ECML-PKDD 2022
253 papers
"Let's Eat Grandma": Does Punctuation Matter in Sentence Representation?
Mansooreh Karami, Ahmadreza Mosallanezhad, Michelle V. Mancenido, Huan Liu A Piece-Wise Polynomial Filtering Approach for Graph Neural Networks
Vijay Lingam, Manan Sharma, Chanakya Ekbote, Rahul Ragesh, Arun Iyer, Sundararajan Sellamanickam A Scaling Law for Syn2real Transfer: How Much Is Your Pre-Training Effective?
Hiroaki Mikami, Kenji Fukumizu, Shogo Murai, Shuji Suzuki, Yuta Kikuchi, Taiji Suzuki, Shin-ichi Maeda, Kohei Hayashi A Stopping Criterion for Transductive Active Learning
Daniel Kottke, Christoph Sandrock, Georg Krempl, Bernhard Sick AD-AUG: Adversarial Data Augmentation for Counterfactual Recommendation
Yifan Wang, Yifang Qin, Yu Han, Mingyang Yin, Jingren Zhou, Hongxia Yang, Ming Zhang ADEPT: Anomaly Detection, Explanation and Processing for Time Series with a Focus on Energy Consumption Data
Benedikt Tobias Müller, Marvin Ender, Jan Erik Swiadek, Mengcheng Jin, Simon Winkel, Dominik Niedziela, Bin Li, Jelle Hüntelmann, Emmanuel Müller Algorithmic Tools for Understanding the Motif Structure of Networks
Tianyi Chen, Brian Matejek, Michael Mitzenmacher, Charalampos E. Tsourakakis An Embedded Continual Learning System for Facial Emotion Recognition
Olivier Antoni, Marion Mainsant, Christelle Godin, Martial Mermillod, Marina Reyboz Anonymity Can Help Minority: A Novel Synthetic Data Over-Sampling Strategy on Multi-Label Graphs
Yijun Duan, Xin Liu, Adam Jatowt, Haitao Yu, Steven J. Lynden, Kyoung-Sook Kim, Akiyoshi Matono Automatic Feature Engineering Through Monte Carlo Tree Search
Yiran Huang, Yexu Zhou, Michael Hefenbrock, Till Riedel, Likun Fang, Michael Beigl Banksformer: A Deep Generative Model for Synthetic Transaction Sequences
Kyle L. Nickerson, Terrence S. Tricco, Antonina Kolokolova, Farzaneh Shoeleh, Charles Robertson, John Hawkin, Ting Hu Bayesian Nonparametrics for Sparse Dynamic Networks
Cian Naik, François Caron, Judith Rousseau, Yee Whye Teh, Konstantina Palla Benchmarking GNNs with GenCAT Workbench
Seiji Maekawa, Yuya Sasaki, George Fletcher, Makoto Onizuka Bi-Directional Contrastive Distillation for Multi-Behavior Recommendation
Yabo Chu, Enneng Yang, Qiang Liu, Yuting Liu, Linying Jiang, Guibing Guo Branch Ranking for Efficient Mixed-Integer Programming via Offline Ranking-Based Policy Learning
Zeren Huang, Wenhao Chen, Weinan Zhang, Chuhan Shi, Furui Liu, Hui-Ling Zhen, Mingxuan Yuan, Jianye Hao, Yong Yu, Jun Wang Calibrate to Interpret
Gregory Scafarto, Nicolas Posocco, Antoine Bonnefoy CDPS: Constrained DTW-Preserving Shapelets
Hussein El Amouri, Thomas Andrew Lampert, Pierre Gançarski, Clément Mallet Class-Incremental Learning via Knowledge Amalgamation
Marcus de Carvalho, Mahardhika Pratama, Jie Zhang, Yajuan Sun Cloud-Based Real-Time Molecular Screening Platform with MolFormer
Brian Belgodere, Vijil Chenthamarakshan, Payel Das, Pierre L. Dognin, Toby Kurien, Igor Melnyk, Youssef Mroueh, Inkit Padhi, Mattia Rigotti, Jarret Ross, Yair Schiff, Richard A. Young Contextualized Graph Embeddings for Adverse Drug Event Detection
Ya Gao, Shaoxiong Ji, Tongxuan Zhang, Prayag Tiwari, Pekka Marttinen Cubism: Co-Balanced Mixup for Unsupervised Volcano-Seismic Knowledge Transfer
Mahsa Keramati, Mohammad A. Tayebi, Zahra Zohrevand, Uwe Glässer, Juan Anzieta, Glyn Williams-Jones Customized Conversational Recommender Systems
Shuokai Li, Yongchun Zhu, Ruobing Xie, Zhenwei Tang, Zhao Zhang, Fuzhen Zhuang, Qing He, Hui Xiong Deep Active Learning for Detection of Mercury's Bow Shock and Magnetopause Crossings
Sahib Julka, Nikolas Kirschstein, Michael Granitzer, Alexander Lavrukhin, Ute V. Amerstorfer Detection of ADHD Based on Eye Movements During Natural Viewing
