Mikael Møller Høgsgaard

26 papers A* 7A 1B 2Journal 16
YearRankTypeTitle / Venue / Authors
2026 J jnl
Agnostic Language Identification and Generation.
CoRR
Mikael Møller Høgsgaard, Chirag Pabbaraju
2026 J jnl
Sample-Near-Optimal Agnostic Boosting with Improved Running Time.
CoRR
Arthur da Cunha, Mikael Møller Høgsgaard, Andrea Paudice
2026 J jnl
The Optimal Sample Complexity of Linear Contracts.
CoRR
Mikael Møller Høgsgaard
2025 B conf
Efficient Optimal PAC Learning.
ALT
Mikael Møller Høgsgaard
2025 J jnl
Efficient Optimal PAC Learning.
CoRR
Mikael Møller Høgsgaard
2025 A* conf
Improved Margin Generalization Bounds for Voting Classifiers.
COLT
Mikael Møller Høgsgaard, Kasper Green Larsen
2025 J jnl
Improved Margin Generalization Bounds for Voting Classifiers.
CoRR
Mikael Møller Høgsgaard, Kasper Green Larsen
2025 J jnl
On Agnostic PAC Learning in the Small Error Regime.
CoRR
Julian Asilis, Mikael Møller Høgsgaard, Grigoris Velegkas
2025 J jnl
Revisiting Agnostic Boosting.
CoRR
Arthur da Cunha, Mikael Møller Høgsgaard, Andrea Paudice, Yuxin Sun
2025 B conf
Understanding Aggregations of Proper Learners in Multiclass Classification.
ALT
Julian Asilis, Mikael Møller Høgsgaard, Grigoris Velegkas
2025 A* conf
Uniform Mean Estimation for Heavy-Tailed Distributions via Median-of-Means.
ICML
Mikael Møller Høgsgaard, Andrea Paudice
2025 J jnl
Uniform Mean Estimation for Heavy-Tailed Distributions via Median-of-Means.
CoRR
Mikael Møller Høgsgaard, Andrea Paudice
2024 J jnl
Majority-of-Three: The Simplest Optimal Learner?
CoRR
Ishaq Aden-Ali, Mikael Møller Høgsgaard, Kasper Green Larsen, Nikita Zhivotovskiy
2024 A* conf
Optimal Parallelization of Boosting.
NeurIPS
Arthur da Cunha, Mikael Møller Høgsgaard, Kasper Green Larsen
2024 J jnl
Optimal Parallelization of Boosting.
CoRR
Arthur da Cunha, Mikael Møller Høgsgaard, Kasper Green Larsen
2024 A* conf
Sparse Dimensionality Reduction Revisited.
ICML
Mikael Møller Høgsgaard, Lior Kamma, Kasper Green Larsen, Jelani Nelson, Chris Schwiegelshohn
2024 A* conf
The Many Faces of Optimal Weak-to-Strong Learning.
NeurIPS
Mikael Møller Høgsgaard, Kasper Green Larsen, Markus Engelund Mathiasen
2024 J jnl
The Many Faces of Optimal Weak-to-Strong Learning.
CoRR
Mikael Møller Høgsgaard, Kasper Green Larsen, Markus Engelund Mathiasen
2024 J jnl
Understanding Aggregations of Proper Learners in Multiclass Classification.
CoRR
Julian Asilis, Mikael Møller Høgsgaard, Grigoris Velegkas
2023 A* conf
AdaBoost is not an Optimal Weak to Strong Learner.
ICML
Mikael Møller Høgsgaard, Kasper Green Larsen, Martin Ritzert
2023 J jnl
AdaBoost is not an Optimal Weak to Strong Learner.
CoRR
Mikael Møller Høgsgaard, Kasper Green Larsen, Martin Ritzert
2023 A conf
Barriers for Faster Dimensionality Reduction.
STACS
Ora Nova Fandina, Mikael Møller Høgsgaard, Kasper Green Larsen
2023 J jnl
Sparse Dimensionality Reduction Revisited.
CoRR
Mikael Møller Høgsgaard, Lior Kamma, Kasper Green Larsen, Jelani Nelson, Chris Schwiegelshohn
2023 A* conf
The Fast Johnson-Lindenstrauss Transform Is Even Faster.
ICML
Ora Nova Fandina, Mikael Møller Høgsgaard, Kasper Green Larsen
2022 J jnl
Barriers for Faster Dimensionality Reduction.
CoRR
Ora Nova Fandina, Mikael Møller Høgsgaard, Kasper Green Larsen
2022 J jnl
The Fast Johnson-Lindenstrauss Transform is Even Faster.
CoRR
Ora Nova Fandina, Mikael Møller Høgsgaard, Kasper Green Larsen