ECML-PKDD 2023
270 papers
A Risk Prediction Framework to Optimize Remote Patient Monitoring Following Cardiothoracic Surgery
Ricardo Santos, Bruno Ribeiro, Pedro Dias, Isabel Curioso, Pedro Madeira, Federico Guede-Fernández, Jorge Santos, Pedro Coelho, Inês Sousa, Ana Londral A Scalable Solution for the Extended Multi-Channel Facility Location Problem
Etika Agarwal, Karthik S. Gurumoorthy, Ankit Ajit Jain, Shantala Manchenahally ActiveGLAE: A Benchmark for Deep Active Learning with Transformers
Lukas Rauch, Matthias Aßenmacher, Denis Huseljic, Moritz Wirth, Bernd Bischl, Bernhard Sick Advancing Fraud Detection Systems Through Online Learning
Tommaso Paladini, Martino Bernasconi de Luca, Michele Carminati, Mario Polino, Francesco Trovò, Stefano Zanero An Empirical Evaluation of the Rashomon Effect in Explainable Machine Learning
Sebastian Müller, Vanessa Toborek, Katharina Beckh, Matthias Jakobs, Christian Bauckhage, Pascal Welke An Examination of Wearable Sensors and Video Data Capture for Human Exercise Classification
Ashish Singh, Antonio Bevilacqua, Timilehin B. Aderinola, Thach Le Nguyen, Darragh Whelan, Martin O'Reilly, Brian Caulfield, Georgiana Ifrim An Interactive Interface for Novel Class Discovery in Tabular Data
Colin Troisemaine, Joachim Flocon-Cholet, Stéphane Gosselin, Alexandre Reiffers-Masson, Sandrine Vaton, Vincent Lemaire Attentive Multi-Layer Perceptron for Non-Autoregressive Generation
Shuyang Jiang, Jun Zhang, Jiangtao Feng, Lin Zheng, Lingpeng Kong Automated Financial Analysis Using GPT-4
Sander Noels, Adriaan Merlevede, Andrew Fecheyr, Maarten Vanhalst, Nick Meerlaen, Sébastien Viaene, Tijl De Bie Bi-Tuning: Efficient Transfer from Pre-Trained Models
Jincheng Zhong, Haoyu Ma, Ximei Wang, Zhi Kou, Mingsheng Long BipNRL: Mutual Information Maximization on Bipartite Graphs for Node Representation Learning
Pranav Poduval, Gaurav Oberoi, Sangam Verma, Ayush Agarwal, Karamjit Singh, Siddhartha Asthana Boosting Object Representation Learning via Motion and Object Continuity
Quentin Delfosse, Wolfgang Stammer, Thomas Rothenbacher, Dwarak Vittal, Kristian Kersting Cad2graph: Automated Extraction of Spatial Graphs from Architectural Drawings
Pratik Maitra, Masahiro Kiji, Talal Riaz, Philip M. Polgreen, Alberto M. Segre, Sriram V. Pemmaraju, Bijaya Adhikari Comprehensive Transformer-Based Model Architecture for Real-World Storm Prediction
Fudong Lin, Xu Yuan, Yihe Zhang, Purushottam Sigdel, Li Chen, Lu Peng, Nian-Feng Tzeng Constrained-HIDA: Heterogeneous Image Domain Adaptation Guided by Constraints
Mihailo Obrenovic, Thomas Andrew Lampert, Milos R. Ivanovic, Pierre Gançarski Continual Model-Based Reinforcement Learning for Data Efficient Wireless Network Optimisation
Cengis Hasan, Alexandros Agapitos, David Lynch, Alberto Castagna, Giorgio Cruciata, Hao Wang, Aleksandar Milenovic Continuous Depth Recurrent Neural Differential Equations
Srinivas Anumasa, Geetakrishnasai Gunapati, P. K. Srijith Contrastive Hierarchical Clustering
Michal Znalezniak, Przemyslaw Rola, Patryk Kaszuba, Jacek Tabor, Marek Smieja Cooperative Bayesian Optimization for Imperfect Agents
