Learning Objective-Specific Active Learning Strategies with Attentive Neural Processes
Tim Bakker, Herke van Hoof, Max Welling
REAL: A Representative Error Driven Approach for Active Learning
Cheng Chen, Yong Wang, Lizi Liao, Yueguo Chen, Xiaoyong Du
Knowledge-driven Active Learning
Gabriele Ciravegna, Frédéric Precioso, Alessandro Betti, Kevin Mottin, Marco Gori
ActiveGLAE: A Benchmark for Deep Active Learning with Transformers
Lukas Rauch, Matthias Aßenmacher, Denis Huseljic, Moritz Wirth, Bernd Bischl, Bernhard Sick
DiffusAL: Coupling Active Learning with Graph Diffusion for Label-Efficient Node Classification
Sandra Gilhuber, Julian Busch, Daniel Rotthues, Christian M.M. Frey, Thomas Seidl
Quantifying Robustness to Adversarial Word Substitutions
Yuting Yang, Pei Huang, Juao Cao, Feifei Ma, Jian Zhang, Jintao Li
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
Adversarial Imitation Learning with Controllable Rewards for Text Generation
Keizaburo Nishikino, Kenichi Kobayashi
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
Adversarial Sample Detection Through Neural Network Transport Dynamics
Skander Karkar, Patrick Gallinari, Alain Rakotomamonjy
CVTGAD: Simplified Transformer with Cross-View Attention for Unsupervised Graph-level Anomaly Detection
Jindong Li, Qianli Xing, Qi Wang, Yi Chang
Graph-level Anomaly Detection via Hierarchical Memory Networks
Chaoxi Niu, Guansong Pang, Ling Chen
Semi-Supervised Learning from Active Noisy Soft Labels for Anomaly Detection
Timo Martens, Lorenzo Perini, Jesse Davis
Learning with Noisy Labels by Adaptive Gradient-Based Outlier Removal
Anastasiia Sedova, Lena Zellinger, Benjamin Roth
DSV: An Alignment Validation Loss for Self-supervised Outlier Model Selection
Jaemin Yoo, Yue Zhao, Lingxiao Zhao, Leman Akoglu
Marvolo: Programmatic Data Augmentation for Deep Malware Detection
Mike Wong, Edward Raff, James Holt, Ravi Netravali
A Transductive Forest for Anomaly Detection with Few Labels
Jingrui Zhang, Ninh Pham, Gillian Dobbie
Co-evolving Graph Reasoning Network for Emotion-Cause Pair Extraction
Bowen Xing, Ivor W. Tsang
SpotGAN: A Reverse-Transformer GAN Generates Scaffold-Constrained Molecules with Property Optimization
Chen Li, Yoshihiro Yamanishi
Spatio-temporal Pyramid Networks for Traffic Forecasting
Jia Hu, Chu Wang, Xianghong Lin
A Passage Retrieval Transformer-based Re-ranking Model for Truthful Consumer Health Search
Rishabh Upadhyay, Gabriella Pasi, Marco Viviani
KESHEM: Knowledge Enabled Short Health Misinformation Detection Framework
Fei Liu, Yibo Li, Meiyun Zuo
Dynamic Thresholding for Accurate Crack Segmentation using Multi-Objective Optimization
Qin Lei, Jiang Zhong, Chen Wang, Yang Xia, Yangmei Zhou
CoSP: Co-supervised pre-training of pocket and ligand
Zhangyang Gao, Cheng Tan, Jun Xia, Stan Z. Li
Decompose, Then Reconstruct: A Framework of Network Structures for Click-Through Rate Prediction
Jiaming Li, Lang Lang, Zhenlong Zhu, Haozhao Wang, Ruixuan Li, Wenchao Xu
DynaBench: A benchmark dataset for learning dynamical systems from low-resolution data
Andrzej Dulny, Andreas Hotho, Anna Krause
Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry
Jonas Gregor Wiese, Lisa Wimmer, Theodore Papamarkou, Bernd Bischl, Stephan Günnemann, David Rügamer
Cooperative Bayesian optimization for imperfect agents
Ali Khoshvishkaie, Petrus Mikkola, Pierre-Alexandre Murena, Samuel Kaski
Leveraging Variational Autoencoders for Multiple Data Imputation
Breeshey Roskams-Hieter, Jude Wells, Sara Wade
A New Framework for Classifying Probability Density Functions
Anis Fradi, Chafik Samir
Learning Conditional Instrumental Variable Representation for Causal Effect Estimation
Debo Cheng, Ziqi Xu, Jiuyong Li, Lin Liu, Thuc Duy Le, Jixue Liu
A kNN-based Non-Parametric Conditional Independence Test for Mixed Data and Application in Causal Discovery
Johannes Huegle, Christopher Hagedorn, Rainer Schlosser
PEACE: Cross-Platform Hate Speech Detection - A Causality-guided Framework
Paras Sheth, Tharindu Kumarage, Raha Moraffah, Aman Chadha, Huan Liu
Estimating Treatment Effects Under Heterogeneous Interference
Xiaofeng Lin, Guoxi Zhang, Xiaotian Lu, Han Bao, Koh Takeuchi, Hisashi Kashima
Powered Dirichlet Process - Controlling the ``Rich-Get-Richer'' Assumption in Bayesian Clustering
