Adaptive Sparsity Level during Training for Efficient Time Series Forecasting with Transformers
Zahra Atashgahi, Mykola Pechenizkiy, Raymond Veldhuis, Decebal Constantin Mocanu
RumorMixer: Exploring Echo Chamber Effect and Platform Heterogeneity
Haowei Xu, Chao Gao, Xianghua Li, Zhen Wang
Diversified Ensemble of Independent Sub-Networks for Robust Self-Supervised Representation Learning
Amihossein Vahidi, Lisa Wimmer, Hüseyin Anil Gündüz, Bernd Bischl, Eyke Hüllermeier, Mina Rezaei
Modular Debiasing of Latent User Representations in Prototype-based Recommender Systems
Alessandro B. Melchiorre, Shahed Masoudian, Deepak Kumar, Markus Schedl
A Mathematics Framework of Artificial Shifted Population Risk and Its Further Understanding Related to Consistency Regularization
Xiliang Yang, Shenyang Deng, Shicong Liu, Yuanchi Suo, Wing.W.Y NG, Jianjun Zhang
Attention-Driven Dropout: A Simple Method to Improve Self-supervised Contrastive Sentence Embeddings
Fabian Stermann, Ilias Chalkidis, Amihossein Vahidi, Bernd Bischl, Mina Rezaei
AEMLO: AutoEncoder-Guided Multi-Label Oversampling
Ao Zhou, Bin Liu, Jin Wang, Kaiwei Sun, Kelin Liu
MANTRA: Temporal Betweenness Centrality Approximation through Sampling
Antonio Cruciani
Dimensionality-induced information loss of outliers in deep neural networks
Kazuki Uematsu, Kosuke Haruki, Taiji Suzuki, Mitsuhiro Kimura, Takahiro Takimoto, Hideyuki Nakagawa
Towards Open-World Cross-Domain Sequential Recommendation: A Model-Agnostic Contrastive Denoising Approach
Wujiang Xu, Xuying Ning, Wenfang Lin, Mingming Ha, Qiongxu Ma, Qianqiao Liang, Xuewen Tao, Linxun Chen, Bing Han, Minnan Luo
MixerFlow: MLP-Mixer meets Normalising Flows
Eshant English, Matthias Kirchler, Christoph Lippert
Handling Delayed Feedback in Distributed Online Optimization : A Projection-Free Approach
Tuan-Anh Nguyen, Nguyen Kim Thang, Denis Trystram
Secure Dataset Condensation for Privacy-Preserving and Efficient Vertical Federated Learning
Dashan Gao, Canhui Wu, Xiaojin Zhang, Xin Yao, Qiang Yang
Neighborhood Component Feature Selection for Multiple Instance Learning Paradigm
Giacomo Turri, Luca Romeo
MESS: Coarse-grained Modular Two-way Dialogue Entity Linking Framework
Pengnian Qi, Zhiyuan Zha, Biao Qin
Session - Target Pair: User Intent Perceiving Networks for Session-based Recommendation
Tingting Dai, Qiao Liu, Yang Xie, Yue Zeng, Rui Hou, Yanglei Gan
Hierarchical Fine-grained Visual Classification Leveraging Consistent Hierarchical Knowledge
Yuting Liu, Liu Yang, Yu Wang
Backdoor Attacks with Input-unique Triggers in NLP
Xukun Zhou, Jiwei Li, Tianwei Zhang, Lingjuan Lyu, Muqiao Yang, Jun He
Label Privacy Source Coding in Vertical Federated Learning
Dashan Gao, Sheng Wan, Hanlin Gu, Lixin Fan, Xin Yao, Qiang Yang
Error types in Transformer-based Paraphrasing Models: A Taxonomy, Paraphrase Annotation Model and Dataset
Auday Berro, Boualem Benatallah, Yacine Gaci, Khalid Benabdeslem
FedHCDR: Federated Cross-Domain Recommendation with Hypergraph Signal Decoupling
Hongyu Zhang, Dongyi Zheng, Lin Zhong, Xu Yang, Jiyuan Feng, Yunqing Feng, Qing Liao
Data-Agnostic Pivotal Instances Selection for Decision-Making Models
Alessio Cascione, Mattia Setzu, Riccardo Guidotti
Reliable Classifications with Guaranteed Confidence using the Dempster-Shafer Theory of Evidence
Marie C. Kempkes, Vedran Dunjko, Evert van Nieuwenburg, Jakob Spiegelberg
A New Framework for Evaluating the Validity and the Performance of Binary Decisions on Manifold-valued Data
Anis Fradi, Chafik Samir
The Future is Different: Predicting Reddits Popularity with Variational Dynamic Language Models
Kostadin Cvejoski, Rams'es J. S'anchez, C'esar Ojeda
CircuitVQA: A Visual Question Answering Dataset for Electrical Circuit Images
Rahul Mehta, Bhavyajeet Singh, Vasudeva Varma, Manish Gupta
Spatiotemporal Covariance Neural Networks
Andrea Cavallo, Mohammad Sabbaqi, Elvin Isufi
Frequency Enhanced Pre-training for Cross-city Few-shot Traffic Forecasting
Zhanyu Liu, Jianrong Ding, Guanjie Zheng
Simple Graph Condensation
Zhenbang Xiao, Yu Wang, Shunyu Liu, Huiqiong Wang, Mingli Song, Tongya Zheng
Multivariate Traffic Demand Prediction via 2D Spectral Learning and Global Spatial Optimization
Changlu Chen, Yanbin Liu, Ling Chen, Chengqi Zhang
Reliable Classifications with Guaranteed Confidence using the Dempster-Shafer Theory of Evidence
Marie C. Kempkes, Vedran Dunjko, Evert van Nieuwenburg, Jakob Spiegelberg
LimGen: Probing the LLMs for Generating Suggestive Limitations of Research Papers
Abdur Rahman Bin Mohammed Faizullah, Ashok Urlana, Rahul Mishra
On the Robustness of Global Feature Effect Explanations