Ali Khoshvishkaie, Petrus Mikkola, Pierre-Alexandre Murena, Samuel Kaski Cooperative Multi-Agent Reinforcement Learning for Inventory Management
Madhav Khirwar, Karthik S. Gurumoorthy, Ankit Ajit Jain, Shantala Manchenahally cuSLINK: Single-Linkage Agglomerative Clustering on the GPU
Corey J. Nolet, Divye Gala, Alexandre Fender, Mahesh Doijade, Joe Eaton, Edward Raff, John Zedlewski, Brad Rees, Tim Oates Deep Imbalanced Time-Series Forecasting via Local Discrepancy Density
Junwoo Park, Jungsoo Lee, Youngin Cho, Woncheol Shin, Dongmin Kim, Jaegul Choo, Edward Choi Deep Learning for Real-Time Neural Decoding of Grasp
Paolo Viviani, Ilaria Gesmundo, Elios Ghinato, Andres Y. Agudelo-Toro, Chiara Vercellino, Giacomo Vitali, Letizia Bergamasco, Alberto Scionti, Marco Ghislieri, Valentina Agostini, Olivier Terzo, Hansjörg Scherberger Detecting Evasion Attacks in Deployed Tree Ensembles
Laurens Devos, Lorenzo Perini, Wannes Meert, Jesse Davis Double Machine Learning at Scale to Predict Causal Impact of Customer Actions
Sushant More, Priya Kotwal, Sujith Chappidi, Dinesh Mandalapu, Chris Khawand Efficient Hyperdimensional Computing
Zhanglu Yan, Shida Wang, Kaiwen Tang, Weng-Fai Wong Enhancing Adversarial Training via Reweighting Optimization Trajectory
Tianjin Huang, Shiwei Liu, Tianlong Chen, Meng Fang, Li Shen, Vlado Menkovski, Lu Yin, Yulong Pei, Mykola Pechenizkiy Enhancing Table Retrieval with Dual Graph Representations
Tianyun Liu, Xinghua Zhang, Zhenyu Zhang, Yubin Wang, Quangang Li, Shuai Zhang, Tingwen Liu Equivariant Representation Learning in the Presence of Stabilizers
Luis Armando Pérez Rey, Giovanni Luca Marchetti, Danica Kragic, Dmitri Jarnikov, Mike Holenderski Estimating Treatment Effects Under Heterogeneous Interference
Xiaofeng Lin, Guoxi Zhang, Xiaotian Lu, Han Bao, Koh Takeuchi, Hisashi Kashima Exploring and Exploiting Data-Free Model Stealing
Chi Hong, Jiyue Huang, Robert Birke, Lydia Y. Chen FG2AN: Fairness-Aware Graph Generative Adversarial Networks
Zichong Wang, Charles Wallace, Albert Bifet, Xin Yao, Wenbin Zhang Filtered Observations for Model-Based Multi-Agent Reinforcement Learning
Linghui Meng, Xuantang Xiong, Yifan Zang, Xi Zhang, Guoqi Li, Dengpeng Xing, Bo Xu Future Augmentation with Self-Distillation in Recommendation
Chong Liu, Ruobing Xie, Xiaoyang Liu, Pinzheng Wang, Rongqin Zheng, Lixin Zhang, Juntao Li, Feng Xia, Leyu Lin Gait-Based Biometrics System
Aleksander Sawicki, Khalid Saeed Generating Robust Counterfactual Explanations
Victor Guyomard, Françoise Fessant, Thomas Guyet, Tassadit Bouadi, Alexandre Termier Hierarchical Graph Contrastive Learning
Hao Yan, Senzhang Wang, Jun Yin, Chaozhuo Li, Junxing Zhu, Jianxin Wang Hypernetworks Build Implicit Neural Representations of Sounds
Filip Szatkowski, Karol J. Piczak, Przemyslaw Spurek, Jacek Tabor, Tomasz Trzcinski Inclusively: An AI-Based Assistant for Inclusive Writing
Moreno La Quatra, Salvatore Greco, Luca Cagliero, Tania Cerquitelli Interactive Visualization of Counterfactual Explanations for Tabular Data
Victor Guyomard, Françoise Fessant, Thomas Guyet, Tassadit Bouadi, Alexandre Termier Is My Neural Net Driven by the MDL Principle?
