Program 20 September 2023

(K2) Keynote 2: Michael Bronstein

Time: 9:00 – 10:00

Room: Fucine

Chair: Claudia Plant

Speaker: Michael Bronstein

Title: Physics-inspired Graph Neural Networks

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(P2) Plenary 2: Selection of best papers from Journal Track

Time: 10:30 – 12:30

Room: Fucine

Chair: Tania Cerquitelli and Fabio Vitale

Poster session: 20 September

Authors	Paper	Track
Nikolaos Mylonas, Ioannis Mollas and Grigorios Tsoumakas	An Attention Matrix for Every Decision: Faithfulness-based Arbitration Among Multiple Attention-Based Interpretations of Transformers in Text Classification	Journal
Navid Mohammadi Foumani, Chang Wei Tan , Geoffrey I. Webb and Mahsa Salehi	Improving Position Encoding of Transformers for Multivariate Time Series Classification	Journal
Maryam Abuissa , Alexander Lee and Matteo Riondato	ROhAN: Row-Order Agnostic Null Models for Statistically-sound Knowledge Discovery	Journal
Fabian Fumagalli, Maximilian Muschalik, Eyke Hüllermeier, Barbara Hammer	Incremental Permutation Feature Importance (iPFI): Towards Online Explanations on Data Streams	Journal
Enes Altinisik, Safa Messaoud, Husrev Taha Sencar, Sanjay Chawla	A3T: Accuracy Aware Adversarial Training	Journal
Mike Huisman, Thomas M. Moerland, Aske Plaat, Jan N. van Rijn	Are LSTMs Good Few-Shot Learners?	Journal

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(S3-Fucine) Interpretability & Explainability 1

Time: 14:00-16:00

Room: Fucine

Chair: Riccardo Guidotti

Poster session: 20 September

Authors	Paper	Track
Amir Hossein Akhavan Rahnama, Judith Butepage, Pierre Geurts, Henrik Bostrom	Can Local Explanation Techniques Explain Linear Additive Models?	Journal
Fereshteh Razmi, Li Xiong, Yuan Hong, Jian Lou	Interpretation Attacks on Interpretable Models with Electronic Health Records	Research
Sebastian Müller, Vanessa Toborek, Katharina Beckh, Matthias Jakobs, Christian Bauckhage, Pascal Welke	An Empirical Evaluation of the Rashomon Effect in Explainable Machine Learning	Research
Susanne Dandl, Giuseppe Casalicchio, Bernd Bischl, Ludwig Bothmann	Interpretable Regional Descriptors: Hyperbox-Based Local Explanations	Research
BHAN, Milan*; Lesot, Marie-Jeanne; Vittaut, Jean-Noël; Chesneau, Nicolas	TIGTEC : Token Importance Guided TExt Counterfactuals	Research
Anton Björklund, Kai Puolamäki,	SLISEMAP: Supervised dimensionality reduction through local explanations	Journal

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(S3-Binario3) Sustainability & Climate

Time: 14:00-16:00

Room: Binario 3

Chair: Prasenjit Mitra

Poster session: 20 September

Authors	Paper	Track
René Heinrich, Christoph Scholz, Stephan Vogt, Malte Lehna	Targeted Adversarial Attacks on Wind Power Forecasts	Journal
Michael Steininger, Daniel Abel, Katrin Ziegler, Anna Krause, Heiko Paeth, Andreas Hotho	ConvMOS: Climate Model Output Statistics with Deep Learning	Journal
Omar Faruque, Francis Ndikum Nji, Mostafa Cham, Rohan Mandar Salvi, Xue Zheng, Jianwu Wang	Deep Spatiotemporal Clustering: A Temporal Clustering Approach for Multi-dimensional Climate Data	ADS
Fudong Lin, Xu Yuan, Yihe Zhang, Purushottam Sigdel, Li Chen, Lu Peng, Nian-Feng Tzeng	Comprehensive Transformer-based Model Architecture for Real-World Storm Prediction	ADS
Chetraj Pandey, Rafal Angryk, Berkay Aydin	Explaining Full-disk Deep Learning model for Solar Flare Prediction using Attribution Methods	ADS
Yifan Zhao, Xian Yang, Ranga Raju Vatsavai	Cloud Imputation for Multi-Sensor Remote Sensing Imagery with Style Transfer	ADS

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(S3-A1i) Representation Learning 1