Hubert Baniecki, Giuseppe Casalicchio, Bernd Bischl, Przemyslaw Biecek
A Unified Data Augmentation Framework for Low-Resource Multi-Domain Dialogue Generation
Yongkang Liu, Ercong Nie, Zheng Hua, Zifeng Ding, Daling Wang, Yifei Zhang, Hinrich Schutze
Improving Diversity in Black-box Few-shot Knowledge Distillation
Tri-Nhan Vo, Dang Nguyen, Kien Do, Sunil Gupta
Self-Pro: A Self-Prompt and Tuning Framework for Graph Neural Networks
Chenghua Gong, Xiang Li, Jianxiang Yu, Yao Cheng, Jiaqi Tan, Chengcheng Yu
Variable-Agnostic Causal Exploration for Reinforcement Learning
Minh Hoang Nguyen, Hung Le, Svetha Venkatesh
LayerGLAT: a Flexible Non-Autoregressive Transformer for Single-Pass and Multi-Pass Prediction
Shijie Li, Inigo Jauregi Unanue, Massimo Piccardi
Generative Modeling with Flow-Guided Density Ratio Learning
Alvin Heng, Abdul Fatir Ansari, Harold Soh
ADR: An Adversarial Approach to Learn Decomposed Representations for Causal Inference
Xiangyu Zheng, Guogang Tian, Sen Wang, Zhixiang Huang
Data is Moody: Discovering Data Modification Rules from Process Event Logs
Marco Bjarne Schuster, Boris Wiegand, Jilles Vreeken
How Much Training Data is Memorized in Overparameterized Autoencoders? An Inverse Problem Perspective on Memorization Evaluation
Koren Abitbul, Yehuda Dar
Continual Neural Computation
Matteo Tiezzi, Simone Marullo, Federico Becattini, Stefano Melacci
PINN-BO: A Black-box Optimization Algorithm using Physics-Informed Neural Networks
Dat Phan-Trong, Hung The Tran, Alistair Shilton, Sunil Gupta
Enhancing Sharpness-Aware Minimization by Learning Perturbation Radius
Xuehao Wang, Weisen Jiang, Shuai Fu, Yu Zhang
SaccadeDet: A Novel Dual-Stage Architecture for Rapid and Accurate Detection in Gigapixel Images
Wenxi Li, Ruxin Zhang, Haozhe Lin, Yuchen Guo, Chao Ma, ', 'Xiaokang Yang
Physics-Informed Spatio-Temporal Model for Human Mobility Prediction
Quanyan Gao, Chao Li, Qinmin Yang
Adaptive Seasonal-Trend Decomposition for Streaming Time Series Data with Transitions and Fluctuations in Seasonality
Thanapol Phungtua-eng, Yoshitaka Yamamoto
A deep cut into Split Federated Self-supervised Learning
Marcin Przewięźlikowski, Marcin Osial, Bartosz Zieliński, Marek Śmieja
Interpretable and Generalizable Spatiotemporal Predictive Learning with Disentangled Consistency
Jingxuan Wei, Cheng Tan, Zhangyang Gao, Linzhuang Sun, Bihui Yu, Ruifeng Guo, Stan Li
Reinventing Node-Centric Traffic Forecasting for Improved Accuracy and Efficiency
Xu Liu, Yuxuan Liang, Chao Huang, Hengchang Hu, Yushi Cao, Bryan Hooi, Roger Zimmermann
Direct-Effect Risk Minimization for Domain Generalization
Yuhui Li, Zejia Wu, Chao Zhang, Hongyang Zhang
Federated Frank-Wolfe Algorithm
Ali Dadras, Sourasekhar Banerjee, Karthik Prakhya, Alp Yurtsever
Bootstrap Latents of Nodes and Neighbors for Graph Self-Supervised Learning
Yunhui Liu, Huaisong Zhang, Tieke He, Tao Zheng, Jianhua Zhao
Deep Sketched Output Kernel Regression for Structured Prediction
Tamim El Ahmad, Junjie Yang, Pierre Laforgue, Florence d'Alch'e-Buc
Hyperbolic Delaunay Geometric Alignment
Aniss Aiman Medbouhi, Giovanni Luca Marchetti, Vladislav Polianskii, Alexander Kravberg, Petra Poklukar, Anastasia Varava, Danica Kragic
ApmNet: Toward Generalizable Visual Continuous Control with Pre-Trained Image Models
Haitao Wang, Hejun Wu
AdaHAT: Adaptive Hard Attention to the Task in Task-Incremental Learning
Pengxiang Wang, Hongbo Bo, Jun Hong, Weiru Liu, Kedian Mu
Probabilistic Circuits with Constraints via Convex Optimization
Soroush Ghandi, Benjamin Quost, Cassio de Campos
FedAR: Addressing Client Unavailability in Federated Learning
Chutian Jiang, Hansong Zhou, Xiaonan Zhang, Shayok Chakraborty
Selecting from Multiple Strategies Improves the Foreseeable Reasoning of Tool-Augmented Large Language Models
Yongchao Wu, Aron Henriksson
Estimating Direct and Indirect Causal Effects of Spatiotemporal Interventions in Presence of Spatial Interference
Sahara Ali, Omar Faruque, Jianwu Wang
Continuous Geometry-Aware Graph Diffusion via Hyperbolic Neural PDE
Jiaxu Liu, Xinping Yi, Sihao Wu, Xiangyu Yin, Tianle Zhang, Xiaowei Huang, Shi Jin
SpanGNN: Towards Memory-Efficient Graph Neural Networks via Spanning Subgraph Training
Xizhi Gu, Hongzheng Li, Shihong Gao, Xinyan Zhang, Lei Chen, Yingxia Shao
AKGNet: Attribute Knowledge Guided Unsupervised Lung-Infected Area Segmentation
Qing En, Yuhong Guo
Diffusion Model in Normal Gathering Latent Space for Time Series Anomaly Detection
Jiashu Han, Shanshan Feng, Min Zhou, Xinyu Zhang, Yew Soon Ong, Xutao Li
Permutation Dependent Feature Mixing for Multivariate Time Series Forecasting
Rikuto Yamazono, Hirotake Hachiya
