← Authors

Kasper Green Larsen

21 papers · 2018–2025 · 5 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (30) 🧭 Keyword Pioneer 🐝 Cross-Pollinator (10) 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (5) πŸƒ Academic Marathon (7) πŸ† Keyword Champion (4) πŸ”¬ Deep Specialist (11) πŸ”₯ Unstoppable (8) ⚑ Prolific Year (8) πŸ’Ž Century Club (21) ❓ The Questioner πŸ“ˆ Trend Setter

Conferences

NIPS (8) ICML (7) COLT (3) ALT (2) IJCAI (1)

Top co-authors

Mikael MΓΈller HΓΈgsgaard (5) Lior Kamma (5) Allan GrΓΈnlund (4) Martin Ritzert (3) Chris Schwiegelshohn (2) Arthur da Cunha (2) Alexander Mathiasen (2) Amin Karbasi (2) Nikita Zhivotovskiy (2) Jelani Nelson (2)

Keywords

sample complexity (6) generalization bound (4) ensemble method (4) weak learner (4) boosting algorithm (4) ensemble learning (4) pac learning (3) majority vote (3) strong learner (3) parallel computing (2) dimensionality reduction (2) computational complexity (2) sparse projection (2) feature hashing (2) learning theory (2) margin theory (2) embedding learning (1) vc dimension (1) empirical risk minimization (1) statistical learning theory (1)

Papers

Improved Margin Generalization Bounds for Voting Classifiers COLT 2025
Boosting, Voting Classifiers and Randomized Sample Compression Schemes ALT 2025
Replicable Learning of Large-Margin Halfspaces ICML 2024
Sparse Dimensionality Reduction Revisited ICML 2024
Majority-of-Three: The Simplest Optimal Learner? COLT 2024
The Many Faces of Optimal Weak-to-Strong Learning NIPS 2024
Derandomizing Multi-Distribution Learning NIPS 2024
The Impossibility of Parallelizing Boosting ALT 2024
Optimal Parallelization of Boosting NIPS 2024
Bagging is an Optimal PAC Learner (Extended Abstract) IJCAI 2024
Bagging is an Optimal PAC Learner COLT 2023
The Fast Johnson-Lindenstrauss Transform Is Even Faster ICML 2023
AdaBoost is not an Optimal Weak to Strong Learner ICML 2023
Improved Coresets for Euclidean $k$-Means NIPS 2022
Optimal Weak to Strong Learning NIPS 2022
CountSketches, Feature Hashing and the Median of Three ICML 2021
Margins are Insufficient for Explaining Gradient Boosting NIPS 2020
Near-Tight Margin-Based Generalization Bounds for Support Vector Machines ICML 2020
Margin-Based Generalization Lower Bounds for Boosted Classifiers NIPS 2019
Optimal Minimal Margin Maximization with Boosting ICML 2019
Fully Understanding The Hashing Trick NIPS 2018