Time: 14:00-16:00

Room: A1i

Chair: Martin Holeňa

Poster session: 20 September

Authors	Paper	Track
Yucheng Shi, Kaixiong Zhou, Ninghao Liu	ENGAGE: Explanation Guided Data Augmentation for Graph Representation Learning	Research
David Friede, Christian Reimers, Heiner Stuckenschmidt, Mathias Niepert	Learning Disentangled Discrete Representations	Research
Quentin Delfosse, Wolfgang Stammer, Thomas Rothenbächer, Dwara Vittal, Kristian Kersting	Boosting Object Representation Learning via Motion and Object Continuity	Research
Alfredo Reichlin, Giovanni Luca Marchetti, Hang Yin, Anastasiia Varava, Danica Kragic	Learning Geometric Representations of Objects via Interaction	Research
Manuele Bicego, Ferdinando Cicalese	On the good behavior of Extremely Randomized Trees in Random Forest-distance computation	Research
Filip Szatkowski, Karol J. Piczak, Tomasz Trzcinski, Przemysław Spurek, Jacek Tabor	Hypernetworks build Implicit Neural Representations of Sounds	Research

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(S3-A3i) Natural Language Processing 2

Time: 14:00-16:00

Room: A3i

Chair: Andreas Hotho

Poster session: 20 September

Authors	Paper	Track
Tianyun Liu, Xinghua Zhang, Zhenyu Zhang, Yubin Wang, Quangang Li, Shuai Zhang, Tingwen Liu	Enhancing Table Retrieval with Dual Graph Representations	Research
Vivek Srivastava, Savita Bhat, Niranjan Pedanekar	A Few Good Sentences: Content Selection For Abstractive Text Summarization	Research
Jiayao Chen, Rui Wang, Jueying He, Mark Junjie Li	Encouraging Sparsity in Neural Topic Modeling with Non-Mean-Field Inference	Research
Wei Wang, Wenhan Ruan, Xiangfu Meng	MODE-Bi-GRU: Orthogonal Independent Bi-GRU Model with Multiscale Feature Extraction	Journal
Kaushal Kumar Maurya, Maunendra Sankar Desarkar, Manish Gupta and Puneet Agrawal	Trie-NLG: Trie Context Augmentation to Improve Personalized Query Auto-Completion for Short and Unseen Prefixes	Journal
Bowen Xing, Ivor W. Tsang	Co-evolving Graph Reasoning Network for Emotion-Cause Pair Extraction	Research

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(S3-A5i) Transfer and Multitask Learning 1

Time: 14:00-16:00

Room: A5i

Chair: Caren Han

Poster session: 20 September

Authors	Paper	Track
Zeren Zhang, Xingjian Li, Tao Hong, Tianyang Wang, Jinwen Ma, Haoyi Xiong, Cheng-Zhong Xu	Overcoming Catastrophic Forgetting for Fine-tuning Pre-trained GANs	Research
Xiyu Wang, Pengxin Guo, Yu Zhang	Unsupervised Domain Adaptation via Bidirectional Cross-Attention Transformer	Research
Dana Zalman, Shai Fine	Multiple-Source Adaptation using Variational Rényi Bound Optimization	Research
François Painblanc, Laetitia Chapel, Nicolas Courty, Chloé Friguet, Charlotte Pelletier, Romain Tavenard	Match-And-Deform: Time Series Domain Adaptation through Optimal Transport and Temporal Alignment	Research
Jincheng Zhong, Haoyu Ma, Ximei Wang, Zhi Kou, Mingsheng Long	Bi-Tuning: Efficient Transfer from Pre-Trained Models	Research
Bhawani Shankar Leelar, Meelis Kull	Generality-training of a Classifier for Improved Calibration in Unseen Contexts	Research