Prior Bilinear-based Models for Knowledge Graph Completion
Jiayi Li, Ruilin Luo, Jiaqi Sun, Jing Xiao, Yujiu Yang
Thinking Like an Author: A Zero-shot Learning Approach to Keyphrase Generation with Large Language Model
Siyu Wang, Shengran Dai, Jianhui Jiang
Molecular Graph Representation Learning via Structural Similarity Information
Chengyu Yao, Hong Huang, Hang Gao, Fengge Wu, Haiming Chen, Junsuo Zhao
Efficient Privacy-preserving Truth Discovery and Copy Detection in Crowdsourcing
Xiu Susie Fang, Xinyang Du, Hao Chen, Ziqi Wei, Yong Zhan, Guohao Sun
FCFL: A Fairness Compensation-based Federated Learning Scheme with Accumulated Queues
Lingfu Wang, Zuobin Xiong, Guangchun Luo, Wei Li, Aiguo Chen
MMDL-based Data Augmentation with Domain Knowledge for Time Series Classification
Xiaosheng Li, Yifan Wu, Wei Jiang, Ying Li, Jianguo Li
FALCUN: A Simple and Efficient Deep Active Learning Strategy
Sandra Gilhuber, Anna Beer, Yunpu Ma, Thomas Seidl
Semi-Supervised Heterogeneous Domain Adaptation via Disentanglement and Pseudo-Labelling
Cassio F. Dantas, Raffaele Gaetano, Dino Ienco
Model Fusion via Neuron Transplantation
Muhammed Oz, Nicholas Kiefer, Charlotte Debus, Jasmin Horter, Achim Streit, Markus Gotz
Compressed Federated Reinforcement Learning with a Generative Model
Ali Beikmohammadi, Sarit Khirirat, Sindri Magn'usson
Walking Noise: On Layer-Specific Robustness of Neural Architectures against Noisy Computations and Associated Characteristic Learning Dynamics
Hendrik Borras, Bernhard Klein, Holger Froning
KAFÈ: Kernel Aggregation for Federated
Pian Qi, Diletta Chiaro, Fabio Giampaolo, Francesco Piccialli
On Suppressing Range of Adaptive Stepsizes of Adam to Improve Generalisation Performance
Guoqiang Zhang
Graph Attention Network with Relational Dynamic Factual Fusion for Knowledge Graph Completion
Mei Yu, Yilin Zuo, Wenbin Zhang, Mankun Zhao, Tianyi Xu, Yue Zhao, Jiujiang Guo, Jian Yu
Low-Hanging Fruit: Knowledge Distillation from Noisy Teachers for Open Domain Spoken Language Understanding
Cheng Chen, Bowen Xing, Ivor W. Tsang
The Price of Labelling: A Two-Phase Federated Self-Learning Approach
Tahani Aladwani, Shameem Puthiya Parambath, Christos Anagnostopoulos, Fani Deligianni
Disentangled Representations for Continual Learning: Overcoming Forgetting and Facilitating Knowledge Transfer
Zhaopeng Xu, Qi Qin, Bing Liu, Dongyan Zhao
On the Calibration of Epistemic Uncertainty: Principles, Paradoxes and Conflictual Loss
Mohammed Fellaji, Fr'ed'eric Pennerath, Brieuc Conan-Guez, Miguel Couceiro
Improving the Evaluation and Actionability of Explanation Methods for Multivariate Time Series Classification
Davide Italo Serramazza, Thach Le Nguyen, Georgiana Ifrim
Novel Node Category Detection Under Subpopulation Shift
Hsing-Huan Chung, Shravan Chaudhari, Yoav Wald, Xing Han, Joydeep Ghosh
SynODC: Utilizing the Syntactic Structure for Outlier Detection in Categorical Attributes
Arthur Zylinski, Abdulhakim A. Qahtan
FELIX: Automatic and Interpretable Feature Engineering Using LLMs
Simon Malberg, Edoardo Mosca, Georg Groh
Harnessing Superclasses for Learning from Hierarchical Databases
Nicolas Urbani, Sylvain Rousseau, Yves Grandvalet, Leonardo Tanzi
Approximation Error of Sobolev Regular Functions with tanh Neural Networks: Theoretical Impact on PINNs
Benjamin Girault, R'emi Emonet, Amaury Habrard, Jordan Patracone, Marc Sebban
An Extension of Universal Attacks from the Attacker's Viewpoint
Jordan Patracone, Paul Viallard, Emilie Morvant, Gilles Gasso, Amaury Habrard, St'ephane Canu
Linear Modeling of the Adversarial Noise Space
Jordan Patracone, Lucas Anquetil, Yuan Liu, Gilles Gasso, St'ephane Canu
Classifier-free graph diffusion for molecular property targeting
Matteo Ninniri, Marco Podda, Davide Bacciu
Sparse Explanations of Neural Networks Using Pruned Layer-Wise Relevance Propagation
Paulo Yanez Sarmiento, Simon Witzke, Nadja Klein, Bernhard Renard
ILPO-NET: Network for the Invariant Recognition of Arbitrary Volumetric Patterns in 3D
Dmitrii Zhemchuzhnikov, Sergei Grudinin
Deep Domain Isolation and Sample Clustered Federated Learning for semantic segmentation
Matthis Manthe, Carole Lartizien, Stefan Duffner
Pointer-Guided Pre-Training: Infusing Large Language Models with Paragraph-Level Contextual Awareness
Lars Hillebrand, Prabhupad Pradhan, Christian Bauckhage, Rafet Sifa
Cut-Stitch: a Simple and Effective Data Augmentation Method for Industrial Inspection
Haigen Hu, Jingshan Hong, Kangkang Song, Jinwei Zhu, Weilun Ren
Functional Latent Dynamics for Irregularly Sampled Time Series Forecasting
Christian Klotergens, Vijaya Krishna Yalavarthi, Maximilian Stubbemann, Lars Schmidt-Thieme
