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Publication search results
found 50 matches
- 2021
- Lior Aloni, Omer Bobrowski, Ronen Talmon:
Joint Geometric and Topological Analysis of Hierarchical Datasets. ECML/PKDD (3) 2021: 478-493 - Philipp F. M. Baumann, Torsten Hothorn, David Rügamer:
Deep Conditional Transformation Models. ECML/PKDD (3) 2021: 3-18 - Jia Bi, Steve R. Gunn:
A Variance Controlled Stochastic Method with Biased Estimation for Faster Non-convex Optimization. ECML/PKDD (3) 2021: 135-150 - Sebastian Buschjäger, Philipp-Jan Honysz, Lukas Pfahler, Katharina Morik:
Very Fast Streaming Submodular Function Maximization. ECML/PKDD (3) 2021: 151-166 - Kan Chen, Zhiqi Bu, Shiyun Xu:
Asymptotic Statistical Analysis of Sparse Group LASSO via Approximate Message Passing. ECML/PKDD (3) 2021: 510-526 - Jiefeng Chen, Yixuan Li, Xi Wu, Yingyu Liang, Somesh Jha:
ATOM: Robustifying Out-of-Distribution Detection Using Outlier Mining. ECML/PKDD (3) 2021: 430-445 - Anton Chernyavskiy, Dmitry Ilvovsky, Preslav Nakov:
Transformers: "The End of History" for Natural Language Processing? ECML/PKDD (3) 2021: 677-693 - Ting-Wu Chin, Ari S. Morcos, Diana Marculescu:
Joslim: Joint Widths and Weights Optimization for Slimmable Neural Networks. ECML/PKDD (3) 2021: 119-134 - Samir Chowdhury, David Miller, Tom Needham:
Quantized Gromov-Wasserstein. ECML/PKDD (3) 2021: 811-827 - Soham Dan, Dushyant Sahoo:
Variance Reduced Stochastic Proximal Algorithm for AUC Maximization. ECML/PKDD (3) 2021: 184-199 - Jérémie Donà, Patrick Gallinari:
Differentiable Feature Selection, A Reparameterization Approach. ECML/PKDD (3) 2021: 414-429 - Nanqing Dong, Michael Kampffmeyer, Irina Voiculescu:
Self-supervised Multi-task Representation Learning for Sequential Medical Images. ECML/PKDD (3) 2021: 779-794 - Benoit Gaujac, Ilya Feige, David Barber:
Learning Disentangled Representations with the Wasserstein Autoencoder. ECML/PKDD (3) 2021: 69-84 - Victor Hamer, Pierre Dupont:
Robust Selection Stability Estimation in Correlated Spaces. ECML/PKDD (3) 2021: 446-461 - Zhiyong Hao, Yixuan Jiang, Huihua Yu, Hsiao-Dong Chiang:
Adaptive Learning Rate and Momentum for Training Deep Neural Networks. ECML/PKDD (3) 2021: 381-396 - Yerlan Idelbayev, Miguel Á. Carreira-Perpiñán:
More General and Effective Model Compression via an Additive Combination of Compressions. ECML/PKDD (3) 2021: 233-248 - Ekhine Irurozki, Aritz Pérez, Jesus L. Lobo, Javier Del Ser:
Rank Aggregation for Non-stationary Data Streams. ECML/PKDD (3) 2021: 297-313 - Endri Kacupaj, Shyamnath Premnadh, Kuldeep Singh, Jens Lehmann, Maria Maleshkova:
VOGUE: Answer Verbalization Through Multi-Task Learning. ECML/PKDD (3) 2021: 563-579 - Lucas Kania, Manuel Schürch, Dario Azzimonti, Alessio Benavoli:
Sparse Information Filter for Fast Gaussian Process Regression. ECML/PKDD (3) 2021: 527-542 - Arpita Kundu, Subhasis Ghosh, Indrajit Bhattacharya:
Semi-structured Document Annotation Using Entity and Relation Types. ECML/PKDD (3) 2021: 52-68 - Yang Li, Shihao Ji:
Dep-L0: Improving L0-Based Network Sparsification via Dependency Modeling. ECML/PKDD (3) 2021: 167-183 - Siyuan Li, Haitao Lin, Zelin Zang, Lirong Wu, Jun Xia, Stan Z. Li:
Invertible Manifold Learning for Dimension Reduction. ECML/PKDD (3) 2021: 713-728 - Jingzhou Liu, Yiming Yang:
Enhancing Summarization with Text Classification via Topic Consistency. ECML/PKDD (3) 2021: 661-676 - Yueming Lyu, Ivor W. Tsang:
Black-Box Optimizer with Stochastic Implicit Natural Gradient. ECML/PKDD (3) 2021: 217-232 - Simona Maggio, Léo Dreyfus-Schmidt:
Ensembling Shift Detectors: An Extensive Empirical Evaluation. ECML/PKDD (3) 2021: 362-377 - Lorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica, Navid Nobani:
TaxoRef: Embeddings Evaluation for AI-driven Taxonomy Refinement. ECML/PKDD (3) 2021: 612-627 - Armin Moharrer, Khashayar Kamran, Edmund Yeh, Stratis Ioannidis:
Robust Regression via Model Based Methods. ECML/PKDD (3) 2021: 200-216 - Phuoc Nguyen, Truyen Tran, Ky Le, Sunil Gupta, Santu Rana, Dang Nguyen, Trong Nguyen, Shannon Ryan, Svetha Venkatesh:
Fast Conditional Network Compression Using Bayesian HyperNetworks. ECML/PKDD (3) 2021: 330-345 - Manuel Nonnenmacher, David Reeb, Ingo Steinwart:
Which Minimizer Does My Neural Network Converge To? ECML/PKDD (3) 2021: 87-102 - Dang Pham, Tuan M. V. Le:
Neural Topic Models for Hierarchical Topic Detection and Visualization. ECML/PKDD (3) 2021: 35-51
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