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(S3-A7i) Knowledge Graphs

Time: 14:00-16:00

Room: A7i

Chair: Luca Cagliero

Poster session: 20 September

Authors	Paper	Track
Bayu Distiawan Trisedya, Flora D. Salim, Jeffrey Chan, Damiano Spina, Falk Scholer and Mark Sanderson	i-Align: An Interpretable Knowledge Graph Alignment Model	Journal
Julia Gastinger, Timo Sztyler, Lokesh Sharma, Anett Schülke, Heiner Stuckenschmidt	Comparing Apples and Oranges? On the Evaluation of Methods for Temporal Knowledge Graph Forecasting	Research
Caglar Demir, Axel-Cyrille Ngonga Ngomo	Clifford Embeddings — A Generalized Approach for Embedding in Normed Algebras	Research
Zhaobo Zhang, Pingpeng Yuan, Hai Jin	Exploring Word-Sememe Graph-Centric Chinese Antonym Detection	Research
Bowen Song, Chengjin Xu, Kossi Amouzouvi, Maocai Wang, Jens Lehmann, Sahar Vahdati	Distinct Geometrical Representations for Temporal and Relational Structures in Knowledge Graphs	Research
Caglar Demir, Michel Wiebesiek, Renzhong Lu, Axel-Cyrille Ngonga Ngomo, Stefan Heindorf	LitCQD: Multi-Hop Reasoning in Incomplete Knowledge Graphs with Numeric Literals	Research

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(S3-A9i) Neurosymbolic Learning

Time: 14:00-16:00

Room: A9i

Chair: Alan Perotti

Poster session: 20 September

Authors	Paper	Track
Sebastian Mežnar, Sašo Džeroski, Ljupčo Todorovski	Efficient Generator of Mathematical Expressions for Symbolic Regression	Journal
Amanda M Bertschinger, Q. Tyrell Davis, James Bagrow, Joshua Bongard	The Metric is the Message: Benchmarking challenges for neural symbolic regression	Research
Nan Jiang, Yexiang Xue	Symbolic Regression via Control Variable Genetic Programming	Research
N’Dah Jean Kouagou, Stefan Heindorf, Caglar Demir, Axel-Cyrille Ngonga Ngomo	Neural Class Expression Synthesis in ALCHIQ(D)	Research
Rishi Hazra, Luc De Raedt	Deep Explainable Relational Reinforcement Learning: A Neuro-Symbolic Approach	Research
Monika Jain, Kuldeep Singh, Raghava Mutharaju	ReOnto: A Neuro-Symbolic Approach for Biomedical Relation Extraction	Research

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(S3-A11i) Journal Track Mix 1

Time: 14:00-16:00

Room: A11i

Chair: Myra Spiliopoulou

Poster session: 20 September

Authors	Paper	Track
Sebastian Buschjäger, Katharina Morik	Joint Leaf-Refinement and Ensemble Pruning Through L1 Regularization	Journal
Matthieu Herrmann, Chang Wei Tan, Geoffrey I. Webb	Parameterizing the cost function of dynamic time warping with application to time series classification	Journal
Xin-Chun Li, Yang Yang. De-Chuan Zhan	MrTF: Model Refinery for Transductive Federated Learning	Journal
Andres Felipe Posada-Moreno, Lukas Kreisköther, Tassilo Glander, Deevio GmbH, Sebastian Trimpe	Scale-Preserving Automatic Concept Extraction (SPACE)	Journal
Mohit Rajpal,Yehong Zhang,Kian Hsiang Low	Pruning during training by network efficacy modeling	Journal
Charles Alexander Hepburn, Giovanni Montana	Model-based trajectory stitching for improved behavioural cloning and its applications	Journal

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(S4-Fucine) Interpretability & Explainability 2

Time: 16:30 – 18:30

Room: Fucine

Chair: Eliana Pastor

Poster session: 20 September

Authors	Paper	Track
Shiyun Xu, Zhiqi Bu, Pratik Chaudhari, Ian J. Barnett	Sparse Neural Additive Model: Interpretable Deep Learning with Feature Selection via Group Sparsity	Research
Kentaro Kanamori	Learning Locally Interpretable Rule Ensemble	Research
Brigt Arve Toppe Håvardstun, Cèsar Ferri, José Hernández-Orallo, Pekka Parviainen, Jan Arne Telle	XAI with Machine Teaching when Humans Are (Not) Informed about the Irrelevant Features	Research
Victor Guyomard, Thomas Guyet, Tassadit Bouadi, Françoise Fessant, Alexandre Termier	Generating robust counterfactual explanations	Research
Tathagata Raha, Mukund Choudhary, Abhinav S Menon, Harshit Gupta, KV Aditya Srivatsa, Manish Gupta, Vasudeva Varma	Neural models for Factual Inconsistency Classification with Explanations	Research
Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier	iSAGE: An Incremental Version of SAGE for Online Explanation on Data Streams	Research

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(S4-Binario3) AI in Industry