Learning Model Agnostic Explanations via Constraint Programming
Frederic Koriche, Jean-Marie Lagniez, Stefan Mengel, Chi Tran
Fair densest subgraph across multiple graphs
Chamalee Wickrama Arachchi, Nikolaj Tatti
A Human-Centric Assessment of the Usefulness of Attribution Methods in Computer Vision
Wiem Ben Rim, Ammar Shaker, Zhao Xu, Kiril Gashteovski, Bhushan Kotnis, Carolin Lawrence, Jurgen Quittek, Sascha Saralajew
Leveraging Plasticity in Incremental Decision Trees
Marco Heyden, Heitor Murilo Gomes, Edouard Fouché
Fast-FedUL: A Training-Free Federated Unlearning with Provable Skew Resilience
Thanh Trung Huynh, Trong Bang Nguyen, Phi Le Nguyen, Thanh Tam Nguyen, Matthias Weidlich, Quoc Viet Hung Nguyen, Karl Aberer
Input Compression with Positional Consistency for Efficient Training and Inference of Transformer Neural Networks
Amrit Nagarajan, Anand Raghunathan
Individual Fairness with Group Awareness under Uncertainty
Zichong Wang, Jocelyn Dzuong, Xiaoyong Yuan, Zhong Chen, Yanzhao Wu, Xin Yao, Wenbin Zhang
FedPrime: An Adaptive Critical Learning Periods Control Framework for Efficient Federated Learning in Heterogeneity Scenarios
Haizhou Du, Zhiyuan Yang
What Drives Online Popularity: Author, Content or Sharers? Estimating Spread Dynamics with Bayesian Mixture Hawkes
Pio Calderon, Marian-Andrei Rizoiu
Disagreement Evaluation of Solutions for Math Word Problem
Yehui Xu, Xuejie Zhang, Jin Wang, Xiaobing Zhou
Co-attention and Contrastive Learning Driven Knowledge Tracing
Ning Zheng, Zhilong Shan
TiNID: A Transfer and Interpretable LLM-enhanced Framework for New Intent Discovery
Shun Zhang, Chaoran Yan, Jian Yang, Wei Zhang, Changyu Ren, Tongliang Li, Jiaqi Bai, Zhoujun Li
Memory-enhanced Emotional Support Conversations with Motivation-driven Strategy Inference
Hao Wang, Bin Guo, Mengqi Chen, Yasan Ding, Qiuyun Zhang, Ying Zhang, Zhiwen Yu
Semi-Automated Construction of Complex Knowledge Base Question Answering Dataset using Large Language Model
Lily Hoang, Fiona Liausvia, Liu Yan, Thanh-Son Nguyen
Graphical Model-Based Lasso for Weakly Dependent Time Series of Tensors
Dorcas Ofori-Boateng, Jaidev Goel, Ivor Cribben, Yulia R. Gel
Multi-Label Adaptive Batch Selection by Highlighting Hard and Imbalanced Samples
Ao Zhou, Bin Liu, Zhaoyang Peng, Jin Wang, Grigorios Tsoumakas
Approximating the Graph Edit Distance with Compact Neighborhood Representations
Franka Bause, Christian Permann, Nils M. Kriege
Online Lⁿatural-Convex Minimization
Ken Yokoyama, Shinji Ito, Tatsuya Matsuoka, Kei Kimura, Makoto Yokoo
Preserving real-world robustness of neural networks under sparsity constraints
Jasmin Viktoria Gritsch, Robert Legenstein, Ozan O
LTCR: Long Temporal Characteristic Reconstruction for Segmentation in Contrastive Learning
Yang He, Yuhan Wu, Junru Zhang, Yabo Dong
LATuner: An LLM-enhanced Database Tuning System based on Adaptive Surrogate Model
Chongjiong Fan, Zhicheng Pan, Wenwen Sun, Chengcheng Yang, Wei-Neng Chen
Improving Meta-learning for Few-shot Text Classification via Label Propagation
Haorui Li, Jie Shao, Xiangqiang Zeng, and Hui Xu
Zero-cost Transition to Multi-Document Processing in Summarization with Multi-Channel Attention
Minh-Quang Nguyen, Duy-Cat Can, Hoang-Quynh Le
PSP: Pre-Training and Structure Prompt Tuning for Graph Neural Networks
Qingqing Ge, Zeyuan Zhao, Yiding Liu, Anfeng Cheng, Xiang Li, Shuaiqiang Wang, Dawei Yin
Wiser than the Wisest of Crowds: The Asch Effect and Polarization Revisited
Dragos Ristache, Fabian Spaeh, Charalampos E. Tsourakakis
Lighter, Better, Faster Multi-Source Domain Adaptation with Gaussian Mixture Models and Optimal Transport
Eduardo Fernandes Montesuma, Fred Ngol`e Mboula, Antoine Souloumiac
Subgraph Retrieval Enhanced by Graph-Text Alignment for Commonsense Question Answering
Boci Peng, Yongchao Liu, Xiaohe Bo, Sheng Tian, Baokun Wang, Chuntao Hong, Yan Zhang
HetCAN: A Heterogeneous Graph Cascade Attention Network with Dual-Level Awareness
Zeyuan Zhao, Qingqing Ge, Anfeng Cheng, Yiding Liu, Xiang Li, Shuaiqiang Wang
Interpetable Target-Feature Aggregation for Multi-Task Learning based on Bias-Variance Analysis
Paolo Bonetti, Alberto Maria Metelli, Marcello Restelli
The Simpler The Better: An Entropy-Based Importance Metric To Reduce Neural Networks' Depth
Victor Qu'etu, Zhu Liao, Enzo Tartaglione
Towards Few-shot Self-explaining Graph Neural Networks
Jingyu Peng, Qi Liu, Linan Yue, Zaixi Zhang, Kai Zhang, Yunhao Sha
Uplift Modeling Under Limited Supervision
George Panagopoulos, Daniele Malitesta, Fragkiskos D. Malliaros, Jun Pang
Self-Supervised Spatial-Temporal Normality Learning for Time Series Anomaly Detection
