factorized Databases.
SIGMOD Rec., 2016

F: Regression Models over Factorized Views.
Proc. VLDB Endow., 2016

Learning Linear Regression Models over Factorized Joins.
Proceedings of the 2016 International Conference on Management of Data, 2016


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