Time: 16:30 – 18:30

Room: Binario 3

Chair: Yexiang Xue

Poster session: 20 September

Authors	Paper	Track
Stefan Kurz (BOSCH)	Hybrid Modeling: Newton + Kepler = Success	Sponsor
Tom Diethe (AstraZeneca)	Machine Learning for Protein Design: Antibodies and Biologics	Sponsor
Asmita Bhat, Nooshin Haji-Ghassemi, Deepak Nagaraj, Sophie Fellenz	Constraint-Based Parameterization and Disentanglement of Aerodynamic Shapes using Deep Generative Models	ADS
Mohamed Abuella, M. Amine Atoui, Slawomir Nowaczyk, Simon Johansson, Ethan Faghani	Data-Driven Explainable Artificial Intelligence for Energy Efficiency in Short-Sea Shipping	ADS
Sushant More, Priya Kotwal, Sujith Chappidi, Dinesh Mandalapu, Chris Khawand	Double Machine Learning at Scale to Predict Causal Impact of Customer Actions	ADS
Cengis Hasan, Alexandros Agapitos, David Lynch, Alberto Castagna, Giorgio Cruciata, Hao Wang, Aleksandar Milenovic	Continual Model-based Reinforcement Learning for Data Efficient Wireless Network Optimisation	ADS

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(S4-A1i) Representation Learning 2

Time: 16:30 – 18:30

Room: A1i

Chair: Tatiana Tommasi

Poster session: 20 September

Authors	Paper	Track
Priyanka Chudasama, Tushar Kadam, Rajat Patel, Aakarsh Malhotra, Manoj Mangam	Contrastive Representation through Angle and Distance based Loss for Partial Label Learning	Research
Luis Armando Pérez Rey, Giovanni Luca Marchetti, Danica Kragic, Dmitri Jarnikov, Mike Holenderski	Equivariant Representation Learning in the Presence of Stabilizers	Research
Hiroki Waida, Yuichiro Wada, Léo Andéol, Takumi Nakagawa, Yuhui Zhang, Takafumi Kanamori	Towards Understanding the Mechanism of Contrastive Learning via Similarity Structure: A Theoretical Analysis	Research
Pranav Poduval, Gaurav Oberoi, Sangam Verma, Ayush Agarwal, Karamjit Singh, Siddhartha Asthana	BipNRL : Mutual Information Maximization on Bipartite Graphs for Node Representation Learning	Research
Debo Cheng, Ziqi Xu, Jiuyong Li, Lin Liu, Thuc Duy Le, Jixue Liu	Learning Conditional Instrumental Variable Representation for Causal Effect Estimation	Research
Mihailo Obrenović, Thomas Lampert, Miloš Ivanović, Pierre Gançarski	Learning domain invariant representations of heterogeneous image data	Journal

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(S4-A3i) Reinforcement Learning 2

Time: 16:30 – 18:30

Room: A3i

Chair: Pablo Samuel Castro

Poster session: 20 September

Authors	Paper	Track
Linghui Meng, Xuantang Xiong, Yifan Zang, Xi Zhang, Guoqi Li, Dengpeng Xing, Bo Xu	Filtered Observations for Model-based Multi-agent Reinforcement Learning	Research
Zhaohui Jiang, Paul Weng	Unsupervised Salient Patch Selection for Data-Efficient Reinforcement Learning	Research
Qiang He, Tianyi Zhou, Meng Fang, Setareh Maghsudi	Eigensubspace of Temporal-Difference Dynamics and How It Improves Value Approximation in Reinforcement Learning	Research
Viktor Bengs,Eyke Hüllermeier	Multi-Armed Bandits with Censored Consumption of Resources	Journal
Anmol Manish Kagrecha,Jayakrishnan Nair, Krishna Jagannathan,	Constrained regret minimization for multi-criterion multi-armed bandits	Journal
Chien-Min Yu, Ming-Hsin Chen, Hsuan-Tien Lin	Learning Key Steps to Attack Deep Reinforcement Learning Agents	Journal

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(S4-A5i) Web & Social

Time: 16:30 – 18:30

Room: A5i

Chair: Marco Viviani

Poster session: 20 September

Authors	Paper	Track
Xing Tang, Yang Qiao, Yuwen Fu, Fuyuan Lyu, Dugang Liu, Xiuqiang He	OptMSM: Optimizing Multi-Scenario Modeling for Click-Through Rate Prediction	ADS
Yuchen Li, Haoyi Xiong, Linghe Kong, Shuaiqiang Wang, Zeyi Sun, Hongyang Chen, Guihai Chen, Dawei Yin	LtrGCN: Large-Scale Graph Convolutional Networks-based Learning to Rank for Web Search	ADS
Ninghan Chen, Xihui Chen, Zhiqiang Zhong and Jun Pang	A Tale of Two Roles: Exploring Topic-specific Susceptibility and Influence in Cascade Prediction	Journal
Shreya Ghosh, Prasenjit Mitra	How Early can we Detect? Detecting Misinformation on Social Media Using User Profiling and Network Characteristics	ADS
Fei Liu, Yibo Li, Meiyun Zuo	KESHEM: Knowledge Enabled Short Health Misinformation Detection Framework	Research
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	Research