Yutong Chen, Hongzuo Xum, Guansong Pang, Hezhe Qiao, Yuan Zhou, Mingsheng Shang
Modeling Text-Label Alignment for Hierarchical Text Classification
Ashish Kumar, Durga Toshniwal
Secure Aggregation is Not Private Against Membership Inference Attacks
Khac-Hoang Ngo, Johan Ostman, Giuseppe Durisi, Alexandre Graell i Amat
Evaluating Negation with Multi-way Joins Accelerates Class Expression Learning
Nikolaos Karalis, Alexander Bigerl, Caglar Demir, Liss Heidrich, Axel-Cyrille Ngonga Ngomo
LayeredLiNGAM: A Practical and Fast Method for Learning a Linear Non-Gaussian Structural Equation Model
Hirofumi Suzuki
Enhanced Bayesian Optimization via Preferential Modeling of Abstract Properties
Arun Kumar A V, Alistair Shilton, Sunil Gupta, Santu Rana, Stewart Greenhill, Svetha Venkatesh
Enhancing LLM's Reliability by Iterative Verification Attributions with Keyword Fronting
Yize Sui, Jing Ren, Huibin Tan, Huan Chen, Zhaoye Li, Ji Wang
Reconstructing the Unseen: GRIOT for Attributed Graph Imputation with Optimal Transport
Richard Serrano, Charlotte Laclau, Baptiste Jeudy, Christine Largeron
Introducing Total Harmonic Resistance for Graph Robustness under Edge Deletions
Lukas Berner, Henning Meyerhenke
Counterfactual-based Root Cause Analysis for Dynamical Systems
Juliane Weilbach, Sebastian Gerwinn, Karim Barsim, Martin Franzle
Dropout Regularization in Extended Generalized Linear Models based on Double Exponential Families
Benedikt Lutke Schwienhorst, Lucas Kock, Nadja Klein, David J. Nott
GLADformer: A Mixed Perspective for Graph-level Anomaly Detection
Fan Xu, Nan Wang, Hao Wu, Xuezhi Wen, Dalin Zhang, Siyang Lu, Binyong Li, Wei Gong, Hai Wan, Xibin Zhao
HiGraphDTI: Hierarchical Graph Representation Learning for Drug-Target Interaction Prediction
Bin Liu, Siqi Wu, Jin Wang, Xin Deng, Ao Zhou
On the Two Sides of Redundancy in Graph Neural Networks
Franka Bause, Samir Moustafa, Johannes Langguth, Wilfried N. Gansterer, Nils M. Kriege
Policy Control with Delayed, Aggregate, and Anonymous Feedback
Guilherme Dinis Junior, Sindri Magn'usson, Jaakko Hollm'en
DiffVersify: a scalable approach to differentiable pattern mining with coverage regularization
Thibaut Chataing, Julien Perez, Marc Plantevit, C'eline Robardet
Hierarchical Graph Contrastive Learning for Review-enhanced Recommendation
Changsheng Shui, Xiang Li, Jianpeng Qi, Guiyuan Jiang, Yanwei Yu
Data with Density-Based Clusters: A Generator for Systematic Evaluation of Clustering Algorithms
Philipp Jahn, Christian M. M. Frey, Anna Beer, Collin Leiber, Thomas Seidl
Model-Based Reinforcement Learning with Multi-Task Offline Pretraining
Minting Pan, Yitao Zheng, Yunbo Wang, Xiaokang Yang
Advancing Graph Counterfactual Fairness through Fair Representation Learning
Zichong Wang, Zhibo Chu, Ronald Blanco, Zhong Chen, Shu-Ching Chen, Wenbin Zhang
Continuously Deep Recurrent Neural Networks
Andrea Ceni, Peter Ford Dominey, Claudio Gallicchio, Alessio Micheli, Luca Pedrelli, Domenico Tortorella
Dynamics Adaptive Safe Reinforcement Learning with a Misspecified Simulator
Ruiqi Xue, Ziqian Zhang, Lihe Li, Feng Chen, Yi-Chen Li, Yang Yu, Lei Yuan
CRISPert: A Transformer-based Model for CRISPR-Cas Off-target Prediction
William Jobson Pargeter, Rolf Backofen, Van Dinh Tran
Improved Topology Features for Node Classification on Heterophilic Graphs
Yurui Lai, Taiyan Zhang, Rui Fan
Fast Redescription Mining Using Locality-Sensitive Hashing
Maiju Karjalainen, Esther Galbrun, Pauli Miettinen
σ-GPTs: A New Approach to Autoregressive Models
Arnaud Pannatier, Evann Courdier, Franc cois Fleuret
FairFlow: An Automated Approach to Model-based Counterfactual Data Augmentation For NLP
Ewoenam Kwaku Tokpo, Toon Calders
GrINd: Grid Interpolation Network for Scattered Observations
Andrzej Dulny, Paul Heinisch, Andreas Hotho, Anna Krause
MEGA: Multi-Encoder GNN Architecture for stronger task collaboration and generalization
Faraz Khoshbakhtian, Gaurav Oberoi, Dionne Aleman, Siddhartha Asthana
MetaQuRe: Meta-Learning from Model Quality and Resource Consumption
Raphael Fischer, Marcel Wever, Sebastian Buschjager, Thomas Liebig
Propagation Structure-Semantic Transfer Learning for Robust Fake News Detection
Mengyang Chen, Lingwei Wei, Han Cao, Wei Zhou, Zhou Yan, Songlin Hu
Exploring Contrastive Learning for Long-Tailed Multi-Label Text Classification
Alexandre Audibert, Aur'elien Gauffre, Massih-Reza Amini
Simultaneous Linear Connectivity of Neural Networks Modulo Permutation
Ekansh Sharma, Devin Kwok, Tom Denton, Daniel M. Roy, David Rolnick, Gintare Karolina Dziugaite
Fast Fishing: Approximating BAIT for Efficient and Scalable Deep Active Image Classification