Gaël Poux-Médard, Julien Velcin, Sabine Loudcher
Contrastive Hierarchical Clustering
Michał Znalezniak, Przemysław Rola, Patryk Kaszuba, Jacek Tabor, Marek Śmieja
Contrastive Learning with Cluster-preserving Augmentation for Attributed Graph Clustering
Yimei Zheng, Caiyan Jia, Jian Yu
k-SubMix: Common Subspace Clustering on Mixed-Type Data
Mauritius Klein, Collin Leiber, Christian Böhm
Transformer-based Contrastive Multi-view Clustering via Ensembles
Mingyu Zhao, Weidong Yang, Feiping Nie
A Deep Dynamic Latent Block Model for the Co-clustering of Zero-Inflated Data Matrices
Giulia Marchello, Marco Corneli, Charles Bouveyron
cuSLINK: Single-Linkage Agglomerative Clustering on the GPU
Corey J. Nolet, Divye Gala, Alex Fender, Mahesh Doijade, Joe Eaton, Edward Raff, John Zedlewski, Brad Rees, Tim Oates
Socially Fair Center-based and Linear Subspace Clustering
Sruthi Gorantla, Kishen N Gowda, Amit Deshpande, Anand Louis
Visualizing Overlapping Biclusterings and Boolean Matrix Factorizations
Thibault Marette, Pauli Miettinen, Stefan Neumann
Sample Prior Guided Robust Model Learning to Suppress Noisy Labels
Wenkai Chen, Chuang Zhu, Mengting Li
Negative Prototypes Guided Contrastive Learning for Weakly Supervised Object Detection
Yu Zhang, Chuang Zhu, Guoqing Yang, Siqi Chen
Voting from Nearest Tasks: Meta-Vote Pruning of Pre-trained Models for Downstream Tasks
Haiyan Zhao, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang
Make A Long Image Short: Adaptive Token Length for Vision Transformers
Qiqi Zhou, Yichen Zhu
Graph Rebasing and Joint Similarity Reconstruction for Cross-Modal Hash Retrieval
Dan Yao, Zhixin Li
ARConvL: Adaptive Region-Based Convolutional Learning for Multi-class Imbalance Classification
Shuxian Li, Liyan Song, Xiaoyu Wu, Zheng Hu, Yiu-ming Cheung, Xin Yao
Binary domain generalization for sparsifying binary neural networks
Riccardo Schiavone, Francesco Galati, Maria A. Zuluaga
Efficient Hyperdimensional Computing
Zhanglu Yan, Shida Wang, Kaiwen Tang, Weng-Fai Wong
Rényi Divergence Deep Mutual Learning
Weipeng Fuzzy Huang, Junjie Tao, Changbo Deng, Ming Fan, Wenqiang Wan, Qi Xiong, Guangyuan Piao
Is my Neural Net driven by the MDL Principle?
Eduardo Brandao, Stefan Duffner, Rémi Emonet, Amaury Habrard, François Jacquenet, Marc Sebban
Scoring rule nets: Beyond mean target prediction in multivariate regression
Daan Roordink, Sibylle Hess
Learning distinct features helps, provably
Firas Laakom, Jenni Raitoharju, Alexandros Iosifidis, Moncef Gabbouj
Continuous Depth Recurrent Neural Differential Equations
Srinivas Anumasa, Geetakrishnasai Gunapati, P.K. Srijith
Mitigating Algorithmic Bias with Limited Annotations
Guanchu Wang, Mengnan Du, Ninghao Liu, Na Zou, Xia Hu
FG²AN: Fairness-aware Graph Generative Adversarial Networks
Zichong Wang, Charles Wallace, Albert Bifet, Xin Yao, Wenbin Zhang
Targeting the Source: Selective Data Curation for Debiasing NLP Models
Yacine Gaci, Boualem Benatallah, Fabio Casati, Khalid Benabdeslem
Fairness in Multi-Task Learning via Wasserstein Barycenters
François Hu, Philipp Ratz, Arthur Charpentier
REST: Enhancing Group Robustness in DNNs through Reweighted Sparse Training
Jiaxu Zhao, Lu Yin, Shiwei Liu, Meng Fang, Mykola Pechenizkiy
How To Overcome Confirmation Bias in Semi-Supervised Image Classification By Active Learning
Sandra Gilhuber, Rasmus Hvingelby, Mang Ling Ada Fok, Thomas Seidl
Towards Practical Federated Causal Structure Learning
Zhaoyu Wang, Pingchuan Ma, Shuai Wang
Triplets Oversampling for Class Imbalanced Federated Datasets
Chenguang Xiao, Shuo Wang
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
Practical and General Backdoor Attacks against Vertical Federated Learning
Yuexin Xuan, Xiaojun Chen, Zhendong Zhao, Bisheng Tang, Ye Dong
Not All Tasks are Equal: a Parameter-efficient Task Reweighting Method for Few-shot learning
Xin Liu, Yilin Lyu, Liping Jing, Tieyong Zeng, Jian Yu
Boosting Generalized Few-Shot Learning by Scattering Intra-Class Distribution
Yunlong Yu, Lisha Jin, Yingming Li
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
Meta-HRNet: A High Resolution Network for Coarse-to-Fine Few-Shot Classification
Zhaochen Li, Kedian Mu
MuSE: A Multi-scale Emotional Flow Graph Model for Empathetic Dialogue Generation