Shuwen Deng, Paul Prasse, David R. Reich, Sabine Dziemian, Maja Stegenwallner-Schütz, Daniel Krakowczyk, Silvia Makowski, Nicolas Langer, Tobias Scheffer, Lena A. Jäger Efficient Automated Deep Learning for Time Series Forecasting
Difan Deng, Florian Karl, Frank Hutter, Bernd Bischl, Marius Lindauer Explaining Predictions by Characteristic Rules
Amr Alkhatib, Henrik Boström, Michalis Vazirgiannis Factorized Structured Regression for Large-Scale Varying Coefficient Models
David Rügamer, Andreas Bender, Simon Wiegrebe, Daniel Racek, Bernd Bischl, Christian L. Müller, Clemens Stachl Fast and Accurate Importance Weighting for Correcting Sample Bias
Antoine de Mathelin, François Deheeger, Mathilde Mougeot, Nicolas Vayatis FastDEC: Clustering by Fast Dominance Estimation
Geping Yang, Hongzhang Lv, Yiyang Yang, Zhiguo Gong, Xiang Chen, Zhifeng Hao Feature-Robust Optimal Transport for High-Dimensional Data
Mathis Petrovich, Chao Liang, Ryoma Sato, Yanbin Liu, Yao-Hung Hubert Tsai, Linchao Zhu, Yi Yang, Ruslan Salakhutdinov, Makoto Yamada Few-Shot Forecasting of Time-Series with Heterogeneous Channels
Lukas Brinkmeyer, Rafael Rêgo Drumond, Johannes Burchert, Lars Schmidt-Thieme Finding Local Groupings of Time Series
Zed Lee, Marco Trincavelli, Panagiotis Papapetrou Fooling Partial Dependence via Data Poisoning
Hubert Baniecki, Wojciech Kretowicz, Przemyslaw Biecek Foveated Neural Computation
Matteo Tiezzi, Simone Marullo, Alessandro Betti, Enrico Meloni, Lapo Faggi, Marco Gori, Stefano Melacci GNNSampler: Bridging the Gap Between Sampling Algorithms of GNN and Hardware
Xin Liu, Mingyu Yan, Shuhan Song, Zhengyang Lv, Wenming Li, Guangyu Sun, Xiaochun Ye, Dongrui Fan Hierarchical Unimodal Bandits
Tianchi Zhao, Chicheng Zhang, Ming Li Hyperbolic Deep Keyphrase Generation
Yuxiang Zhang, Tianyu Yang, Tao Jiang, Xiaoli Li, Suge Wang Hypothesis Testing for Class-Conditional Label Noise
Rafael Poyiadzi, Weisong Yang, Niall Twomey, Raúl Santos-Rodríguez Improving Micro-Video Recommendation by Controlling Position Bias
Yisong Yu, Beihong Jin, Jiageng Song, Beibei Li, Yiyuan Zheng, Wei Zhuo Inferring Tie Strength in Temporal Networks
Lutz Oettershagen, Athanasios L. Konstantinidis, Giuseppe F. Italiano Knowledge Integration in Deep Clustering
Nguyen-Viet-Dung Nghiem, Christel Vrain, Thi-Bich-Hanh Dao Learning to Control Local Search for Combinatorial Optimization
Jonas K. Falkner, Daniela Thyssens, Ahmad Bdeir, Lars Schmidt-Thieme Logistics, Graphs, and Transformers: Towards Improving Travel Time Estimation
Natalia Semenova, Vadim Porvatov, Vladislav Tishin, Artyom Sosedka, Vladislav Zamkovoy Masked Graph Auto-Encoder Constrained Graph Pooling
Chuang Liu, Yibing Zhan, Xueqi Ma, Dapeng Tao, Bo Du, Wenbin Hu MAVIPER: Learning Decision Tree Policies for Interpretable Multi-Agent Reinforcement Learning
Stephanie Milani, Zhicheng Zhang, Nicholay Topin, Zheyuan Ryan Shi, Charles A. Kamhoua, Evangelos E. Papalexakis, Fei Fang MEAD: A Multi-Armed Approach for Evaluation of Adversarial Examples Detectors
Federica Granese, Marine Picot, Marco Romanelli, Francesco Messina, Pablo Piantanida MepoGNN: Metapopulation Epidemic Forecasting with Graph Neural Networks
Qi Cao, Renhe Jiang, Chuang Yang, Zipei Fan, Xuan Song, Ryosuke Shibasaki Multi-Agent Heterogeneous Stochastic Linear Bandits
Avishek Ghosh, Abishek Sankararaman, Kannan Ramchandran Multi-Objective Actor-Critics for Real-Time Bidding in Display Advertising
Haolin Zhou, Chaoqi Yang, Xiaofeng Gao, Qiong Chen, Gongshen Liu, Guihai Chen Multi-Source Inductive Knowledge Graph Transfer
Junheng Hao, Lu-An Tang, Yizhou Sun, Zhengzhang Chen, Haifeng Chen, Junghwan Rhee, Zhichuan Li, Wei Wang Multi-Task Adversarial Learning for Semi-Supervised Trajectory-User Linking