Denis Huseljic, Paul Hahn, Marek Herde, Lukas Rauch, Bernhard Sick
Understanding Domain-Size Generalization in Markov Logic Networks
Florian Chen, Felix Weitkämpfer, Sagar Malhotra
Retrieval-Augmented Mining of Temporal Logic Specifications from Data
Gaia Saveri, Luca Bortolussi
CAM-Based Methods Can See through Walls
Magamed Taimeskhanov, Ronan Sicre, Damien Garreau
Making Alice Appear Like Bob: A Probabilistic Preference Obfuscation Method For Implicit Feedback Recommendation Models
Gustavo Escobedo, Marta Moscati, Peter Muellner, Simone Kopeinik, Dominik Kowald, Elisabeth Lex, Markus Schedl
Leiden-Fusion Partitioning Method for Effective Distributed Training of Graph Embeddings
Yuhe Bai, Camelia Constantin, Hubert Naacke
Automated Design of Linear Bounding Functions for Sigmoidal Nonlinearities in Neural Networks
Matthias Konig, Xiyue Zhang, Holger H. Hoos, Marta Kwiatkowska, Jan N. van Rijn
Efficiently Predicting Mutational Effect on Homologous Proteins by Evolution Encoding
Zhiqiang Zhong, Davide Mottin
Interpretable and Fair Mechanisms for Abstaining Classifiers
Daphne Lenders, Andrea Pugnana, Roberto Pellungrini, Toon Calders, Dino Pedreschi, Fosca Giannotti
Boosting Long-Tail Data Classification with Sparse Prototypical Networks
Alexei Figueroa, Jens-Michalis Papaioannou, Conor Fallon, Alexandra Bekiaridou, Keno Bressem, Stavros Zanos, Felix Gers, Wolfgang Nejdl, Alexander Loser
A Unified Contrastive Loss for Self-Training
Aurélien Gauffre, Julien Horvat, Massih-Reza Amini
Achieving Counterfactual Explanation for Sequence Anomaly Detection
He Cheng, Depeng Xu, Shuhan Yuan, Xintao Wu
Hierarchical Structure-aware Graph Prompting for Drug-Drug Interaction Prediction
Yuhan Ye, Jingbo Zhou, Shuangli Li, Congxi Xiao, Haochao Ying, Hui Xiong
Frugal Generative Modeling for Tabular Data
Alice Lacan, Blaise Hanczar, Michele Sebag
Employing Two-Dimensional Word Embedding for Difficult Tabular Data Stream Classification
Paweł Zyblewski
Univariate Skeleton Prediction in Multivariate Systems Using Transformers
Giorgio Morales, John W. Sheppard
Adaptive Certified Training: Towards Better Accuracy-Robustness Tradeoffs
Zhakshylyk Nurlanov, Frank R. Schmidt, Florian Bernard
Tackling Oversmoothing in GNN via Graph Sparsification
Tanvir Hossain, Khaled Mohammed Saifuddin, Muhammad Ifte Khairul Islam, Farhan Tanvir, Esra Akbas
Enhancing Shortest-Path Graph Kernels via Graph Augmentation
Wei Ye, Hao Tian, Shuhao Tang, Xin Sun
Hyperbolic Contrastive Learning with Model-augmentation for Knowledge-aware Recommendation
Shengyin Sun, Chen Ma
Harnessing the Power of Prompt Experts: Efficient Knowledge Distillation for Enhanced Language Understanding
Xv Meng, Jun Rao, Shuhan Qi, Lei Wang, Jing Xiao, Xuan Wang
Adaptive Knowledge Distillation for Classification of Hand Images using Explainable Vision Transformers
Thanh Thi Nguyen, Campbell Wilson, Janis Dalins
Adaptively Denoising Graph Neural Networks for Knowledge Distillation
Yuxin Guo, Cheng Yang, Chuan Shi, Ke Tu, Zhengwei Wu, Zhiqiang Zhang, Jun Zhou
Lifelong Hierarchical Topic Modeling via Nonparametric Word Embedding Clustering
Jiaxing Yan, Yuyin Lu, Hegang Chen, Jianxing Yu, Yanghui Rao
High-Dimensional Bayesian Optimization via Random Projection of Manifold Subspaces
Quoc-Anh Nguyen, The Hung Tran
CUQ-GNN: Committee-based Graph Uncertainty Quantification using Posterior Networks
Clemens Damke, Eyke Hullermeier
Bundle Recommendation with Item-level Causation-enhanced Multi-view Learning
Huy-Son Nguyen, Tuan-Nghia Bui, Long-Hai Nguyen, Hung Hoang, Cam-Van Thi Nguyen, Hoang-Quynh Le, Duc-Trong Le
Towards Context and Semantic Infused Dialogue Generation Loss Function
Abhisek Tiwari, Muhammed Sinan, Kaushik Roy, Amit Sheth, Sriparna Saha, Pushpak Bhattacharyya
GRETEL 2.0: Generation and Evaluation of Graph Counterfactual Explanations Evolved
Mario Alfonso Prado-Romero, Bardh Prenkaj, Giovanni Stilo
CityFlowER: An Efficient and Realistic Traffic Simulator with Embedded Machine Learning Models
Longchao Da, Chen Chu, Weinan Zhang, Hua Wei
ART: Actually Robust Training
Sebastian Chwilczyński, Kacper Trębacz, Karol Cyganik, Mateusz Małecki, Dariusz Brzeziński
Pattern or Artifact? Interactively Exploring Embedding Quality with TRACE
Edith Heiter, Liesbet Martens, Ruth Seurinck, Martin Guilliams, Tijl De Bie, Yvan Saeys, Jefrey Lijffijt
Interactive motif discovery in time series with persistent homology
Thibaut Germain, Charles Truong, Laurent Oudre
RE-GrievanceAssist: Enhancing Customer Experience through ML-Powered Complaint Management
Venkatesh C, Harshit Oberoi, Anurag Kumar Pandey, Anil Goyal, Nikhil Sikka