Deji Zhao, Donghong Han, Ye Yuan, Chao Wang, Shuangyong Song
Posterior Consistency for Missing Data in Variational Autoencoders
Timur Sudak, Sebastian Tschiatschek
KnowPrefix-Tuning: A Two-Stage Prefix-Tuning Framework for Knowledge-Grounded Dialogue Generation
Jiaqi Bai, Zhao Yan, Ze Yang, Jian Yang, Xinnian Liang, Hongcheng Guo, Zhoujun Li
Learning Data Representations with Joint Diffusion Models
Kamil Deja, Tomasz Trzciński, Jakub M. Tomczak
MiDi: Mixed Graph and 3D Denoising Diffusion for Molecule Generation
Clément Vignac, Nagham Osman, Laura Toni, Pascal Frossard
Cold-start Multi-hop Reasoning by Hierarchical Guidance and Self-verification
Mayi Xu, Ke Sun, Yongqi Li, Tieyun Qian
Efficient Fine-tuning Large Language Models for Knowledge-Aware Response Planning
Minh Nguyen, Kishan K C, Toan Nguyen, Ankit Chadha, Thuy Vu
Attentive Multi-Layer Perceptron for Non-autoregressive Generation
Shuyang Jiang, Jun Zhang, Jiangtao Feng, Lin Zheng, Lingpeng Kong
MASTER: Multi-task Pre-trained Bottlenecked Masked Autoencoders are Better Dense Retrievers
Kun Zhou, Xiao Liu, Yeyun Gong, Wayne Xin Zhao, Daxin Jiang, Nan Duan, Ji-Rong Wen
Duplicate Multi-modal Entities Detection with Graph Contrastive Self-training Network
Shuyun Gu, Xiao Wang, Chuan Shi
Graph Contrastive Representation Learning with Input-aware and Cluster-aware Regularization
Jin Li, Bingshi Li, Qirong Zhang, Xinlong Chen, Xinyang Huang, Longkun Guo, Yang-Geng Fu
Temporal Graph Representation Learning with Adaptive Augmentation Contrastive
Hongjiang Chen, Pengfei Jiao, Huijun Tang, Huaming Wu
Hierarchical Graph Contrastive Learning
Hao Yan, Senzhang Wang, Jun Yin, Chaozhuo Li, Junxing Zhu, Jianxin Wang
Learning to Augment Graph Structure for both Homophily and Heterophily Graphs
Lirong Wu, Cheng Tan, Zihan Liu, Zhangyang Gao, Haitao Lin, Stan Z. Li
Learning Representations for Bipartite Graphs using Multi-Task Self-Supervised Learning
Akshay Sethi, Sonia Gupta, Aakarsh Malhotra, Siddhartha Asthana
ChiENN: Embracing Molecular Chirality with Graph Neural Networks
Piotr Gaiński, Michał Koziarski, Marek Śmieja, Jacek Tabor
Multi-Label Image Classification with Multi-Scale Global-Local Semantic Graph Network
Wenlan Kuang, Qiangxi Zhu, Zhixin Li
CasSampling: Exploring Efficient Cascade Graph Learning for Popularity Prediction
Guixiang Cheng, Xin Yan, Shengxiang Gao, Guangyi Xu, Xianghua Miao
Boosting Adaptive Graph Augmented MLPs via Customized Knowledge Distillation
Shaowei Wei, Zhengwei Wu, Zhiqiang Zhang, Jun Zhou
ENGAGE: Explanation Guided Data Augmentation for Graph Representation Learning
Yucheng Shi, Kaixiong Zhou, Ninghao Liu
Modeling Graphs Beyond Hyperbolic: Graph Neural Networks in Symmetric Positive Definite Matrices
Wei Zhao, Federico Lopez, J. Maxwell Riestenberg, Michael Strube, Diaaeldin Taha, Steve Trettel
Leveraging Free Labels to Power Up Heterophilic Graph Learning in Weakly-Supervised Settings: An Empirical Study
Xugang Wu, Huijun Wu, Ruibo Wang, Duanyu Li, Xu Zhou, Kai Lu
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
The Mont Blanc of Twitter: Identifying Hierarchies of Outstanding Peaks in Social Networks
Maximilian Stubbemann, Gerd Stumme
RBNets: A Reinforcement Learning Approach for Learning Bayesian Network Structure
Zuowu Zheng, Chao Wang, Xiaofeng Gao, Guihai Chen
A Unified Spectral Rotation Framework Using a Fused Similarity Graph
Yuting Liang, Wen Bai, Yuncheng Jiang
SimSky: An Accuracy-Aware Algorithm for Single-Source SimRank Search
Liping Yan, Weiren Yu
Quantifying Node-based Core Resilience
Jakir Hossain, Sucheta Soundarajan, Ahmet Erdem Sarıyüce
Construction and Training of Multi-Associative Graph Networks
Adrian Horzyk, Daniel Bulanda, Janusz A. Starzyk
Skeletal cores and graph resilience
Danylo Honcharov, Ahmet Erdem Sarıyüce, Ricky Laishram, Sucheta Soundarajan
GDM: Dual Mixup for Graph Classification with Limited Supervision
Abdullah Alchihabi, Yuhong Guo
SL-Diff: Two-stage Denoising Diffusion Model for Source Localization in Graph Inverse Problems
Bosong Huang, Weihao Yu, Ruzhong Xie, Jing Xiao, Jin Huang
Sparse Neural Additive Model: Interpretable Deep Learning with Feature Selection via Group Sparsity
Shiyun Xu, Zhiqi Bu, Pratik Chaudhari, Ian J. Barnett
