ECML/PKDD (1)

Keyphrases

Publications

2023

Krzysztof Rudas, Szymon Jaroszewicz
Regularization for Uplift Regression. ECML/PKDD (1) (2023)
Paras Sheth, Tharindu Kumarage, Raha Moraffah, Aman Chadha, Huan Liu
PEACE: Cross-Platform Hate Speech Detection - A Causality-Guided Framework. ECML/PKDD (1) (2023)
Gaël Poux-Médard, Julien Velcin, Sabine Loudcher
Powered Dirichlet Process - Controlling the "Rich-Get-Richer" Assumption in Bayesian Clustering. ECML/PKDD (1) (2023)
Jia Hu, Chu Wang, Xianghong Lin
Spatio-Temporal Pyramid Networks for Traffic Forecasting. ECML/PKDD (1) (2023)
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)
Mingyu Zhao, Weidong Yang, Feiping Nie
Transformer-Based Contrastive Multi-view Clustering via Ensembles. ECML/PKDD (1) (2023)
Sruthi Gorantla, Kishen N. Gowda, Amit Deshpande, Anand Louis
Socially Fair Center-Based and Linear Subspace Clustering. ECML/PKDD (1) (2023)
Chen Li, Yoshihiro Yamanishi
SpotGAN: A Reverse-Transformer GAN Generates Scaffold-Constrained Molecules with Property Optimization. ECML/PKDD (1) (2023)
Anastasiia Sedova, Lena Zellinger, Benjamin Roth
Learning with Noisy Labels by Adaptive Gradient-Based Outlier Removal. ECML/PKDD (1) (2023)
Jingrui Zhang, Ninh D. Pham, Gillian Dobbie
A Transductive Forest for Anomaly Detection with Few Labels. ECML/PKDD (1) (2023)
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)
Yimei Zheng, Caiyan Jia, Jian Yu
Contrastive Learning with Cluster-Preserving Augmentation for Attributed Graph Clustering. ECML/PKDD (1) (2023)
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)
Cheng Chen, Yong Wang, Lizi Liao, Yueguo Chen, Xiaoyong Du
Real: A Representative Error-Driven Approach for Active Learning. ECML/PKDD (1) (2023)
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)
Zhiyu Zhu, Jiayu Zhang, Zhibo Jin, Xinyi Wang, Minhui Xue, Jun Shen, Kim-Kwang Raymond Choo, Huaming Chen
Towards Minimising Perturbation Rate for Adversarial Machine Learning with Pruning. ECML/PKDD (1) (2023)
Breeshey Roskams-Hieter, Jude Wells, Sara Wade
Leveraging Variational Autoencoders for Multiple Data Imputation. ECML/PKDD (1) (2023)
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)
Qin Lei, Jiang Zhong, Chen Wang, Yang Xia, Yangmei Zhou
Dynamic Thresholding for Accurate Crack Segmentation Using Multi-objective Optimization. ECML/PKDD (1) (2023)
Xiaofeng Lin, Guoxi Zhang, Xiaotian Lu, Han Bao, Koh Takeuchi, Hisashi Kashima
Estimating Treatment Effects Under Heterogeneous Interference. ECML/PKDD (1) (2023)
Mike Wong, Edward Raff, James Holt, Ravi Netravali
Marvolo: Programmatic Data Augmentation for Deep Malware Detection. ECML/PKDD (1) (2023)
Thibault Marette, Pauli Miettinen, Stefan Neumann
Visualizing Overlapping Biclusterings and Boolean Matrix Factorizations. ECML/PKDD (1) (2023)
Tim Bakker, Herke van Hoof, Max Welling
Learning Objective-Specific Active Learning Strategies with Attentive Neural Processes. ECML/PKDD (1) (2023)
Gabriele Ciravegna, Frédéric Precioso, Alessandro Betti, Kevin Mottin, Marco Gori
Knowledge-Driven Active Learning. ECML/PKDD (1) (2023)
Bowen Xing, Ivor W. Tsang
Co-Evolving Graph Reasoning Network for Emotion-Cause Pair Extraction. ECML/PKDD (1) (2023)
Mauritius Klein, Collin Leiber, Christian Böhm
k-SubMix: Common Subspace Clustering on Mixed-Type Data. ECML/PKDD (1) (2023)
Fei Liu, Yibo Li, Meiyun Zuo
KESHEM: Knowledge Enabled Short Health Misinformation Detection Framework. ECML/PKDD (1) (2023)
Keizaburo Nishikino, Kenichi Kobayashi
Adversarial Imitation Learning with Controllable Rewards for Text Generation. ECML/PKDD (1) (2023)
Skander Karkar, Patrick Gallinari, Alain Rakotomamonjy
Adversarial Sample Detection Through Neural Network Transport Dynamics. ECML/PKDD (1) (2023)
Rishabh Upadhyay, Gabriella Pasi, Marco Viviani
A Passage Retrieval Transformer-Based Re-Ranking Model for Truthful Consumer Health Search. ECML/PKDD (1) (2023)
Jonas Gregor Wiese, Lisa Wimmer, Theodore Papamarkou, Bernd Bischl, Stephan Günnemann, David Rügamer
Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry. ECML/PKDD (1) (2023)
Chaoxi Niu, Guansong Pang, Ling Chen
Graph-Level Anomaly Detection via Hierarchical Memory Networks. ECML/PKDD (1) (2023)
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)
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)
Ali Khoshvishkaie, Petrus Mikkola, Pierre-Alexandre Murena, Samuel Kaski
Cooperative Bayesian Optimization for Imperfect Agents. ECML/PKDD (1) (2023)
Jaemin Yoo, Yue Zhao, Lingxiao Zhao, Leman Akoglu
DSV: An Alignment Validation Loss for Self-supervised Outlier Model Selection. ECML/PKDD (1) (2023)
Andrzej Dulny, Andreas Hotho, Anna Krause
DynaBench: A Benchmark Dataset for Learning Dynamical Systems from Low-Resolution Data. ECML/PKDD (1) (2023)
Michal Znalezniak, Przemyslaw Rola, Patryk Kaszuba, Jacek Tabor, Marek Smieja
Contrastive Hierarchical Clustering. ECML/PKDD (1) (2023)
Zhangyang Gao, Cheng Tan, Jun Xia, Stan Z. Li
Co-supervised Pre-training of Pocket and Ligand. ECML/PKDD (1) (2023)
Timo Martens, Lorenzo Perini, Jesse Davis
Semi-supervised Learning from Active Noisy Soft Labels for Anomaly Detection. ECML/PKDD (1) (2023)
Anis Fradi, Chafik Samir
A New Framework for Classifying Probability Density Functions. ECML/PKDD (1) (2023)
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)
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)
Yuting Yang, Pei Huang, Juao Cao, Feifei Ma, Jian Zhang, Jintao Li
Quantifying Robustness to Adversarial Word Substitutions. ECML/PKDD (1) (2023)

volume 14169, 2023

Machine Learning and Knowledge Discovery in Databases: Research Track - European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part I ECML/PKDD (1) 14169 (2023)

volume 13713, 2023

Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part I ECML/PKDD (1) 13713 (2023)

2022