Sen Zhang, Senzhang Wang, Xiang Wang, Shigeng Zhang, Hao Miao, Junxing Zhu MultiLayerET: A Unified Representation of Entities and Topics Using Multilayer Graphs
Jumanah Alshehri, Marija Stanojevic, Parisa Khan, Benjamin Rapp, Eduard C. Dragut, Zoran Obradovic On the Relationship Between Disentanglement and Multi-Task Learning
Lukasz Maziarka, Aleksandra Nowak, Maciej Wolczyk, Andrzej Bedychaj Ordinal Quantification Through Regularization
Mirko Bunse, Alejandro Moreo, Fabrizio Sebastiani, Martin Senz Overcoming Catastrophic Forgetting via Direction-Constrained Optimization
Yunfei Teng, Anna Choromanska, Murray Campbell, Songtao Lu, Parikshit Ram, Lior Horesh PathOracle: A Deep Learning Based Trip Planner for Daily Commuters
Md. Tareq Mahmood, Mohammed Eunus Ali, Muhammad Aamir Cheema, Syed Md. Mukit Rashid, Timos Sellis Powershap: A Power-Full Shapley Feature Selection Method
Jarne Verhaeghe, M. Jeroen Van Der Donckt, Femke Ongenae, Sofie Van Hoecke ProtoMIL: Multiple Instance Learning with Prototypical Parts for Whole-Slide Image Classification
Dawid Rymarczyk, Adam Pardyl, Jaroslaw Kraus, Aneta Kaczynska, Marek Skomorowski, Bartosz Zielinski R2-AD2: Detecting Anomalies by Analysing the Raw Gradient
Jan-Philipp Schulze, Philip Sperl, Ana Radutoiu, Carla Sagebiel, Konstantin Böttinger Random Similarity Forests
Maciej Piernik, Dariusz Brzezinski, Pawel Zawadzki Reducing the Planning Horizon Through Reinforcement Learning
Logan Dunbar, Benjamin Rosman, Anthony G. Cohn, Matteo Leonetti Rethinking the Misalignment Problem in Dense Object Detection
Yang Yang, Min Li, Bo Meng, Zihao Huang, Junxing Ren, Degang Sun Route to Time and Time to Route: Travel Time Estimation from Sparse Trajectories
Zhiwen Zhang, Hongjun Wang, Zipei Fan, Jiyuan Chen, Xuan Song, Ryosuke Shibasaki Scalable Adversarial Online Continual Learning
Tanmoy Dam, Mahardhika Pratama, Md Meftahul Ferdaus, Sreenatha G. Anavatti, Hussein A. Abbass Spectral Ranking with Covariates
Siu Lun Chau, Mihai Cucuringu, Dino Sejdinovic Stock Trading Volume Prediction with Dual-Process Meta-Learning
Ruibo Chen, Wei Li, Zhiyuan Zhang, Ruihan Bao, Keiko Harimoto, Xu Sun Structure-Preserving Gaussian Process Dynamics
Katharina Ensinger, Friedrich Solowjow, Sebastian Ziesche, Michael Tiemann, Sebastian Trimpe Structured Nonlinear Discriminant Analysis
Christopher M. A. Bonenberger, Wolfgang Ertel, Markus Schneider, Friedhelm Schwenker Summarizing Labeled Multi-Graphs
Dimitris Berberidis, Pierre J. Liang, Leman Akoglu Team-Imitate-Synchronize for Solving Dec-POMDPs
Eliran Abdoo, Ronen I. Brafman, Guy Shani, Nitsan Soffair Time Constrained DL8.5 Using Limited Discrepancy Search
Harold Silvère Kiossou, Pierre Schaus, Siegfried Nijssen, Vinasétan Ratheil Houndji Towards Federated COVID-19 Vaccine Side Effect Prediction
Jiaqi Wang, Cheng Qian, Suhan Cui, Lucas Glass, Fenglong Ma Trigger Detection for the sPHENIX Experiment via Bipartite Graph Networks with Set Transformer
Tingting Xuan, Giorgian Borca-Tasciuc, Yimin Zhu, Yu Sun, Cameron Dean, Zhaozhong Shi, Dantong Yu TS-mIoU: A Time Series Similarity Metric Without Mapping
Azim Ahmadzadeh, Yang Chen, Krishna Rukmini Puthucode, Ruizhe Ma, Rafal A. Angryk U-Net Inspired Transformer Architecture for Far Horizon Time Series Forecasting
Kiran Madhusudhanan, Johannes Burchert, Nghia Duong-Trung, Stefan Born, Lars Schmidt-Thieme VCNet: A Self-Explaining Model for Realistic Counterfactual Generation
Victor Guyomard, Françoise Fessant, Thomas Guyet, Tassadit Bouadi, Alexandre Termier Wasserstein T-SNE
Fynn Bachmann, Philipp Hennig, Dmitry Kobak Waypoint Generation in Row-Based Crops with Deep Learning and Contrastive Clustering
Francesco Salvetti, Simone Angarano, Mauro Martini, Simone Cerrato, Marcello Chiaberge