XAI with Machine Teaching when Humans Are (Not) Informed about the Irrelevant Features
Brigt Arve Toppe Håvardstun, Cèsar Ferri, Jose Hernández-Orallo, Pekka Parviainen, Jan Arne Telle
Generating robust counterfactual explanations
Victor Guyomard, Françoise Fessant, Thomas Guyet, Tassadit Bouadi, Alexandre Termier
Neural models for Factual Inconsistency Classification with Explanations
Tathagata Raha, Mukund Choudhary, Abhinav Menon, Harshit Gupta, K V Aditya Srivatsa, Manish Gupta, Vasudeva Varma
iSAGE: An Incremental Version of SAGE for Online Explanation on Data Streams
Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier
Interpretation Attacks and Defenses on Predictive Models using Electronic Health Records
Fereshteh Razmi, Jian Lou, Yuan Hong, Li Xiong
An Empirical Evaluation of the Rashomon Effect in Explainable Machine Learning
Sebastian Müller, Vanessa Toborek, Katharina Beckh, Matthias Jakobs, Christian Bauckhage, Pascal Welke
Interpretable Regional Descriptors: Hyperbox-Based Local Explanations
Susanne Dandl, Giuseppe Casalicchio, Bernd Bischl, Ludwig Bothmann
TIGTEC : Token Importance Guided TExt Counterfactuals
Milan Bhan, Jean-Noël Vittaut, Nicolas Chesneau, Marie-Jeanne Lesot
Towards Few-shot Inductive Link Prediction on Knowledge Graphs: A Relational Anonymous Walk-guided Neural Process Approach
Zicheng Zhao, Linhao Luo, Shirui Pan, Quoc Viet Hung Nguyen, Chen Gong
Comparing Apples and Oranges? On the Evaluation of Methods for Temporal Knowledge Graph Forecasting
Julia Gastinger, Timo Sztyler, Lokesh Sharma, Anett Schuelke, Heiner Stuckenschmidt
Improving Few-Shot Inductive Learning on Temporal Knowledge Graphs using Confidence-Augmented Reinforcement Learning
Zifeng Ding, Jingpei Wu, Zongyue Li, Yunpu Ma, Volker Tresp
Clifford Embeddings -- A Generalized Approach for Embedding in Normed Algebras
Caglar Demir, Axel-Cyrille Ngonga Ngomo
Exploring Word-Sememe Graph-Centric Chinese Antonym Detection
Zhaobo Zhang, Pingpeng Yuan, Hai Jin
Distinct Geometrical Representations for Temporal and Relational Structures in Knowledge Graphs
Bowen Song, Chengjin Xu, Kossi Amouzouvi, Maocai Wang, Jens Lehmann, Sahar Vahdati
LitCQD: Multi-Hop Reasoning in Incomplete Knowledge Graphs with Numeric Literals
Caglar Demir, Michel Wiebesiek, Renzhong Lu, Axel-Cyrille Ngonga Ngomo, Stefan Heindorf
Cross Model Parallelism for Faster Bidirectional Training of Large Convolutional Neural Networks
An Xu, Yang Bai
PROPAGATE: a seed propagation framework to compute Distance-based metrics on Very Large Graphs
Giambattista Amati, Antonio Cruciani, Daniele Pasquini, Paola Vocca, Simone Angelini
Towards Memory-Efficient Training for Extremely Large Output Spaces -- Learning with 670k Labels on a Single Commodity GPU
Erik Schultheis, Rohit Babbar
Unsupervised Deep Cross-Language Entity Alignment
Chuanyu Jiang, Yiming Qian, Lijun Chen, Yang Gu, Xia Xie
Corpus-Based Relation Extraction by Identifying and Refining Relation Patterns
Sizhe Zhou, Suyu Ge, Jiaming Shen, Jiawei Han
Learning to Play Text-based Adventure Games with Maximum Entropy Reinforcement Learning
Weichen Li, Rati Devidze, Sophie Fellenz
SALAS: Supervised Aspect Learning Improves Abstractive Multi-Document Summarization through Aspect Information Loss
Haotian Chen, Han Zhang, Houjing Guo, Shuchang Yi, Bingsheng Chen, Xiangdong Zhou
KL Regularized Normalization Framework for Low Resource Tasks
Neeraj Kumar, Ankur Narang, Brejesh Lall
Improving Autoregressive NLP Tasks via Modular Linearized Attention
Victor Agostinelli, Lizhong Chen
Enhancing Table Retrieval with Dual Graph Representations
Tianyun Liu, Xinghua Zhang, Zhenyu Zhang, Yubin Wang, Quangang Li, Shuai Zhang, Tingwen Liu
A Few Good Sentences: Content Selection For Abstractive Text Summarization
Vivek Srivastava, Savita Bhat, Niranjan Pedanekar
Encouraging Sparsity in Neural Topic Modeling with Non-Mean-Field Inference
Jiayao Chen, Rui Wang, Jueying He, Mark Junjie Li
The Metric is the Message: Benchmarking challenges for neural symbolic regression
Amanda Bertschinger, Q. Tyrell Davis, James Bagrow, Joshua Bongard
Neural Class Expression Synthesis in ALCHIQ(D)
N’Dah Jean Kouagou, Stefan Heindorf, Caglar Demir, Axel-Cyrille Ngonga Ngomo
Deep Explainable Relational Reinforcement Learning: A Neuro-Symbolic Approach
