Mikael Møller Høgsgaard

8 papers · 2023–2026 · 3 venues · across top CS/AI venues

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Achievements

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🌍 Conference Polyglot · Bronze 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (13)

Venues

ICML (4) ALT (2) NeurIPS (2)

Top co-authors

Kasper Green Larsen (5) Andrea Paudice (2) Arthur da Cunha (2) Lior Kamma (1) Jelani Nelson (1) Julian Asilis (1) Grigoris Velegkas (1) Chris Schwiegelshohn (1) Ora Nova Fandina (1) Martin Ritzert (1)

Research topics

Machine Learning (7) Optimization & Theory (7) Mathematics & Optimization (4) Core Methods (4) Mathematics (3) Learning Types · Machine Learning (2) Optimization (2) Deep Learning (1) Application Areas (1) Learning Types · Deep Learning (1)

Keywords

sample complexity (5) boosting algorithm (3) weak learner (2) ensemble learning (2) dimensionality reduction (2) majority vote (1) parallel computing (1) multi-class classification (1) linear regression (1) sparse matrix (1) ensemble method (1) heavy-tailed distribution (1) weak-to-strong learning (1) johnson-lindenstrauss transform (1) sparse embedding (1) weak classifier (1) strong learner (1) weak-to-strong learner (1) hadamard matrix (1) johnson-lindenstrauss lemma (1)

Papers

Sample-Near-Optimal Agnostic Boosting with Improved Running Time ALT 2026 Understanding Aggregations of Proper Learners in Multiclass Classification ALT 2025 Uniform Mean Estimation for Heavy-Tailed Distributions via Median-of-Means ICML 2025 Optimal Parallelization of Boosting NeurIPS 2024 Sparse Dimensionality Reduction Revisited ICML 2024 The Many Faces of Optimal Weak-to-Strong Learning NeurIPS 2024 AdaBoost is not an Optimal Weak to Strong Learner ICML 2023 The Fast Johnson-Lindenstrauss Transform Is Even Faster ICML 2023