MLJ 2024
288 papers
A Survey on Interpretable Reinforcement Learning
Claire Glanois, Paul Weng, Matthieu Zimmer, Dong Li, Tianpei Yang, Jianye Hao, Wulong Liu Active Learning Algorithm Through the Lens of Rejection Arguments
Christophe Denis, Mohamed Hebiri, Boris Ndjia Njike, Xavier Siebert Active Model Selection: A Variance Minimization Approach
Satoshi Hara, Mitsuru Matsuura, Junya Honda, Shinji Ito Automotive Fault Nowcasting with Machine Learning and Natural Language Processing
John Pavlopoulos, Alv Romell, Jacob Curman, Olof Steinert, Tony Lindgren, Markus Borg, Korbinian Randl Black-Box Bayesian Adversarial Attack with Transferable Priors
Shudong Zhang, Haichang Gao, Chao Shu, Xiwen Cao, Yunyi Zhou, Jianping He Can Cross-Domain Term Extraction Benefit from Cross-Lingual Transfer and Nested Term Labeling?
Tran Thi Hong Hanh, Matej Martinc, Andraz Repar, Nikola Ljubesic, Antoine Doucet, Senja Pollak CoMadOut - A Robust Outlier Detection Algorithm Based on CoMAD
Andreas Lohrer, Daniyal Kazempour, Maximilian Hünemörder, Peer Kröger Communication-Efficient Clustered Federated Learning via Model Distance
Mao Zhang, Tie Zhang, Yifei Cheng, Changcun Bao, Haoyu Cao, Deqiang Jiang, Linli Xu Coresets for Kernel Clustering
Shaofeng H.-C. Jiang, Robert Krauthgamer, Jianing Lou, Yubo Zhang Deep Doubly Robust Outcome Weighted Learning
Xiaotong Jiang, Xin Zhou, Michael R. Kosorok Deep Negative Correlation Classification
Le Zhang, Qibin Hou, Yun Liu, Jia-Wang Bian, Xun Xu, Joey Tianyi Zhou, Ce Zhu Deep Reinforcement Learning for Multi-Class Imbalanced Training: Applications in Healthcare
Jenny Yang, Rasheed El-Bouri, Odhran O'Donoghue, Alexander S. Lachapelle, Andrew A. S. Soltan, David W. Eyre, Lei Lu, David A. Clifton Did We Personalize? Assessing Personalization by an Online Reinforcement Learning Algorithm Using Resampling
Susobhan Ghosh, Raphael Kim, Prasidh Chhabria, Raaz Dwivedi, Predrag Klasnja, Peng Liao, Kelly W. Zhang, Susan A. Murphy Differentially Private Riemannian Optimization
Andi Han, Bamdev Mishra, Pratik Jawanpuria, Junbin Gao DPQ: Dynamic Pseudo-Mean Mixed-Precision Quantization for Pruned Neural Network
Songwen Pei, Jiyao Wang, Bingxue Zhang, Wei Qin, Hai Xue, Xiaochun Ye, Mingsong Chen Dynamic Datasets and Market Environments for Financial Reinforcement Learning
Xiao-Yang Liu, Ziyi Xia, Hongyang Yang, Jiechao Gao, Daochen Zha, Ming Zhu, Christina Dan Wang, Zhaoran Wang, Jian Guo Dynamic Weighted Ensemble for Diarrhoea Incidence Predictions
Thanh Duy Do, Thuan Dinh Nguyen, Viet Cuong Ta, Duong Tran Anh, Tuyet-Hanh Tran Thi, Diep Phan, Son T. Mai DynamiSE: Dynamic Signed Network Embedding for Link Prediction
Haiting Sun, Peng Tian, Yun Xiong, Yao Zhang, Yali Xiang, Xing Jia, Haofen Wang Evaluating Feature Attribution Methods in the Image Domain
Arne Gevaert, Axel-Jan Rousseau, Thijs Becker, Dirk Valkenborg, Tijl De Bie, Yvan Saeys Evidential Uncertainty Sampling Strategies for Active Learning
Arthur Hoarau, Vincent Lemaire, Yolande Le Gall, Jean-Christophe Dubois, Arnaud Martin Explainable Dating of Greek Papyri Images
John Pavlopoulos, Maria Konstantinidou, Elpida Perdiki, Isabelle Marthot-Santaniello, Holger Essler, Georgios Vardakas, Aristidis Likas Explainable Models via Compression of Tree Ensembles