Rishi Hazra, Luc De Raedt
ReOnto: A Neuro-Symbolic Approach for Biomedical Relation Extraction
Monika Jain, Kuldeep Singh, Raghava Mutharaju
NKFAC: A Fast and Stable KFAC Optimizer for Deep Neural Networks
Ying Sun, Hongwei Yong, Lei Zhang
Exact Combinatorial Optimization with Temporo-Attentional Graph Neural Networks
Mehdi Seyfi, Amin Banitalebi-Dehkordi, Zirui Zhou, Yong Zhang
Improved Multi-Label Propagation for Small Data with Multi-Objective Optimization
Khadija Musayeva, Mickaël Binois
Fast Convergence of Random Reshuffling under Over-Parameterization and the Polyak-Łojasiewicz Condition
Chen Fan, Christos Thrampoulidis, Mark Schmidt
A scalable solution for the extended multi-channel facility location problem
Etika Agarwal, Karthik S. Gurumoorthy, Ankit Ajit Jain, Shantala Manchenahally
Online State Exploration: Competitive Worst Case and Learning-Augmented Algorithms
Sungjin Im, Benjamin Moseley, Chenyang Xu, Ruilong Zhang
Learning Graphical Factor Models with Riemannian Optimization
Alexandre Hippert-Ferrer, Florent Bouchard, Ammar Mian, Titouan Vayer, Arnaud Breloy
ConGCN: Factorized Graph Convolutional Networks for Consensus Recommendation
Boyu Li, Ting Guo, Xingquan Zhu, Yang Wang, Fang Chen
Long-tail Augmented Graph Contrastive Learning for Recommendation
Qian Zhao, Zhengwei Wu, Zhiqiang Zhang, Jun Zhou
News Recommendation via Jointly Modeling Event Matching and Style Matching
Pengyu Zhao, Shoujin Wang, Wenpeng Lu, Xueping Peng, Weiyu Zhang, Chaoqun Zheng, Yonggang Huang
BalancedQR : A framework for balanced query recommendation
Harshit Mishra, Sucheta Soundarajan
On the Distributional Convergence of Temporal Difference Learning
Jie Dai, Xuguang Chen
Offline Reinforcement Learning with On-Policy Q-Function Regularization
Laixi Shi, Robert Dadashi, Yuejie Chi, Pablo Samuel Castro, Matthieu Geist
Alpha Elimination: Using Deep Reinforcement Learning to Reduce Fill-In during Sparse Matrix Decomposition
Arpan Dasgupta, Pawan Kumar
Learning Hierarchical Planning-Based Policies from Offline Data
Jan Wöhlke, Felix Schmitt, Herke van Hoof
Stepsize Learning for Policy Gradient Methods in Contextual Markov Decision Processes
Luca Sabbioni, Francesco Corda, Marcello Restelli
Invariant Lipschitz Bandits: A Side Observation Approach
Nam Phuong Tran, Long Tran-Thanh
Filtered Observations for Model-based Multi-agent Reinforcement Learning
Linghui Meng, Xuantang Xiong, Yifan Zang, Xi Zhang, Guoqi Li, Dengpeng Xing, Bo Xu
Unsupervised Salient Patch Selection for Data-Efficient Reinforcement Learning
Zhaohui Jiang, Paul Weng
Eigensubspace of Temporal-Difference Dynamics and How It Improves Value Approximation in Reinforcement Learning
Qiang He, Tianyi Zhou, Meng Fang, Setareh Maghsudi
Learning Disentangled Discrete Representations
David Friede, Christian Reimers, Heiner Stuckenschmidt, Mathias Niepert
Boosting Object Representation Learning via Motion and Object Continuity
Quentin Delfosse, Wolfgang Stammer, Thomas Rothenbächer, Dwarak Vittal, Kristian Kersting
Learning Geometric Representations of Objects via Interaction
Alfredo Reichlin, Giovanni Luca Marchetti, Hang Yin, Anastasiia Varava, Danica Kragic
On the good behaviour of Extremely Randomized Trees in Random Forest-distance computation
Manuele Bicego, Ferdinando Cicalese
Hypernetworks build Implicit Neural Representations of Sounds
Filip Szatkowski, Karol J. Piczak, Przemysław Spurek, Jacek Tabor, Tomasz Trzciński
Contrastive Representation through Angle and Distance based Loss for Partial Label Learning
Priyanka Chudasama, Tushar Kadam, Rajat Patel, Aakarsh Malhotra, Manoj Mangam
Equivariant Representation Learning in the Presence of Stabilizers
Luis Armando Pérez Rey, Giovanni Luca Marchetti, Danica Kragic, Dmitri Jarnikov, Mike Holenderski
Towards Understanding the Mechanism of Contrastive Learning via Similarity Structure: A Theoretical Analysis
Hiroki Waida, Yuichiro Wada, Léo Andéol, Takumi Nakagawa, Yuhui Zhang, Takafumi Kanamori
BipNRL : Mutual Information Maximization on Bipartite Graphs for Node Representation Learning
Pranav Poduval, Gaurav Oberoi, Sangam Verma, Ayush Agarwal, Karamjit Singh, Siddhartha Asthana
MMA: Multi-Metric-Autoencoder for Analyzing High-Dimensional and Incomplete Data