Eduardo Brandao, Stefan Duffner, Rémi Emonet, Amaury Habrard, François Jacquenet, Marc Sebban Knowledge-Driven Active Learning
Gabriele Ciravegna, Frédéric Precioso, Alessandro Betti, Kevin Mottin, Marco Gori Learning Disentangled Discrete Representations
David Friede, Christian Reimers, Heiner Stuckenschmidt, Mathias Niepert Learning Distinct Features Helps, Provably
Firas Laakom, Jenni Raitoharju, Alexandros Iosifidis, Moncef Gabbouj Learning Fast and Slow: Towards Inclusive Federated Learning
Muhammad Tahir Munir, Muhammad Mustansar Saeed, Mahad Ali, Zafar Ayyub Qazi, Agha Ali Raza, Ihsan Ayyub Qazi Learning Geometric Representations of Objects via Interaction
Alfredo Reichlin, Giovanni Luca Marchetti, Hang Yin, Anastasiia Varava, Danica Kragic Learning Graphical Factor Models with Riemannian Optimization
Alexandre Hippert-Ferrer, Florent Bouchard, Ammar Mian, Titouan Vayer, Arnaud Breloy LitCQD: Multi-Hop Reasoning in Incomplete Knowledge Graphs with Numeric Literals
Caglar Demir, Michel Wiebesiek, Renzhong Lu, Axel-Cyrille Ngonga Ngomo, Stefan Heindorf LtrGCN: Large-Scale Graph Convolutional Networks-Based Learning to Rank for Web Search
Yuchen Li, Haoyi Xiong, Linghe Kong, Shuaiqiang Wang, Zeyi Sun, Hongyang Chen, Guihai Chen, Dawei Yin Match-and-Deform: Time Series Domain Adaptation Through Optimal Transport and Temporal Alignment
François Painblanc, Laetitia Chapel, Nicolas Courty, Chloé Friguet, Charlotte Pelletier, Romain Tavenard Memento: Facilitating Effortless, Efficient, and Reliable ML Experiments
Zac Pullar-Strecker, Xinglong Chang, Liam Brydon, Ioannis Ziogas, Katharina Dost, Jörg Wicker Mitigating Algorithmic Bias with Limited Annotations
Guanchu Wang, Mengnan Du, Ninghao Liu, Na Zou, Xia Ben Hu Modeling Graphs Beyond Hyperbolic: Graph Neural Networks in Symmetric Positive Definite Matrices
Wei Zhao, Federico López, J. Maxwell Riestenberg, Michael Strube, Diaaeldin Taha, Steve Trettel Neural Class Expression Synthesis in ALCHIQ(D)
N'Dah Jean Kouagou, Stefan Heindorf, Caglar Demir, Axel-Cyrille Ngonga Ngomo Neural Models for Factual Inconsistency Classification with Explanations
Tathagata Raha, Mukund Choudhary, Abhinav Menon, Harshit Gupta, KV Aditya Srivatsa, Manish Gupta, Vasudeva Varma News Recommendation via Jointly Modeling Event Matching and Style Matching
Pengyu Zhao, Shoujin Wang, Wenpeng Lu, Xueping Peng, Weiyu Zhang, Chaoqun Zheng, Yonggang Huang Offline Reinforcement Learning with On-Policy Q-Function Regularization
Laixi Shi, Robert Dadashi, Yuejie Chi, Pablo Samuel Castro, Matthieu Geist Ordinal Regression for Difficulty Prediction of StepMania Levels
Billy Joe Franks, Benjamin Dinkelmann, Marius Kloft, Sophie Fellenz Overcoming Catastrophic Forgetting for Fine-Tuning Pre-Trained GANs
Zeren Zhang, Xingjian Li, Tao Hong, Tianyang Wang, Jinwen Ma, Haoyi Xiong, Cheng-Zhong Xu PCDF: A Parallel-Computing Distributed Framework for Sponsored Search Advertising Serving