Siwen Yan, Sriraam Natarajan, Saket Joshi, Roni Khardon, Prasad Tadepalli Explaining Neural Networks Without Access to Training Data
Sascha Marton, Stefan Lüdtke, Christian Bartelt, Andrej Tschalzev, Heiner Stuckenschmidt Explaining Siamese Networks in Few-Shot Learning
Andrea Fedele, Riccardo Guidotti, Dino Pedreschi Exploiting Counter-Examples for Active Learning with Partial Labels
Fei Zhang, Yunjie Ye, Lei Feng, Zhongwen Rao, Jieming Zhu, Marcus Kalander, Chen Gong, Jianye Hao, Bo Han Exploiting Sparsity and Statistical Dependence in Multivariate Data Fusion: An Application to Misinformation Detection for High-Impact Events
Lucas P. Damasceno, Egzona Rexhepi, Allison Shafer, Ian Whitehouse, Nathalie Japkowicz, Charles C. Cavalcante, Roberto Corizzo, Zois Boukouvalas Exposing and Explaining Fake News On-the-Fly
Francisco de Arriba-Pérez, Silvia García-Méndez, Fátima Leal, Benedita Malheiro, Juan-Carlos Burguillo Fair Tree Classifier Using Strong Demographic Parity
António Pereira Barata, Frank W. Takes, H. Jaap van den Herik, Cor J. Veenman Fairness Seen as Global Sensitivity Analysis
Clément Benesse, Fabrice Gamboa, Jean-Michel Loubes, Thibaut Boissin Fast Deep Mixtures of Gaussian Process Experts
Clement Etienam, Kody J. H. Law, Sara Wade, Vitaly Zankin Fast Linear Model Trees by PILOT
Jakob Raymaekers, Peter J. Rousseeuw, Tim Verdonck, Ruicong Yao Fast Parameterless Prototype-Based Co-Clustering
Elena Battaglia, Federico Peiretti, Ruggero G. Pensa Feature Extractor Stacking for Cross-Domain Few-Shot Learning
Hongyu Wang, Eibe Frank, Bernhard Pfahringer, Michael Mayo, Geoff Holmes Forecasting of Mobile Network Traffic and Spatio-Temporal Analysis Using modLSTM
Vidyadhar Jinnappa Aski, Rugved Sanjay Chavan, Vijaypal Singh Dhaka, Geeta Rani, Ester Zumpano, Eugenio Vocaturo Fraud Detection with Natural Language Processing
Petros Boulieris, John Pavlopoulos, Alexandros Xenos, Vasilis Vassalos From MNIST to ImageNet and Back: Benchmarking Continual Curriculum Learning
Kamil Faber, Dominik Zurek, Marcin Pietron, Nathalie Japkowicz, Antonio Vergari, Roberto Corizzo Gradient Boosted Trees for Evolving Data Streams
Nuwan Gunasekara, Bernhard Pfahringer, Heitor Murilo Gomes, Albert Bifet GVFs in the Real World: Making Predictions Online for Water Treatment
Muhammad Kamran Janjua, Haseeb Shah, Martha White, Erfan Miahi, Marlos C. Machado, Adam White Holistic Deep Learning
Dimitris Bertsimas, Kimberly Villalobos Carballo, Léonard Boussioux, Michael Lingzhi Li, Alex Paskov, Ivan S. Paskov Ijuice: Integer JUstIfied Counterfactual Explanations
Alejandro Kuratomi, Ioanna Miliou, Zed Lee, Tony Lindgren, Panagiotis Papapetrou Imbalanced Gradients: A Subtle Cause of Overestimated Adversarial Robustness
Xingjun Ma, Linxi Jiang, Hanxun Huang, Zejia Weng, James Bailey, Yu-Gang Jiang Improving Fraud Detection via Imbalanced Graph Structure Learning
Lingfei Ren, Ruimin Hu, Yang Liu, Dengshi Li, Junhang Wu, Yilong Zang, Wenyi Hu Integration of Multi-Modal Datasets to Estimate Human Aging
Rogério Ribeiro, Athos Moraes, Marta Moreno, Pedro G. Ferreira Kalt: Generating Adversarial Explainable Chinese Legal Texts
Yunting Zhang, Shang Li, Lin Ye, Hongli Zhang, Zhe Chen, Binxing Fang Learning Differentiable Logic Programs for Abstract Visual Reasoning