Cheng Liang, Di Wu, Yi He, Teng Huang, Zhong Chen, Xin Luo
Exploring and Exploiting Data-Free Model Stealing
Chi Hong, Jiyue Huang, Robert Birke, Lydia Y. Chen
Exploring the Training Robustness of Distributional Reinforcement Learning against Noisy State Observations
Ke Sun, Yingnan Zhao, Shangling Jui, Linglong Kong
Overcoming the Limitations of Localization Uncertainty: Efficient & Exact Non-Linear Post-Processing and Calibration
Moussa Kassem Sbeyti, Michelle Karg, Christian Wirth, Azarm Nowzad, Sahin Albayrak
Label Shift Quantification with Robustness Guarantees via Distribution Feature Matching
Bastien Dussap, Gilles Blanchard, Badr-Eddine Chérief-Abdellatif
Robust Classification of High-Dimensional Data using Data-Adaptive Energy Distance
Jyotishka Ray Choudhury, Aytijhya Saha, Sarbojit Roy, Subhajit Dutta
DualMatch: Robust Semi-Supervised Learning with Dual-Level Interaction
Cong Wang, Xiaofeng Cao, Lanzhe Guo, Zenglin Shi
Detecting Evasion Attacks in Deployed Tree Ensembles
Laurens Devos, Lorenzo Perini, Wannes Meert, Jesse Davis
Deep Imbalanced Time-series Forecasting via Local Discrepancy Density
Junwoo Park, Jungsoo Lee, Youngin Cho, Woncheol Shin, Dongmin Kim, Jaegul Choo, Edward Choi
Online Deep Hybrid Ensemble Learning for Time Series Forecasting
Amal Saadallah, Matthias Jakobs
Adacket: ADAptive Convolutional KErnel Transform for Multivariate Time Series Classification
Junru Zhang, Lang Feng, Haowen Zhang, Yuhan Wu, Yabo Dong
Efficient Adaptive Spatial-Temporal Attention Network for Traffic Flow Forecasting
Hongyang Su, Xiaolong Wang, Qingcai Chen, Yang Qin
Estimating Dynamic Time Warping Distance Between Time Series with Missing Data
Aras Yurtman, Jonas Soenen, Wannes Meert, Hendrik Blockeel
Uncovering Multivariate Structural Dependency for Analyzing Irregularly Sampled Time Series
Zhen Wang, Ting Jiang, Zenghui Xu, Jianliang Gao, Ou Wu, Ke Yan, Ji Zhang
Weighted Multivariate Mean Reversion for Online Portfolio Selection
Boqian Wu, Benmeng Lyu, Jiawen Gu
H2-Nets: Hyper-Hodge Convolutional Neural Networks for Time-series Forecasting
Yuzhou Chen, Tian Jiang, Yulia R. Gel
Overcoming Catastrophic Forgetting for Fine-tuning Pre-trained GANs
Zeren Zhang, Xingjian Li, Tao Hong, Tianyang Wang, Jinwen Ma, Haoyi Xiong, Cheng-Zhong Xu
Unsupervised Domain Adaptation via Bidirectional Cross-Attention Transformer
Xiyu Wang, Pengxin Guo, Yu Zhang
Multiple-Source Adaptation using Variational Rényi Bound Optimization
Dana Zalman (Oshri), Shai Fine
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
Bi-Tuning: Efficient Transfer from Pre-Trained Models
Jincheng Zhong, Haoyu Ma, Ximei Wang, Zhi Kou, Mingsheng Long
Generality-training of a Classifier for Improved Calibration in Unseen Contexts
Bhawani Shankar Leelar, Meelis Kull
Informed Priors for Knowledge Integration in Trajectory Prediction
Christian Schlauch, Christian Wirth, Nadja Klein
CAENet: Efficient Multi-task Learning for Joint Semantic Segmentation and Depth Estimation
Luxi Wang, Yingming Li
Click-aware Structure Transfer with Sample Weight Assignment for Post-Click Conversion Rate Estimation
Kai Ouyang, Wenhao Zheng, Chen Tang, Xuanji Xiao, Hai-Tao Zheng
Constrained-HIDA: Heterogeneous Image Domain Adaptation Guided by Constraints
Mihailo Obrenović, Thomas Lampert, Miloš Ivanović, Pierre Gançarski
Rectifying Bias in Ordinal Observational Data using Unimodal Label Smoothing
Stefan Haas, Eyke Hüllermeier
A Baseline Generative Probabilistic Model for Weakly Supervised Learning
Georgios Papadopoulos, Fran Silavong, Sean Moran
DyCOD - Determining Cash on Delivery Limits for Real-time E-commerce Transactions via Constrained Optimisation Modelling
Akash Deep, Sri Charan Kattamuru, Meghana Negi, Jose Mathew, Jairaj Sathyanarayana
Pattern Mining for Anomaly Detection in Graphs: Application to Fraud in Public Procurement
Lucas Potin, Rosa Figueiredo, Vincent Labatut, Christine Largeron
Aspect-based Complaint and Cause Detection: A Multimodal Generative Framework with External Knowledge Infusion
Raghav Jain, Apoorv Verma, Apoorva Singh, Vivek Gangwar, Sriparna Saha
Sequence-Graph Fusion Neural Network for User Mobile App Behavior Prediction
Yizhuo Wang, Renhe Jiang, Hangchen Liu, Du Yin, Xuan Song
DegUIL: Degree-aware Graph Neural Networks for Long-tailed User Identity Linkage
