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Publication search results
found 45 matches
- 2021
- Frank Hutter, Kristian Kersting, Jefrey Lijffijt, Isabel Valera:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020, Proceedings, Part III. Lecture Notes in Computer Science 12459, Springer 2021, ISBN 978-3-030-67663-6 [contents] - 2020
- Zilong Bai, S. S. Ravi, Ian Davidson:
Towards Description of Block Model on Graph. ECML/PKDD (3) 2020: 37-53 - Andreas Bender, David Rügamer, Fabian Scheipl, Bernd Bischl:
A General Machine Learning Framework for Survival Analysis. ECML/PKDD (3) 2020: 158-173 - Manliang Cao, Xiangdong Zhou, Lan Lin:
Soft Labels Transfer with Discriminative Representations Learning for Unsupervised Domain Adaptation. ECML/PKDD (3) 2020: 515-530 - Hau Chan, Grigorios Loukides, Zhenghui Su:
Algorithms for Optimizing the Ratio of Monotone k-Submodular Functions. ECML/PKDD (3) 2020: 3-19 - Tianyi Chen, Tianyu Ding, Bo Ji, Guanyi Wang, Yixin Shi, Jing Tian, Sheng Yi, Xiao Tu, Zhihui Zhu:
Orthant Based Proximal Stochastic Gradient Method for ℓ 1-Regularized Optimization. ECML/PKDD (3) 2020: 57-73 - Junyang Chen, Zhiguo Gong, Wei Wang, Xiao Dong, Wei Wang, Weiwen Liu, Cong Wang, Xian Chen:
Inductive Document Representation Learning for Short Text Clustering. ECML/PKDD (3) 2020: 600-616 - Lingwei Chen, Xiaoting Li, Dinghao Wu:
Enhancing Robustness of Graph Convolutional Networks via Dropping Graph Connections. ECML/PKDD (3) 2020: 412-428 - Lu Chen, Jiao Sun, Wei Xu:
FAWA: Fast Adversarial Watermark Attack on Optical Character Recognition (OCR) Systems. ECML/PKDD (3) 2020: 547-563 - Giorgio Corani, Dario Azzimonti, João P. S. C. Augusto, Marco Zaffalon:
Probabilistic Reconciliation of Hierarchical Forecast via Bayes' Rule. ECML/PKDD (3) 2020: 211-226 - Qi Deng, Chenghao Lan:
Efficiency of Coordinate Descent Methods for Structured Nonconvex Optimization. ECML/PKDD (3) 2020: 74-89 - Léo Gautheron, Pascal Germain, Amaury Habrard, Guillaume Metzler, Emilie Morvant, Marc Sebban, Valentina Zantedeschi:
Landmark-Based Ensemble Learning with Random Fourier Features and Gradient Boosting. ECML/PKDD (3) 2020: 141-157 - Gonzalo Hernández-Muñoz, Carlos Villacampa-Calvo, Daniel Hernández-Lobato:
Deep Gaussian Processes Using Expectation Propagation and Monte Carlo Methods. ECML/PKDD (3) 2020: 479-494 - James M. Hickey, Pietro G. Di Stefano, Vlasios Vasileiou:
Fairness by Explicability and Adversarial SHAP Learning. ECML/PKDD (3) 2020: 174-190 - Wenxin Hu, Xiaofeng Zhang, Yunpeng Ren:
Generating Financial Reports from Macro News via Multiple Edits Neural Networks. ECML/PKDD (3) 2020: 667-682 - Yugang Ji, Mingyang Yin, Yuan Fang, Hongxia Yang, Xiangwei Wang, Tianrui Jia, Chuan Shi:
Temporal Heterogeneous Interaction Graph Embedding for Next-Item Recommendation. ECML/PKDD (3) 2020: 314-329 - Ziyu Jia, Youfang Lin, Jing Wang, Kaixin Yang, Tianhang Liu, Xinwang Zhang:
MMCNN: A Multi-branch Multi-scale Convolutional Neural Network for Motor Imagery Classification. ECML/PKDD (3) 2020: 736-751 - Hongwei Jin, Xinhua Zhang:
Robust Training of Graph Convolutional Networks via Latent Perturbation. ECML/PKDD (3) 2020: 394-411 - Zixuan Ke, Bing Liu, Hao Wang, Lei Shu:
Continual Learning with Knowledge Transfer for Sentiment Classification. ECML/PKDD (3) 2020: 683-698 - Takuya Konishi, Takuro Fukunaga:
End-to-End Learning for Prediction and Optimization with Gradient Boosting. ECML/PKDD (3) 2020: 191-207 - Shiwei Liu, Tim van der Lee, Anil Yaman, Zahra Atashgahi, Davide Ferraro, Ghada Sokar, Mykola Pechenizkiy, Decebal Constantin Mocanu:
Topological Insights into Sparse Neural Networks. ECML/PKDD (3) 2020: 279-294 - Henry B. Moss, David S. Leslie, Paul Rayson:
MUMBO: MUlti-task Max-Value Bayesian Optimization. ECML/PKDD (3) 2020: 447-462 - Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung:
A Self-attention Network Based Node Embedding Model. ECML/PKDD (3) 2020: 364-377 - Xueping Peng, Guodong Long, Tao Shen, Sen Wang, Jing Jiang:
Self-attention Enhanced Patient Journey Understanding in Healthcare System. ECML/PKDD (3) 2020: 719-735 - Lorenzo Perini, Vincent Vercruyssen, Jesse Davis:
Quantifying the Confidence of Anomaly Detectors in Their Example-Wise Predictions. ECML/PKDD (3) 2020: 227-243 - Victor Picheny, Vincent Dutordoir, Artem Artemev, Nicolas Durrande:
Automatic Tuning of Stochastic Gradient Descent with Bayesian Optimisation. ECML/PKDD (3) 2020: 431-446 - Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz, Vu-Linh Nguyen, Eyke Hüllermeier:
Learning Gradient Boosted Multi-label Classification Rules. ECML/PKDD (3) 2020: 124-140 - Diederik M. Roijers, Luisa M. Zintgraf, Pieter Libin, Mathieu Reymond, Eugenio Bargiacchi, Ann Nowé:
Interactive Multi-objective Reinforcement Learning in Multi-armed Bandits with Gaussian Process Utility Models. ECML/PKDD (3) 2020: 463-478 - Polina Rozenshtein, Giulia Preti, Aristides Gionis, Yannis Velegrakis:
Mining Dense Subgraphs with Similar Edges. ECML/PKDD (3) 2020: 20-36 - Bruna Zamith Santos, Felipe Kenji Nakano, Ricardo Cerri, Celine Vens:
Predictive Bi-clustering Trees for Hierarchical Multi-label Classification. ECML/PKDD (3) 2020: 701-718
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