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ORCIDMaximilian Schleich
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- affiliation: University of Washington, WA, USA
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2020 – today
- 2024
[j11]Amir Shaikhha
, Dan Suciu, Maximilian Schleich, Hung Q. Ngo:
Optimizing Nested Recursive Queries. Proc. ACM Manag. Data 2(1): 16:1-16:27 (2024)- 2023
- [j10]Maximilian Schleich, Amir Shaikhha, Dan Suciu:
Optimizing Tensor Programs on Flexible Storage. Proc. ACM Manag. Data 1(1): 37:1-37:27 (2023) - 2022
- [j9]Guy Van den Broeck, Anton Lykov, Maximilian Schleich, Dan Suciu:
On the Tractability of SHAP Explanations. J. Artif. Intell. Res. 74: 851-886 (2022) - [j8]Zixuan Geng, Maximilian Schleich, Dan Suciu:
Computing Rule-Based Explanations by Leveraging Counterfactuals. Proc. VLDB Endow. 16(3): 420-432 (2022) - [i13]Maximilian Schleich, Amir Shaikhha, Dan Suciu:
Optimizing Tensor Programs on Flexible Storage. CoRR abs/2210.06267 (2022) - [i12]Zixuan Geng, Maximilian Schleich, Dan Suciu:
Computing Rule-Based Explanations by Leveraging Counterfactuals. CoRR abs/2210.17071 (2022) - 2021
- [j7]Maximilian Schleich, Zixuan Geng, Yihong Zhang, Dan Suciu:
GeCo: Quality Counterfactual Explanations in Real Time. Proc. VLDB Endow. 14(9): 1681-1693 (2021) - [j6]Amir Shaikhha, Maximilian Schleich, Dan Olteanu:
An Intermediate Representation for Hybrid Database and Machine Learning Workloads. Proc. VLDB Endow. 14(12): 2831-2834 (2021) - [c12]Guy Van den Broeck, Anton Lykov, Maximilian Schleich, Dan Suciu:
On the Tractability of SHAP Explanations. AAAI 2021: 6505-6513 - [c11]Maximilian Schleich:
Structure-Aware Machine Learning over Multi-Relational Databases. SIGMOD Conference 2021: 6-7 - [i11]Maximilian Schleich, Zixuan Geng, Yihong Zhang, Dan Suciu:
GeCo: Quality Counterfactual Explanations in Real Time. CoRR abs/2101.01292 (2021) - 2020
- [b1]Maximilian-Joel Schleich:
Structure-aware machine learning over multi-relational databases. University of Oxford, UK, 2020 - [j5]Maximilian Schleich, Dan Olteanu:
LMFAO: An Engine for Batches of Group-By Aggregates. Proc. VLDB Endow. 13(12): 2945-2948 (2020) - [j4]Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich:
Learning Models over Relational Data Using Sparse Tensors and Functional Dependencies. ACM Trans. Database Syst. 45(2): 7:1-7:66 (2020) - [j3]Mahmoud Abo Khamis, Ryan R. Curtin, Benjamin Moseley, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich:
Functional Aggregate Queries with Additive Inequalities. ACM Trans. Database Syst. 45(4): 17:1-17:41 (2020) - [c10]Ryan R. Curtin, Benjamin Moseley, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich:
Rk-means: Fast Clustering for Relational Data. AISTATS 2020: 2742-2752 - [c9]Amir Shaikhha, Maximilian Schleich, Alexandru Ghita, Dan Olteanu:
Multi-layer optimizations for end-to-end data analytics. CGO 2020: 145-157 - [c8]Leopoldo E. Bertossi, Jordan Li, Maximilian Schleich, Dan Suciu, Zografoula Vagena:
Causality-based Explanation of Classification Outcomes. DEEM@SIGMOD 2020: 6:1-6:10 - [i10]Amir Shaikhha, Maximilian Schleich, Alexandru Ghita, Dan Olteanu:
Multi-layer Optimizations for End-to-End Data Analytics. CoRR abs/2001.03541 (2020) - [i9]Leopoldo E. Bertossi, Jordan Li, Maximilian Schleich, Dan Suciu, Zografoula Vagena:
Causality-based Explanation of Classification Outcomes. CoRR abs/2003.06868 (2020) - [i8]Maximilian Schleich, Dan Olteanu:
LMFAO: An Engine for Batches of Group-By Aggregates. CoRR abs/2008.08657 (2020) - [i7]Guy Van den Broeck, Anton Lykov, Maximilian Schleich, Dan Suciu:
On the Tractability of SHAP Explanations. CoRR abs/2009.08634 (2020)
2010 – 2019
- 2019
- [c7]Mahmoud Abo Khamis, Ryan R. Curtin, Benjamin Moseley, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich:
On Functional Aggregate Queries with Additive Inequalities. PODS 2019: 414-431 - [c6]Maximilian Schleich, Dan Olteanu, Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen:
A Layered Aggregate Engine for Analytics Workloads. SIGMOD Conference 2019: 1642-1659 - [c5]Maximilian Schleich, Dan Olteanu, Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen:
Learning Models over Relational Data: A Brief Tutorial. SUM 2019: 423-432 - [i6]Maximilian Schleich, Dan Olteanu, Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen:
A Layered Aggregate Engine for Analytics Workloads. CoRR abs/1906.08687 (2019) - [i5]Ryan R. Curtin, Benjamin Moseley, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich:
Rk-means: Fast Clustering for Relational Data. CoRR abs/1910.04939 (2019) - [i4]Maximilian Schleich, Dan Olteanu, Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen:
Learning Models over Relational Data: A Brief Tutorial. CoRR abs/1911.06577 (2019) - 2018
- [c4]Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich:
In-Database Learning with Sparse Tensors. PODS 2018: 325-340 - [c3]Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich:
AC/DC: In-Database Learning Thunderstruck. DEEM@SIGMOD 2018: 8:1-8:10 - [i3]Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich:
AC/DC: In-Database Learning Thunderstruck. CoRR abs/1803.07480 (2018) - [i2]Mahmoud Abo Khamis, Ryan R. Curtin, Benjamin Moseley, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich:
On Functional Aggregate Queries with Additive Inequalities. CoRR abs/1812.09526 (2018) - 2017
- [c2]Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich:
In-Database Factorized Learning. AMW 2017 - [i1]Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich:
In-Database Learning with Sparse Tensors. CoRR abs/1703.04780 (2017) - 2016
- [j2]Dan Olteanu, Maximilian Schleich:
F: Regression Models over Factorized Views. Proc. VLDB Endow. 9(13): 1573-1576 (2016) - [j1]Dan Olteanu, Maximilian Schleich:
Factorized Databases. SIGMOD Rec. 45(2): 5-16 (2016) - [c1]Maximilian Schleich, Dan Olteanu, Radu Ciucanu:
Learning Linear Regression Models over Factorized Joins. SIGMOD Conference 2016: 3-18
Coauthor Index
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