Han Xu, Hao Qi, Yaokun Wang, Pei Wang, Guowei Zhang, Congcong Liu, Junsheng Jin, Xiwei Zhao, Zhangang Lin, Jinghe Hu, Jingping Shao PICT: Precision-Enhanced Road Intersection Recognition Using Cycling Trajectories
Wenyu Wu, Wenyi Shen, Jiali Mao, Lisheng Zhao, Shaosheng Cao, Aoying Zhou, Lin Zhou PIQARD System for Experimenting and Testing Language Models with Prompting Strategies
Marcin Korcz, Dawid Plaskowski, Mateusz Politycki, Jerzy Stefanowski, Alex Terentowicz Quantifying Node-Based Core Resilience
Jakir Hossain, Sucheta Soundarajan, Ahmet Erdem Sariyüce Quantifying Robustness to Adversarial Word Substitutions
Yuting Yang, Pei Huang, Juan Cao, Feifei Ma, Jian Zhang, Jintao Li Regularization for Uplift Regression
Krzysztof Rudas, Szymon Jaroszewicz Rényi Divergence Deep Mutual Learning
Weipeng Fuzzy Huang, Junjie Tao, Changbo Deng, Ming Fan, Wenqiang Wan, Qi Xiong, Guangyuan Piao Skeletal Cores and Graph Resilience
Danylo Honcharov, Ahmet Erdem Sariyüce, Ricky Laishram, Sucheta Soundarajan Socially Fair Center-Based and Linear Subspace Clustering
Sruthi Gorantla, Kishen N. Gowda, Amit Deshpande, Anand Louis Spatial-Temporal Graph Sandwich Transformer for Traffic Flow Forecasting
Yujie Fan, Chin-Chia Michael Yeh, Huiyuan Chen, Liang Wang, Zhongfang Zhuang, Junpeng Wang, Xin Dai, Yan Zheng, Wei Zhang Temporal Graph Based Incident Analysis System for Internet of Things
Peng Yuan, Lu-An Tang, Haifeng Chen, David S. Chang, Moto Sato, Kevin Woodward TIGTEC: Token Importance Guided TExt Counterfactuals
Milan Bhan, Jean-Noël Vittaut, Nicolas Chesneau, Marie-Jeanne Lesot Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry
Jonas Gregor Wiese, Lisa Wimmer, Theodore Papamarkou, Bernd Bischl, Stephan Günnemann, David Rügamer Towards Minimising Perturbation Rate for Adversarial Machine Learning with Pruning
Zhiyu Zhu, Jiayu Zhang, Zhibo Jin, Xinyi Wang, Minhui Xue, Jun Shen, Kim-Kwang Raymond Choo, Huaming Chen Train Your Own GNN Teacher: Graph-Aware Distillation on Textual Graphs
Costas Mavromatis, Vassilis N. Ioannidis, Shen Wang, Da Zheng, Soji Adeshina, Jun Ma, Han Zhao, Christos Faloutsos, George Karypis Unsupervised Deep Cross-Language Entity Alignment
Chuanyu Jiang, Yiming Qian, Lijun Chen, Yang Gu, Xia Xie vMF Loss: Exploring a Scattered Intra-Class Hypersphere for Few-Shot Learning
Xin Liu, Shijing Wang, Kairui Zhou, Yilin Lyu, Mingyang Song, Liping Jing, Tieyong Zeng, Jian Yu Weak Supervision and Clustering-Based Sample Selection for Clinical Named Entity Recognition
Wei Sun, Shaoxiong Ji, Tuulia Denti, Hans Moen, Oleg Kerro, Antti Rannikko, Pekka Marttinen, Miika Koskinen XAI with Machine Teaching When Humans Are (Not) Informed About the Irrelevant Features
Brigt Arve Toppe Håvardstun, Cèsar Ferri, José Hernández-Orallo, Pekka Parviainen, Jan Arne Telle Χiplot: Web-First Visualisation Platform for Multidimensional Data
Akihiro Tanaka, Juniper Tyree, Anton Björklund, Jarmo Mäkelä, Kai Puolamäki