Generating artificial displacement data of cracked specimen using physics-guided adversarial networks von Melching, David, Schultheis, Erik, Breitbarth, Eric

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Speeding-up one-versus-all training for extreme classification via mean-separating initialization von Schultheis, Erik, Babbar, Rohit

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Towards Memory-Efficient Training for Extremely Large Output Spaces – Learning with 670k Labels on a Single Commodity GPU von Schultheis, Erik, Babbar, Rohit

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Channeling of Branched Flow in Weakly Scattering Anisotropic Media von Degueldre, Henri, Metzger, Jakob J, Schultheis, Erik, Fleischmann, Ragnar

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Towards Memory-Efficient Training for Extremely Large Output Spaces -- Learning with 500k Labels on a Single Commodity GPU von Schultheis, Erik, Babbar, Rohit

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Speeding-up One-vs-All Training for Extreme Classification via Smart Initialization von Schultheis, Erik, Babbar, Rohit

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Unbiased Loss Functions for Multilabel Classification with Missing Labels von Schultheis, Erik, Babbar, Rohit

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Generating artificial digital image correlation data using physics-guided adversarial networks von Melching, David, Schultheis, Erik, Breitbarth, Eric

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Correction to: Towards Memory-Efficient Training for Extremely Large Output Spaces – Learning with 670k Labels on a Single Commodity GPU von Schultheis, Erik, Babbar, Rohit

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Labels in Extremes: How Well Calibrated are Extreme Multi-label Classifiers? von Ullah, Nasib, Schultheis, Erik, Zhang, Jinbin, Babbar, Rohit

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Navigating Extremes: Dynamic Sparsity in Large Output Space von Ullah, Nasib, Schultheis, Erik, Lasby, Mike, Ioannou, Yani, Babbar, Rohit

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Machine Learning under Resource Constraints - Fundamentals von Katharina Morik, Peter Marwedel, Katharina Morik, Peter Marwedel, Jens Buß, Andreas Becker

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Fast gradient-free optimization of excitations in variational quantum eigensolvers von Jäger, Jonas, Kaldenbach, Thierry Nicolas, Haas, Max, Schultheis, Erik

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A General Online Algorithm for Optimizing Complex Performance Metrics von Kotłowski, Wojciech, Wydmuch, Marek, Schultheis, Erik, Babbar, Rohit, Dembczyński, Krzysztof

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Generalized test utilities for long-tail performance in extreme multi-label classification von Schultheis, Erik, Wydmuch, Marek, Kotłowski, Wojciech, Babbar, Rohit, Dembczyński, Krzysztof

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CascadeXML: Rethinking Transformers for End-to-end Multi-resolution Training in Extreme Multi-label Classification von Kharbanda, Siddhant, Banerjee, Atmadeep, Schultheis, Erik, Babbar, Rohit

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Learning label-label correlations in Extreme Multi-label Classification via Label Features von Kharbanda, Siddhant, Gupta, Devaansh, Schultheis, Erik, Banerjee, Atmadeep, Hsieh, Cho-Jui, Babbar, Rohit

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On Missing Labels, Long-tails and Propensities in Extreme Multi-label Classification von Schultheis, Erik, Wydmuch, Marek, Babbar, Rohit, Dembczyński, Krzysztof

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Unbiased Loss Functions for Multilabel Classification with Missing Labels von Schultheis, Erik, Babbar, Rohit

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Consistent algorithms for multi-label classification with macro-at-$k$ metrics von Schultheis, Erik, Kotłowski, Wojciech, Wydmuch, Marek, Babbar, Rohit, Borman, Strom, Dembczyński, Krzysztof

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