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Alexander Mey
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2020 – today
- 2024
- [i11]Alexander Mey, Rui Manuel Castro:
Invariant Causal Prediction with Locally Linear Models. CoRR abs/2401.05218 (2024) - 2023
- [j1]Alexander Mey
, Marco Loog
Improved Generalization in Semi-Supervised Learning: A Survey of Theoretical Results. IEEE Trans. Pattern Anal. Mach. Intell. 45(4): 4747-4767 (2023) - 2021
- [c10]Alexander Mey, Marco Loog:
Consistency and Finite Sample Behavior of Binary Class Probability Estimation. AAAI 2021: 8967-8974 - [c9]Alexander Mey, Frans A. Oliehoek:
Environment Shift Games: Are Multiple Agents the Solution, and not the Problem, to Non-Stationarity? AAMAS 2021: 23-27 - [c8]Elena Congeduti, Alexander Mey, Frans A. Oliehoek:
Loss Bounds for Approximate Influence-Based Abstraction. AAMAS 2021: 377-385 - 2020
- [c7]Alexander Mey
A Distribution Dependent and Independent Complexity Analysis of Manifold Regularization. IDA 2020: 326-338 - [c6]Tom Julian Viering
Making Learners (More) Monotone. IDA 2020: 535-547 - [c5]Julius von Kügelgen, Alexander Mey
Semi-supervised learning, causality, and the conditional cluster assumption. UAI 2020: 1-10 - [i10]Marco Loog, Tom J. Viering, Alexander Mey, Jesse H. Krijthe, David M. J. Tax:
A Brief Prehistory of Double Descent. CoRR abs/2004.04328 (2020) - [i9]Alexander Mey
A Note on High-Probability versus In-Expectation Guarantees of Generalization Bounds in Machine Learning. CoRR abs/2010.02576 (2020) - [i8]Elena Congeduti, Alexander Mey, Frans A. Oliehoek:
Loss Bounds for Approximate Influence-Based Abstraction. CoRR abs/2011.01788 (2020)
2010 – 2019
- 2019
- [c4]Julius von Kügelgen, Alexander Mey
Semi-Generative Modelling: Covariate-Shift Adaptation with Cause and Effect Features. AISTATS 2019: 1361-1369 - [c3]Tom J. Viering, Alexander Mey
Open Problem: Monotonicity of Learning. COLT 2019: 3198-3201 - [c2]Marco Loog, Tom J. Viering, Alexander Mey
Minimizers of the Empirical Risk and Risk Monotonicity. NeurIPS 2019: 7476-7485 - [i7]Julius von Kügelgen, Marco Loog, Alexander Mey, Bernhard Schölkopf:
Semi-Supervised Learning, Causality and the Conditional Cluster Assumption. CoRR abs/1905.12081 (2019) - [i6]Alexander Mey, Tom J. Viering, Marco Loog:
A Distribution Dependent and Independent Complexity Analysis of Manifold Regularization. CoRR abs/1906.06100 (2019) - [i5]Marco Loog, Tom J. Viering, Alexander Mey:
Minimizers of the Empirical Risk and Risk Monotonicity. CoRR abs/1907.05476 (2019) - [i4]Alexander Mey
Improvability Through Semi-Supervised Learning: A Survey of Theoretical Results. CoRR abs/1908.09574 (2019) - [i3]Alexander Mey, Marco Loog:
Consistency and Finite Sample Behavior of Binary Class Probability Estimation. CoRR abs/1908.11823 (2019) - [i2]Tom J. Viering, Alexander Mey, Marco Loog:
Making Learners (More) Monotone. CoRR abs/1911.11030 (2019) - 2018
- [i1]Julius von Kügelgen, Alexander Mey, Marco Loog:
Semi-Generative Modelling: Domain Adaptation with Cause and Effect Features. CoRR abs/1807.07879 (2018) - 2016
- [c1]Alexander Mey
A soft-labeled self-training approach. ICPR 2016: 2604-2609
Coauthor Index
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