Erik Schultheis
6 papers · 2022–2025 · 3 venues · across top CS/AI venues
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Achievements
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Conference Polyglot · Bronze
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Interdisciplinary Bridge · Bronze
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Taxonomy Completionist
(11)
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Triple Crown
Venues
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Research topics
Machine Learning
(5)
Core Methods
(5)
Optimization & Theory · Machine Learning
(3)
Artificial Intelligence
(1)
Deep Learning
(1)
Mathematics & Optimization
(1)
Natural Language Processing
(1)
Application Areas
(1)
Applications
(1)
Core AI
(1)
Learning Paradigms
(1)
Learning Types
(1)
Optimization
(1)
Optimization & Theory · Deep Learning
(1)
Keywords
extreme multi-label classification
(2)
multi-label classification
(2)
efficient computing
(1)
large-scale classification
(1)
label prediction
(1)
label tree
(1)
confusion matrix
(1)
regret
(1)
regret bound
(1)
online algorithm
(1)
f-measure
(1)
dynamic sparse training
(1)
low-precision training
(1)
frank-wolfe method
(1)
multi-resolution learning
(1)
precision at k
(1)
propensity scoring
(1)
long-tail learning
(1)
stochastic rounding
(1)
gradient fusion
(1)
Papers
ELMO : Efficiency via Low-precision and Peak Memory Optimization in Large Output Spaces
ICML 2025
A General Online Algorithm for Optimizing Complex Performance Metrics
ICML 2024
Consistent algorithms for multi-label classification with macro-at-k metrics
ICLR 2024
Navigating Extremes: Dynamic Sparsity in Large Output Spaces
NeurIPS 2024
Generalized test utilities for long-tail performance in extreme multi-label classification
NeurIPS 2023
CascadeXML: Rethinking Transformers for End-to-end Multi-resolution Training in Extreme Multi-label Classification
NeurIPS 2022