Kasper Green Larsen
23 papers · 2018–2026 · 5 conferences · across top CS/AI conferences
Achievements
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๐ Academic Marathon (7) ๐ Interdisciplinary Bridge ๐งญ Keyword Pioneer ๐ Conference Polyglot (5) ๐ Cross-Pollinator (10)
๐ฃ
Hot Topic Early Bird
๐
Conference Polyglot
(5)
๐
Academic Marathon
(7)
๐
Keyword Champion
(4)
๐ฌ
Deep Specialist
(11)
๐ฅ
Unstoppable
(8)
โก
Prolific Year
(8)
๐
Century Club
(21)
โ
The Questioner
๐
Trend Setter
Conferences
NIPS (8)
ICML (7)
ALT (4)
COLT (3)
IJCAI (1)
Top co-authors
Keywords
sample complexity
(7)
boosting algorithm
(5)
ensemble learning
(4)
weak learner
(4)
ensemble method
(4)
generalization bound
(4)
strong learner
(3)
majority vote
(3)
pac learning
(3)
parallel computing
(2)
binary classification
(2)
computational complexity
(2)
feature hashing
(2)
dimensionality reduction
(2)
learning theory
(2)
margin theory
(2)
sparse projection
(2)
embedding learning
(1)
vc dimension
(1)
empirical risk minimization
(1)
Papers
Learning with Monotone Adversarial Corruptions
ALT 2026
Improved Replicable Boosting with Majority-of-Majorities
ALT 2026
Improved Margin Generalization Bounds for Voting Classifiers
COLT 2025
Boosting, Voting Classifiers and Randomized Sample Compression Schemes
ALT 2025
The Impossibility of Parallelizing Boosting
ALT 2024
Majority-of-Three: The Simplest Optimal Learner?
COLT 2024
Optimal Parallelization of Boosting
NIPS 2024
The Many Faces of Optimal Weak-to-Strong Learning
NIPS 2024
Derandomizing Multi-Distribution Learning
NIPS 2024
Sparse Dimensionality Reduction Revisited
ICML 2024
Replicable Learning of Large-Margin Halfspaces
ICML 2024
Bagging is an Optimal PAC Learner (Extended Abstract)
IJCAI 2024
The Fast Johnson-Lindenstrauss Transform Is Even Faster
ICML 2023
Bagging is an Optimal PAC Learner
COLT 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
Near-Tight Margin-Based Generalization Bounds for Support Vector Machines
ICML 2020
Margins are Insufficient for Explaining Gradient Boosting
NIPS 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