Hikaru Shindo, Viktor Pfanschilling, Devendra Singh Dhami, Kristian Kersting Learning Sample-Aware Threshold for Semi-Supervised Learning
Qi Wei, Lei Feng, Haoliang Sun, Ren Wang, Rundong He, Yilong Yin Learning to Bid and Rank Together in Recommendation Systems
Geng Ji, Wentao Jiang, Jiang Li, Fahmid Morshed Fahid, Zhengxing Chen, Yinghua Li, Jun Xiao, Chongxi Bao, Zheqing Zhu Libsignal: An Open Library for Traffic Signal Control
Hao Mei, Xiaoliang Lei, Longchao Da, Bin Shi, Hua Wei Machine Learning with a Reject Option: A Survey
Kilian Hendrickx, Lorenzo Perini, Dries Van der Plas, Wannes Meert, Jesse Davis Manas: Multi-Agent Neural Architecture Search
Vasco Lopes, Fabio Maria Carlucci, Pedro M. Esperança, Marco Singh, Antoine Yang, Victor Gabillon, Hang Xu, Zewei Chen, Jun Wang Methodology and Evaluation in Sports Analytics: Challenges, Approaches, and Lessons Learned
Jesse Davis, Lotte Bransen, Laurens Devos, Arne Jaspers, Wannes Meert, Pieter Robberechts, Jan Van Haaren, Maaike Van Roy Multi-Agent Reinforcement Learning for Fast-Timescale Demand Response of Residential Loads
Vincent Mai, Philippe Maisonneuve, Tianyu Zhang, Hadi Nekoei, Liam Paull, Antoine Lesage-Landry Multi-Armed Bandits with Dependent Arms
Rahul Singh, Fang Liu, Yin Sun, Ness B. Shroff Natural Language Inference Model for Customer Advocacy Detection in Online Customer Engagement
Bilal Abu-Salih, Mohammed Alweshah, Moutaz Alazab, Manaf Al-Okaily, Muteeb Alahmari, Mohammad Alhabashneh, Saleh H. Al-Sharaeh Neural Network Relief: A Pruning Algorithm Based on Neural Activity
Aleksandr Dekhovich, David M. J. Tax, Marcel H. F. Sluiter, Miguel A. Bessa No Regret Sample Selection with Noisy Labels
Heon Song, Nariaki Mitsuo, Seiichi Uchida, Daiki Suehiro Nrat: Towards Adversarial Training with Inherent Label Noise
Zhen Chen, Fu Wang, Ronghui Mu, Peipei Xu, Xiaowei Huang, Wenjie Ruan On the Incompatibility of Accuracy and Equal Opportunity
Carlos Pinzón, Catuscia Palamidessi, Pablo Piantanida, Frank Valencia On-the-Fly Image-Level Oversampling for Imbalanced Datasets of Manufacturing Defects
Spyros Theodoropoulos, Patrik Zajec, Joze M. Rozanec, Dimosthenis Kyriazis, Panayiotis Tsanakas Online Binary Classification from Similar and Dissimilar Data
Senlin Shu, Haobo Wang, Zhuowei Wang, Bo Han, Tao Xiang, Bo An, Lei Feng Open-Set Learning Under Covariate Shift
Jie-Jing Shao, Xiaowen Yang, Lan-Zhe Guo Optimal Clustering from Noisy Binary Feedback
Kaito Ariu, Jungseul Ok, Alexandre Proutière, Seyoung Yun OT-Net: A Reusable Neural Optimal Transport Solver
Zezeng Li, Shenghao Li, Lianbao Jin, Na Lei, Zhongxuan Luo PANACEA: A Neural Model Ensemble for Cyber-Threat Detection
Malik Al-Essa, Giuseppina Andresini, Annalisa Appice, Donato Malerba Partitioned Least Squares
Roberto Esposito, Mattia Cerrato, Marco Locatelli Permutation-Invariant Linear Classifiers
Ludwig Lausser, Robin Szekely, Hans A. Kestler Persian Offensive Language Detection
Emad Kebriaei, Ali Homayouni, Roghayeh Faraji, Armita Razavi, Azadeh Shakery, Heshaam Faili, Yadollah Yaghoobzadeh Personalization for Web-Based Services Using Offline Reinforcement Learning
Pavlos Athanasios Apostolopoulos, Zehui Wang, Hanson Wang, Tenghyu Xu, Chad Zhou, Kittipat Virochsiri, Norm Zhou, Igor L. Markov POMDP Inference and Robust Solution via Deep Reinforcement Learning: An Application to Railway Optimal Maintenance