An Interactive Tool for Interpretability of Time Series Classification
Brigt Haa vardstun, César Ferri, Jan Arne Telle
FuseRank (Demo): Filtered Vector Search in Multimodal Structured Data
Dimitris Paraschakis, Rasmus Ros, Markus Borg, Per Runeson
KamerRaad: Enhancing Information Retrieval in Belgian National Politics through Hierarchical Summarization and Conversational Interfaces
Alexander Rogiers, Maarten Buyl, Bo Kang, Tijl De Bie
Subgroup Harm Assessor: Identifying Potential Fairness-Related Harms and Predictive Bias
Adam Dubowski, Hilde Weerts, Anouk Wolters, Mykola Pechenizkiy
FinQA: A Training-free Dynamic Knowledge Graph Question Answering System in Finance with LLM-based Revision
Wenbiao Tao, Hanlun Zhu, Keren Tan, Jiani Wang, Yuanyuan Liang, Huihui Jiang, Pengcheng Yuan, Yunshi Lan
VulEXplaineR: XAI for Vulnerability Detection on Assembly Code
Samaneh Mahdavifar, Mohd Saqib, Benjamin C. M. Fung, Philippe Charland, Andrew Walenstein
Guiding Catalogue Enrichment with User Queries
Yupei Du, Jacek Golebiowski, Philipp Schmidt, Ziawasch Abedjan
PeersimGym: An Environment for Solving the Task Offloading Problem with Reinforcement Learning
Frederico Metelo, Cláudia Soares, Stevo Racković, Pedro 'Akos Costa
Robust Interaction-based Relevance Modeling for Online E-Commerce Search
Ben Chen, Huangyu Dai, Xiang Ma, Wen Jiang, Wei Ning
Learning Optimal Linear Precoding for Cell-Free Massive MIMO with GNN
Benjamin Parlier, Lou Salaun, Hong Yang
Multiple Hypergraph Learning for Ephemeral Group Recommendation
Rui Zhao, Beihong Jin, Yimin Lv, Yiyuan Zheng, Weijiang Lai
Spoofing Transaction Detection with Group Perceptual Enhanced Graph Neural Network
Le Kang, Tai-Jiang Mu, XiaoDong Ning
Self-SLAM: A Self-Supervised Learning Based Annotation Method to Reduce Labeling Overhead
Alfiya M. Shaikh, Hrithik Nambiar, Kshitish Ghate, Swarnali Banik, Sougata Sen, Surjya Ghosh, Vaskar Raychoudhury, Niloy Ganguly, Snehanshu Saha
Multi-intent Driven Contrastive Sequential Recommendation
Yiyuan Zheng, Beibei Li, Beihong Jin, Rui Zhao, Weijiang Lai, Tao Xiang
KAT5: Knowledge-Aware Transfer Learning with a Text-to-Text Transfer Transformer
Mohammad Golam Sohrab, Makoto Miwa
Asymmetric Graph-based Deep Reinforcement Learning for Portfolio Optimization
Haoyu Sun, Xin Liu, Yuxuan Bian, Peng Zhu, Dawei Cheng, Yuqi Liang
Code Summarization with Project-Specific Features
Yu Wang, Xin Liu, Xuesong Lu, Aoying Zhou
Unraveling Anomalies in Time: Unsupervised Discovery and Isolation of Anomalous Behavior in Bio-regenerative Life Support System Telemetry
Ferdinand Rewicki, Jakob Gawlikowski, Julia Niebling, Joachim Denzler
Long-term Fairness in Ride-Hailing Platform
Yufan Kang, Jeffrey Chan, Wei Shao, Flora D. Salim, Christopher Leckie
A Merge Sort Based Ranking System for the Evaluation of Large Language Models
Chenchen Li, Linfeng Shi, Chunyi Zhou, Zhaoxin Huan, Chengfu Tang, Xiaolu Zhang, Xudong Wang, Jun Zhou, Song Liu
Enhancing HVAC Control Efficiency: A Hybrid Approach Using Imitation and Reinforcement Learning
Kevlyn Kadamala, Des Chambers, Enda Barrett
Synthesis of Standard 12-lead ECG from Single-lead ECG using Shifted Diffusion Models
Jingwei Liu, Hongyan Li, Shenda Hong
SAGS-DynamicBio: Integrating Semantic-Aware and Graph Structure-Aware Embedding for Dynamic Biological Data with Knowledge Graphs
Yao Liu, Yongfei Zhang, Xin Wang
Graph Machine Learning for fast product development from formulation trials
Manuel Dileo, Raffaele Olmeda, Margherita Pindaro, Matteo Zignani
HPExplorer: XAI method to explore the relationship between hyperparameters and model performance
Yulia Grushetskaya, Mike Sips, Reyko Schachtschneider, Mohammadmehdi Saberioon, Akram Mahan
Boosting Patient Representation Learning via Graph Contrastive Learning
Zhenhao Zhang, Yuxi Liu, Jiang Bian, Antonio Jimeno Yepes, Jun Shen, Fuyi Li, Guodong Long, Flora D. Salim
Time Series Clustering for Enhanced Dynamic Allocation in A/B Testing
Emmanuelle Claeys, Myriam Maumy-Bertrand, Pierre Gancc
Reinforcement learning meets microeconomics: Learning to designate price-dependent supply and demand for automated trading
Łukasz Lepak, Paweł Wawrzynski
Spatial Transfer Learning for Estimating PM₂.₅ in Data-poor Regions
Shrey Gupta, Yongbee Park, Jianzhao Bi, Suyash Gupta, Andreas Züfle, Avani Wildani, Yang Liu
Leveraging Foundation Models for Multi-modal Federated Learning with Incomplete Modality
Liwei Che, Jiaqi Wang, Xinyue Liu, Fenglong Ma
Contrastive Learning Enhanced Diffusion Model for Improving Tropical Cyclone Intensity Estimation with Test-time Adaptation
Ziheng Zhou, Haojia Zuo, Ying Zhao, Wenguang Chen
BESTMVQA: A Benchmark Evaluation System for Medical Visual Question Answering
