Erik Schultheis
Doctoral Researcher
Doctoral Researcher
T313 Dept. Computer Science
Full researcher profile
https://research.aalto.fi/...
Contact information
Email
[email protected]
Honors and awards
NeurIPS 2021 Outstanding Reviewer Award
Award or honor granted for a specific work
School common, SCI
Oct 2021
Research groups
- Professorship Babbar Rohit, Doctoral Researcher
Publications
CascadeXML: Rethinking Transformers for End-to-end Multi-resolution Training in Extreme Multi-label Classification
Siddhant Kharbanda, Atmadeep Banerjee, Erik Schultheis, Rohit Babbar
2022
Advances in Neural Information Processing Systems 35 (NeurIPS 2022)
Beyond Standard Performance Measures in Extreme Multi-label Classification
Erik Schultheis, Marek Wydmuch, Rohit Babbar, Krzysztof Dembczynski
2022
CascadeXML : Rethinking Transformers for End-to-end Multi-resolution Extreme Multi-label Classification
Erik Schultheis
2022
On Missing Labels, Long-tails and Propensities in Extreme Multi-label Classification
Erik Schultheis, Rohit Babbar, Marek Wydmuch, Krzysztof Dembczynski
2022
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
Speeding-up one-versus-all training for extreme classification via mean-separating initialization
Erik Schultheis, Rohit Babbar
2022
Machine Learning
Convex Surrogates for Unbiased Loss Functions in Extreme Classification With Missing Labels
Mohammadreza Mohammadnia Qaraei, Erik Schultheis, Priyanshu Gupta, Rohit Babbar
2021
The Web Conference 2021 - Proceedings of the World Wide Web Conference, WWW 2021
Speeding-up One-vs-All Training for Extreme Classification via Smart Initialization
Erik Schultheis, Rohit Babbar
2021
Unbiased Loss Functions for Multilabel Classification with Missing Labels
Erik Schultheis, Rohit Babbar
2021
Unbiased Loss Functions for Extreme Classification With Missing Labels
Erik Schultheis, Mohammadreza Mohammadnia Qaraei, Priyanshu Gupta, Rohit Babbar
2020