Meixiu Long, Siyuan Chen, Xin Du, Jiahai Wang
Ex-ThaiHate: A Generative Multi-task Framework for Sentiment and Emotion Aware Hate Speech Detection with Explanation in Thai
Krishanu Maity, Shaubhik Bhattacharya, Salisa Phosit, Sawarod Kongsamlit, Sriparna Saha, Kitsuchart Pasupa
Deep Serial Number: Computational Watermark for DNN Intellectual Property Protection
Ruixiang Tang, Mengnan Du, Xia Hu
How Early can we Detect? Detecting Misinformation on Social Media Using User Profiling and Network Characteristics
Shreya Ghosh, Prasenjit Mitra
Boosting the performance of Deployable Timestamped Directed GNNs via Time-Relaxed Sampling
Arihant Jain, Gundeep Arora, Anoop Saladi
Semi-Supervised Social Bot Detection with Initial Residual Relation Attention Networks
Ming Zhou, Wenzheng Feng, Yifan Zhu, Dan Zhang, Yuxiao Dong, Jie Tang
On Calibration of Mathematical Finance Models by Hypernetworks
Yongxin Yang, Timothy M. Hospedales
PU GNN: Chargeback Fraud Detection in P2E MMORPGs via Graph Attention Networks with Imbalanced PU Labels
Jiho Choi, Junghoon Park, Woocheol Kim, Jin-Hyeok Park, Yumin Suh, Minchang Sung
BCAD: An Interpretable Anomaly Transaction Detection System based on Behavior Consistency
Jun Hu, Xu Min, Xiaolu Zhang, Chilin Fu, Weichang Wu, Jun Zhou
Advancing Fraud Detection Systems through Online Learning
Tommaso Paladini, Martino Bernasconi de Luca, Michele Carminati, Mario Polino, Francesco Trovò, Stefano Zanero
Continual Model-based Reinforcement Learning for Data Efficient Wireless Network Optimisation
Cengis Hasan, David Lynch, Alexandros Agapitos, Alberto Castagna, Giorgio Cruciata, Hao Wang, Aleksandar Milenovic
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
Context-Aware Deep Time-Series Decomposition for Anomaly Detection in Businesses
Youngeun Nam, Patara Trirat, Taeyoon Kim, Youngseop Lee, Jae-Gil Lee
F-3DNet: Leveraging Inner Order of Point Clouds for 3D Object Detection
Ying Chen, Rui Liu, Zhihui Li, Andy Song
Constraint-Based Parameterization and Disentanglement of Aerodynamic Shapes using Deep Generative Models
Asmita Bhat, Nooshin Haji-Ghassemi, Deepak Nagaraj, Sophie Fellenz
Deep Learning for real-time neural decoding of grasp
Paolo Viviani, Ilaria Gesmundo, Elios Ghinato, Andres Agudelo-Toro, Chiara Vercellino, Giacomo Vitali, Letizia Bergamasco, Alberto Scionti, Marco Ghislieri, Valentina Agostini, Olivier Terzo, Hansjörg Scherberger
MCTN: A Multi-Channel Temporal Network for Wearable Fall Prediction
Jiawei Liu, Xiaohu Li, Guorui Liao, Shu Wang, Li Liu
Contrastive Learning-based Imputation-Prediction Networks for In-hospital Mortality Risk Modeling using EHRs
Yuxi Liu, Zhenhao Zhang, Shaowen Qin, Flora D. Salim, Antonio Jimeno Yepes
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
Fairness-Aware Processing Techniques in Survival Analysis: Promoting Equitable Predictions
Zhouting Zhao, Tin Lok James Ng
Ordinal Regression for Difficulty Prediction of StepMania Levels
Billy Joe Franks, Benjamin Dinkelmann, Marius Kloft, Sophie Fellenz
Double Machine Learning at Scale to Predict Causal Impact of Customer Actions
Sushant More, Priya Kotwal, Sujith Chappidi, Dinesh Mandalapu, Chris Khawand
Knowledge Distillation with Graph Neural Networks for Epileptic Seizure Detection
Qinyue Zheng, Arun Venkitaraman, Simona Petravic, Pascal Frossard
OptMSM: Optimizing Multi-Scenario Modeling for Click-Through Rate Prediction
Xing Tang, Yang Qiao, Yuwen Fu, Fuyuan Lyu, Dugang Liu, Xiuqiang He
PDF-VQA: A New Dataset for Real-World VQA on PDF Documents
Yihao Ding, Siwen Luo, Hyunsuk Chung, Soyeon Caren Han
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
Cooperative Multi-Agent Reinforcement Learning for Inventory Management
Madhav Khirwar, Karthik S. Gurumoorthy, Ankit Ajit Jain, Shantala Manchenahally
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
Prototype-Guided Counterfactual Explanations via Variational Auto-Encoder for Recommendation
Ming He, Jiwen Wang, Boyang An, Hao Wen
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
A Vlogger-augmented Graph Neural Network Model for Micro-video Recommendation
Weijiang Lai, Beihong Jin, Beibei Li, Yiyuan Zheng, Rui Zhao
Continually learning out-of-distribution spatiotemporal data for robust energy forecasting