Giacomo Arcieri, Cyprien Hoelzl, Oliver Schwery, Daniel Straub, Konstantinos G. Papakonstantinou, Eleni N. Chatzi ProtoSimi: Label Correction for Fine-Grained Visual Categorization
Jialiang Shen, Yu Yao, Shaoli Huang, Zhiyong Wang, Jing Zhang, Ruxing Wang, Jun Yu, Tongliang Liu Random Fourier Features for Asymmetric Kernels
Mingzhen He, Fan He, Fanghui Liu, Xiaolin Huang Regional Bias in Monolingual English Language Models
Jiachen Lyu, Katharina Dost, Yun Sing Koh, Jörg Wicker Reinforcement Learning Tutor Better Supported Lower Performers in a Math Task
Sherry Ruan, Allen Nie, William Steenbergen, Jiayu He, J. Q. Zhang, Meng Guo, Yao Liu, Kyle Dang Nguyen, Catherine Y. Wang, Rui Ying, James A. Landay, Emma Brunskill Rule Learning by Modularity
Albert Nössig, Tobias Hell, Georg Moser Sample Complexity of Variance-Reduced Policy Gradient: Weaker Assumptions and Lower Bounds
Gabor Paczolay, Matteo Papini, Alberto Maria Metelli, István Á. Harmati, Marcello Restelli Sanitized Clustering Against Confounding Bias
Yinghua Yao, Yuangang Pan, Jing Li, Ivor W. Tsang, Xin Yao Spatial Entropy as an Inductive Bias for Vision Transformers
Elia Peruzzo, Enver Sangineto, Yahui Liu, Marco De Nadai, Wei Bi, Bruno Lepri, Nicu Sebe Special Issue on Feature Engineering Editorial
Tim Verdonck, Bart Baesens, María Óskarsdóttir, Seppe vanden Broucke Stress Detection with Encoding Physiological Signals and Convolutional Neural Network
Michela Quadrini, Antonino Capuccio, Denise Falcone, Sebastian Daberdaku, Alessandro Blanda, Luca Bellanova, Gianluca Gerard Targeted Adversarial Attacks on Wind Power Forecasts
René Heinrich, Christoph Scholz, Stephan Vogt, Malte Lehna The Class Imbalance Problem in Deep Learning
Kushankur Ghosh, Colin Bellinger, Roberto Corizzo, Paula Branco, Bartosz Krawczyk, Nathalie Japkowicz Towards a Foundation Large Events Model for Soccer
Tiago Mendes-Neves, Luís Meireles, João Mendes-Moreira TSFuse: Automated Feature Construction for Multiple Time Series Data
Arne De Brabandere, Tim Op De Beéck, Kilian Hendrickx, Wannes Meert, Jesse Davis Understanding CNN Fragility When Learning with Imbalanced Data
Damien Dablain, Kristen N. Jacobson, Colin Bellinger, Mark Roberts, Nitesh V. Chawla Understanding Imbalanced Data: XAI & Interpretable ML Framework
Damien Dablain, Colin Bellinger, Bartosz Krawczyk, David W. Aha, Nitesh V. Chawla Upper and Lower Bounds for Complete Linkage in General Metric Spaces
Anna Arutyunova, Anna Großwendt, Heiko Röglin, Melanie Schmidt, Julian Wargalla Utilizing Reinforcement Learning for De Novo Drug Design
Hampus Gummesson Svensson, Christian Tyrchan, Ola Engkvist, Morteza Haghir Chehreghani Wasserstein Dropout
Joachim Sicking, Maram Akila, Maximilian Pintz, Tim Wirtz, Stefan Wrobel, Asja Fischer When Are They Coming? Understanding and Forecasting the Timeline of Arrivals at the FC Barcelona Stadium on Match Days
Feliu Serra-Burriel, Pedro Delicado, Fernando M. Cucchietti, Eduardo Graells-Garrido, Alex Gil, Imanol Eguskiza Martínez X-Detect: Explainable Adversarial Patch Detection for Object Detectors in Retail
Omer Hofman, Amit Giloni, Yarin Hayun, Ikuya Morikawa, Toshiya Shimizu, Yuval Elovici, Asaf Shabtai