Xiaojie Hong, Zixin Song, Liangzhi Li, Xiaoli Wang, Feiyan Liu
AeroINR: Meta-learning for efficient generation of aerodynamic geometries
Tom Bamford, David Toal, Andy Keane
MT-HCCAR: Multi-Task Deep Learning with Hierarchical Classification and Attention-based Regression for Cloud Property Retrieval
Xingyan Li, Andrew M. Sayer, Ian T. Carroll, Xin Huang, Jianwu Wang
Machine Learning Based Tool for Automated Sperm Cell Tracking and Sperm Bundle Detection
Jakub Horenin, Veronika Magdanz, Islam S. M. Khalil, Anke Klingner, Alexander Kovalenko, Miroslav v Cepek
DISCO: An End-to-End Bandit Framework for Personalised Discount Allocation
Jason Shuo Zhang, Benjamin Howson, Panayiota Savva, Eleanor Loh
Advancing Solar Flare Prediction using Deep Learning with Active Region Patches
Chetraj Pandey, Temitope Adeyeha, Jinsu Hong, Rafal A. Angryk, Berkay Aydin
Exceptional Subitizing Patterns: Exploring Mathematical Abilities of Finnish Primary School Children with Piecewise Linear Regression
Rianne M. Schouten, Wouter Duivesteijn, Pekka Räsänen, Jacob M. Paul, Mykola Pechenizkiy
Intent Enhanced Self-Supervised Hypergraph Learning for Session-Based Recommendation
Xiu Susie Fang, Yonggang Wu, Jinhu Lu, Xiaoyu Gu, Guohao Sun, Yong Zhan
Missing Data Imputation: Do Advanced ML/DL Techniques Outperform Traditional Approaches?
Youran Zhou, Mohamed Reda Bouadjenek, Sunil Aryal
Evaluating Vision Transformer Models for Visual Quality Control in Industrial Manufacturing
Miriam Alber, Christoph Hönes, Patrick Baier
GraphRPM: Risk Pattern Mining on Industrial Large Attributed Graphs
Sheng Tian, Xintan Zeng, Yifei Hu, Baokun Wang, Yongchao Liu, Yue Jin, Changhua Meng, Chuntao Hong, Tianyi Zhang, Weiqiang Wang
Solving a Real-World Optimization Problem Using Proximal Policy Optimization with Curriculum Learning and Reward Engineering
Abhijeet Pendyala, Asma Atamna, Tobias Glasmachers
Spatial-Temporal PDE Networks for Traffic Flow Forecasting
Tianshu Bao, Hua Wei, Junyi Ji, Daniel Work, Taylor Thomas Johnson
Symbolic Prompt Tuning Completes the App Promotion Graph
Zhongyu Ouyang, Chunhui Zhang, Shifu Hou, Shang Ma, Chaoran Chen, Toby Li, Xusheng Xiao, Yanfang Ye
Boosting Protein Language Models with Negative Sample Mining
Yaoyao Xu, Xinjian Zhao, Xiaozhuang Song, Benyou Wang, Tianshu Yu
MedSyn: LLM-based Synthetic Medical Text Generation Framework
Gleb Kumichev, Pavel Blinov, Yulia Kuzkina, Vasily Goncharov, Galina Zubkova, Nikolai Zenovkin, Aleksei Goncharov, Andrey Savchenko
A Crystal Knowledge-enhanced Pre-training Framework for Crystal Property Estimation
Haomin Yu, Yanru Song, Jilin Hu, Chenjuan Guo, Bin Yang, Christian S. Jensen
Multiplex Community Detection for Resilient Electrical Segmentation Enabling Management of an Increasingly Complex Power Grid
Noureddine Henka, Sami Tazi, Mohamad Assaad
Bandits for Sponsored Search Auctions under Unknown Valuation Model: Case Study in E-Commerce Advertising
Danil Provodin, Jérémie Joudioux, Eduard Duryev
Unbiased Recommendation through Invariant Representation Learning
Min Tang, Lixin Zou, Shujie Cui, Shiuan-ni Liang, Zhe Jin
Enhancing Multi-Objective Optimisation through Machine Learning-Supported Multiphysics Simulation
Diego Botache, Jens Decke, Winfried Ripken, Abhinay Dornipati, Franz Gotz-Hahn, Mohamed Ayeb, Bernhard Sick
DistALANER: Distantly Supervised Active Learning Augmented Named Entity Recognition in the Open Source Software Ecosystem
Somnath Banerjee, Avik Dutta, Aaditya Agrawal, Rima Hazra, Animesh Mukherjee
DiffSynth: Latent In-Iteration Deflickering for Realistic Video Synthesis
Zhongjie Duan, Lizhou You, Chengyu Wang, Cen Chen, Ziheng Wu, Weining Qian, Jun Huang
Offline Imitation of Badminton Player Behavior via Experiential Contexts and Brownian Motion
Kuang-Da Wang, Wei-Yao Wang, Ping-Chun Hsieh, Wen-Chih Peng
Fast and Adaptive Questionnaires for Voting Advice Applications
Fynn Bachmann, Cristina Sarasua, Abraham Bernstein
Job Title Prediction as A Dual Task of Expertise Prediction in Open Source Software
Xin Liu, Yu Wang, Qiwen Dong, Xuesong Lu
LLMs in the Loop: Leveraging Large Language Model Annotations for Active Learning in Low-Resource Languages
Nataliia Kholodna, Sahib Julka, Mohammad Khodadadi, Muhammed Nurullah Gumus, Michael Granitzer
Multi-spectral Gradient Residual Network For Haze Removal In Multi-sensor Remote Sensing Imagery
Xian Yang, Ranga Raju Vatsavai
ExTea: An Evolutionary Algorithm-Based Approach for Enhancing Explainability in Time-Series Models
Yiran Huang, Yexu Zhou, Haibin Zhao, Likun Fang, Till Riedel, Michael Beigl
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