Arian Prabowo, Kaixuan Chen, Hao Xue, Subbu Sethuvenkatraman, Flora D. Salim
Counterfactual Explanations for Remote Sensing Time Series Data: an Application to Land Cover Classification
Cassio F. Dantas, Thalita F. Drumond, Diego Marcos, Dino Ienco
Cloud Imputation for Multi-Sensor Remote Sensing Imagery with Style Transfer
Yifan Zhao, Xian Yang, Ranga Raju Vatsavai
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
Explaining Full-disk Deep Learning Model for Solar Flare Prediction using Attribution Methods
Chetraj Pandey, Rafal Angryk, Berkay Aydin
Deep Spatiotemporal Clustering: A Temporal Clustering Approach for Multi-dimensional Climate Data
Omar Faruque, Francis Ndikum Nji, Mostafa Cham, Rohan Mandar Salvi, Xue Zheng, Jianwu Wang
Circle Attention: Forecasting Network Traffic by Learning Interpretable Spatial Relationships from Intersecting Circles
Espen Haugsdal, Sara Malacarne, Massimiliano Ruocco
Pre-training Contextual Location Embeddings in Personal Trajectories via Efficient Hierarchical Location Representations
Chung Park, Taesan Kim, Junui Hong, Minsung Choi, Jaegul Choo
Leveraging Queue Length and Attention Mechanisms for Enhanced Traffic Signal Control Optimization
Liang Zhang, Shubin Xie, Jianming Deng
PICT: Precision-enhanced Road Intersection Recognition using Cycling Trajectories
Wenyu Wu, Wenyi Shen, Jiali Mao, Lisheng Zhao, Shaosheng Cao, Aoying Zhou, Lin Zhou
FDTI: Fine-grained Deep Traffic Inference with Roadnet-enriched Graph
Zhanyu Liu, Chumeng Liang, Guanjie Zheng, Hua Wei
RulEth: Genetic Programming-Driven Derivation of Security Rules for Automotive Ethernet
Felix Gail, Roland Rieke, Florian Fenzl
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
Data-Driven Explainable Artificial Intelligence for Energy Efficiency in Short-Sea Shipping
Mohamed Abuella, M. Amine Atoui, Slawomir Nowaczyk, Simon Johansson, Ethan Faghani
Multivariate Time-Series Anomaly Detection with Temporal Self-Supervision and Graphs: Application to Vehicle Failure Prediction
Hadi Hojjati, Mohammadreza Sadeghi, Narges Armanfard
Predictive Maintenance, Adversarial Autoencoders and Explainability
Miguel E. P. Silva, Bruno Veloso, João Gama
TDCM: Transport Destination Calibrating based on Multi-task Learning
Tao Wu, Kaixuan Zhu, Jiali Mao, Miaomiao Yang, Aoying Zhou
An Interactive Interface for Novel Class Discovery in Tabular Data
Colin Troisemaine, Joachim Flocon-Cholet, Stéphane Gosselin, Alexandre Reiffers-Masson, Sandrine Vaton, Vincent Lemaire
marl-jax: Multi-agent Reinforcement Leaning framework for Social Generalization
Kinal Mehta, Anuj Mahajan, Pawan Kumar
Temporal Graph based Incident Analysis System for Internet of Things
Peng Yuan, Lu-An Tang, Haifeng Chen, David S. Chang, Moto Sato
MEMENTO: Facilitating Effortless, Efficient, and Reliable ML Experiments
Zac Pullar-Strecker, Xinglong Chang, Liam Brydon, Ioannis Ziogas, Katharina Dost, Jörg Wicker
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
PIQARD system for experimenting and testing Language Models with prompting strategies
Marcin Korcz, Dawid Plaskowski, Mateusz Politycki, Jerzy Stefanowski, Alex Terentowicz
Using Multiple RDF Knowledge Graphs for Enriching ChatGPT Responses
Michalis Mountantonakis, Yannis Tzitzikas
Interactive visualization of counterfactual explanations for tabular data
Victor Guyomard, Françoise Fessant, Thomas Guyet, Tassadit Bouadi, Alexandre Termier
χiplot: web-first visualisation platform for multidimensional data
Akihiro Tanaka, Juniper Tyree, Anton Björklund, Jarmo Mäkelä, Kai Puolamäki
Lumos in the Night Sky: AI-enabled Visual Tool for Exploring Night-Time Light Patterns
Jakob Hederich, Shreya Ghosh, Zeyu He, Prasenjit Mitra
Automated Financial Analysis Using GPT-4
Sander Noels, Adriaan Merlevede, Andrew Fecheyr, Maarten Vanhalst, Nick Meerlaen, Sébastien Viaene, Tijl De Bie
The Good, The Bad And The Average: Benchmarking of Reconstruction Based Multivariate Time Series Anomaly Detection
Arn Baudzus, Bin Li, Adnane Jadid, Emmanuel Müller
Inclusively: an AI-based Assistant for Inclusive Writing
Moreno La Quatra, Salvatore Greco, Luca Cagliero, Tania Cerquitelli
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
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