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Publication search results
found 45 matches
- 2023
- Tim Bakker, Herke van Hoof, Max Welling:
Learning Objective-Specific Active Learning Strategies with Attentive Neural Processes. ECML/PKDD (1) 2023: 3-19 - Cheng Chen, Yong Wang, Lizi Liao, Yueguo Chen, Xiaoyong Du:
Real: A Representative Error-Driven Approach for Active Learning. ECML/PKDD (1) 2023: 20-37 - Debo Cheng, Ziqi Xu, Jiuyong Li, Lin Liu, Thuc Duy Le, Jixue Liu:
Learning Conditional Instrumental Variable Representation for Causal Effect Estimation. ECML/PKDD (1) 2023: 525-540 - Gabriele Ciravegna, Frédéric Precioso, Alessandro Betti, Kevin Mottin, Marco Gori:
Knowledge-Driven Active Learning. ECML/PKDD (1) 2023: 38-54 - Andrzej Dulny, Andreas Hotho, Anna Krause:
DynaBench: A Benchmark Dataset for Learning Dynamical Systems from Low-Resolution Data. ECML/PKDD (1) 2023: 438-455 - Anis Fradi, Chafik Samir:
A New Framework for Classifying Probability Density Functions. ECML/PKDD (1) 2023: 507-522 - Zhangyang Gao, Cheng Tan, Jun Xia, Stan Z. Li:
Co-supervised Pre-training of Pocket and Ligand. ECML/PKDD (1) 2023: 405-421 - Sandra Gilhuber, Julian Busch, Daniel Rotthues, Christian M. M. Frey, Thomas Seidl:
DiffusAL: Coupling Active Learning with Graph Diffusion for Label-Efficient Node Classification. ECML/PKDD (1) 2023: 75-91 - Sruthi Gorantla, Kishen N. Gowda, Amit Deshpande, Anand Louis:
Socially Fair Center-Based and Linear Subspace Clustering. ECML/PKDD (1) 2023: 727-742 - Jia Hu, Chu Wang, Xianghong Lin:
Spatio-Temporal Pyramid Networks for Traffic Forecasting. ECML/PKDD (1) 2023: 339-354 - Tianjin Huang, Shiwei Liu, Tianlong Chen, Meng Fang, Li Shen, Vlado Menkovski, Lu Yin, Yulong Pei, Mykola Pechenizkiy:
Enhancing Adversarial Training via Reweighting Optimization Trajectory. ECML/PKDD (1) 2023: 113-130 - Johannes Huegle, Christopher Hagedorn, Rainer Schlosser:
A KNN-Based Non-Parametric Conditional Independence Test for Mixed Data and Application in Causal Discovery. ECML/PKDD (1) 2023: 541-558 - Skander Karkar, Patrick Gallinari, Alain Rakotomamonjy:
Adversarial Sample Detection Through Neural Network Transport Dynamics. ECML/PKDD (1) 2023: 164-181 - Ali Khoshvishkaie, Petrus Mikkola, Pierre-Alexandre Murena, Samuel Kaski:
Cooperative Bayesian Optimization for Imperfect Agents. ECML/PKDD (1) 2023: 475-490 - Mauritius Klein, Collin Leiber, Christian Böhm:
k-SubMix: Common Subspace Clustering on Mixed-Type Data. ECML/PKDD (1) 2023: 662-677 - Qin Lei, Jiang Zhong, Chen Wang, Yang Xia, Yangmei Zhou:
Dynamic Thresholding for Accurate Crack Segmentation Using Multi-objective Optimization. ECML/PKDD (1) 2023: 389-404 - Jiaming Li, Lang Lang, Zhenlong Zhu, Haozhao Wang, Ruixuan Li, Wenchao Xu:
Decompose, Then Reconstruct: A Framework of Network Structures for Click-Through Rate Prediction. ECML/PKDD (1) 2023: 422-437 - Jindong Li, Qianli Xing, Qi Wang, Yi Chang:
CVTGAD: Simplified Transformer with Cross-View Attention for Unsupervised Graph-Level Anomaly Detection. ECML/PKDD (1) 2023: 185-200 - Chen Li, Yoshihiro Yamanishi:
SpotGAN: A Reverse-Transformer GAN Generates Scaffold-Constrained Molecules with Property Optimization. ECML/PKDD (1) 2023: 323-338 - Xiaofeng Lin, Guoxi Zhang, Xiaotian Lu, Han Bao, Koh Takeuchi, Hisashi Kashima:
Estimating Treatment Effects Under Heterogeneous Interference. ECML/PKDD (1) 2023: 576-592 - Fei Liu, Yibo Li, Meiyun Zuo:
KESHEM: Knowledge Enabled Short Health Misinformation Detection Framework. ECML/PKDD (1) 2023: 372-388 - Giulia Marchello, Marco Corneli, Charles Bouveyron:
A Deep Dynamic Latent Block Model for the Co-Clustering of Zero-Inflated Data Matrices. ECML/PKDD (1) 2023: 695-710 - Thibault Marette, Pauli Miettinen, Stefan Neumann:
Visualizing Overlapping Biclusterings and Boolean Matrix Factorizations. ECML/PKDD (1) 2023: 743-758 - Timo Martens, Lorenzo Perini, Jesse Davis:
Semi-supervised Learning from Active Noisy Soft Labels for Anomaly Detection. ECML/PKDD (1) 2023: 219-236 - Keizaburo Nishikino, Kenichi Kobayashi:
Adversarial Imitation Learning with Controllable Rewards for Text Generation. ECML/PKDD (1) 2023: 131-146 - Chaoxi Niu, Guansong Pang, Ling Chen:
Graph-Level Anomaly Detection via Hierarchical Memory Networks. ECML/PKDD (1) 2023: 201-218 - Corey J. Nolet, Divye Gala, Alexandre Fender, Mahesh Doijade, Joe Eaton, Edward Raff, John Zedlewski, Brad Rees, Tim Oates:
cuSLINK: Single-Linkage Agglomerative Clustering on the GPU. ECML/PKDD (1) 2023: 711-726 - Gaël Poux-Médard, Julien Velcin, Sabine Loudcher:
Powered Dirichlet Process - Controlling the "Rich-Get-Richer" Assumption in Bayesian Clustering. ECML/PKDD (1) 2023: 611-626 - Lukas Rauch, Matthias Aßenmacher, Denis Huseljic, Moritz Wirth, Bernd Bischl, Bernhard Sick:
ActiveGLAE: A Benchmark for Deep Active Learning with Transformers. ECML/PKDD (1) 2023: 55-74 - Breeshey Roskams-Hieter, Jude Wells, Sara Wade:
Leveraging Variational Autoencoders for Multiple Data Imputation. ECML/PKDD (1) 2023: 491-506
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