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(S4-A7i) Graphs 2

Time: 16:30 – 18:30

Room: A7i

Chair: Yuzhou Chen

Poster session: 20 September

Authors	Paper	Track
Maximilian Stubbemann, Gerd Stumme	The Mont Blanc of Twitter: Identifying Hierarchies of Outstanding Peaks in Social Networks	Research
Yuting Liang, Wen Bai, Yuncheng Jiang	A Unified Spectral Rotation Framework Using a Fused Similarity Graph	Research
Liping Yan, Weiren Yu	SimSky: An Accuracy-Aware Algorithm for Single-Source SimRank Search	Research
Laura Toni, Pascal Frossard	Online Network Source Optimization with Graph-Kernel MAB	Research
Adrian Horzyk, Daniel Bulanda, Janusz A. Starzyk	Construction and Training of Multi-Associative Graph Networks	Research
Bosong Huang, Weihao Yu, Ruzhong Xie, Jing Xiao, Jin Huang	SL-Diff: Two-stage Denoising Diffusion Model for Source Localization in Graph Inverse Problems	Research

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(S4-A9i) Few-shot Learning

Time: 16:30 – 18:30

Room: A9i

Chair: Gabriele Ciravegna

Poster session: 20 September

Authors	Paper	Track
Zicheng Zhao, Linhao Luo, Shirui Pan, Quoc Viet Hung Nguyen, Chen Gong	Towards Few-shot Inductive Link Prediction on Knowledge Graphs: A Relational Anonymous Walk-guided Neural Process Approach	Research
Zifeng Ding, Jingpei Wu, Zongyue Li, Yunpu Ma, Volker Tresp	Improving Few-Shot Inductive Learning on Temporal Knowledge Graphs using Confidence-Augmented Reinforcement Learning	Research
Xin Liu, Yilin Lyu, Liping Jing, Tieyong Zeng, Jian Yu	Not All Tasks are Equal: a Parameter-efficient Task Reweighting Method for Few-shot learning	Research
Yunlong Yu, Lisha Jin, Yingming Li	Boosting Generalized Few-Shot Learning by Scattering Intra-Class Distribution	Research
Xin Liu, Shijing Wang, Kairui Zhou, Yilin Lyu, Mingyang Song, Liping Jing, Tieyong Zeng, Jian Yu	vMF Loss: Exploring a Scattered Intra-class Hypersphere for Few-shot Learning	Research
Zhaochen Li, Kedian Mu	Meta-HRNet: A High Resolution Network for Coarse-to-Fine Few-Shot Classification	Research

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(S4-A11i) Mobility 2

Time: 16:30 – 18:30

Room: A11i

Chair: Latifa Oukhellou

Poster session: 20 September

Authors	Paper	Track
Miguel E. P. Silva, Bruno Veloso, João Gama	Predictive Maintenance, Adversarial Autoencoders and Explainability	ADS
Espen Haugsdal, Sara Malacarne, Massimiliano Ruocco	Circle Attention: Forecasting network traffic by learning interpretable spatial relationships from intersecting circles	ADS
Massimiliano Luca, Luca Pappalardo, Bruno Lepri, Gianni Barlacchi	Trajectory Test-Train Overlap in Next-Location Prediction Datasets	Journal
Arian Prabowo, Wei Shao, Hao Xue, Piotr Koniusz, Flora Salim	Traffic Forecasting on New Roads Unseen in the Training Data Using Spatial Contrastive Pre-Training	Journal
Jingwei Zuo, Karine Zeitouni, Yehia Taher, Sandra Garcia-Rodriguez	Graph Convolutional Networks for Traffic Forecasting with Missing Values	Journal
Tao Wu, Kaixuan Zhu, Jiali Mao, Miaomiao Yang, Aoying Zhou	TDCM: Transport Destination Calibrating based on Multi-task Learning	ADS