MLJ 2022

146 papers

A Brain-Inspired Algorithm for Training Highly Sparse Neural Networks Zahra Atashgahi, Joost Pieterse, Shiwei Liu, Decebal Constantin Mocanu, Raymond N. J. Veldhuis, Mykola Pechenizkiy

A Flexible Class of Dependence-Aware Multi-Label Loss Functions Eyke Hüllermeier, Marcel Wever, Eneldo Loza Mencía, Johannes Fürnkranz, Michael Rapp

A Generalized Weisfeiler-Lehman Graph Kernel Till Hendrik Schulz, Tamás Horváth, Pascal Welke, Stefan Wrobel

A Network-Based Positive and Unlabeled Learning Approach for Fake News Detection Mariana Caravanti de Souza, Bruno Magalhães Nogueira, Rafael Geraldeli Rossi, Ricardo Marcondes Marcacini, Brucce Neves dos Santos, Solange Oliveira Rezende

A Review on Instance Ranking Problems in Statistical Learning Tino Werner

A Stochastic Approach to Handle Resource Constraints as Knapsack Problems in Ensemble Pruning András Hajdu, György Terdik, Attila Tiba, Henrietta Tomán

A Study of BERT for Context-Aware Neural Machine Translation Xueqing Wu, Yingce Xia, Jinhua Zhu, Lijun Wu, Shufang Xie, Tao Qin

A Taxonomy for Similarity Metrics Between Markov Decision Processes Javier García, Álvaro Visús, Fernando Fernández

A Taxonomy of Weight Learning Methods for Statistical Relational Learning Sriram Srinivasan, Charles Dickens, Eriq Augustine, Golnoosh Farnadi, Lise Getoor

A Unified Framework for Online Trip Destination Prediction Victor Eberstein, Jonas Sjöblom, Nikolce Murgovski, Morteza Haghir Chehreghani

A User-Guided Bayesian Framework for Ensemble Feature Selection in Life Science Applications (UBayFS) Anna Jenul, Stefan Schrunner, Jürgen Pilz, Oliver Tomic

Achieving Adversarial Robustness via Sparsity Ningyi Liao, Shufan Wang, Liyao Xiang, Nanyang Ye, Shuo Shao, Pengzhi Chu

Adaptive Infinite Dropout for Noisy and Sparse Data Streams Ha Nguyen, Hoang Pham, Son Nguyen, Ngo Van Linh, Khoat Than

Adversarial Examples for Extreme Multilabel Text Classification Mohammadreza Qaraei, Rohit Babbar

Aliasing and Adversarial Robust Generalization of CNNs Julia Grabinski, Janis Keuper, Margret Keuper

An Accurate, Scalable and Verifiable Protocol for Federated Differentially Private Averaging César Sabater, Aurélien Bellet, Jan Ramon

An Adaptive Polyak Heavy-Ball Method Samer Saab Jr., Shashi Phoha, Minghui Zhu, Asok Ray

Analyzing and Repairing Concept Drift Adaptation in Data Stream Classification Ben Halstead, Yun Sing Koh, Patricia Riddle, Russel Pears, Mykola Pechenizkiy, Albert Bifet, Gustavo Olivares, Guy Coulson

Arbitrary Conditional Inference in Variational Autoencoders via Fast Prior Network Training Ga Wu, Justin Domke, Scott Sanner

Attacking Neural Machine Translations via Hybrid Attention Learning Mingze Ni, Ce Wang, Tianqing Zhu, Shui Yu, Wei Liu

Bayesian Mixture Variational Autoencoders for Multi-Modal Learning Keng-Te Liao, Bo-Wei Huang, Chih-Chun Yang, Shou-De Lin

Bayesian Optimization with Partially Specified Queries Shogo Hayashi, Junya Honda, Hisashi Kashima

Boosting Poisson Regression Models with Telematics Car Driving Data Guangyuan Gao, He Wang, Mario V. Wüthrich

BT-UNet: A Self-Supervised Learning Framework for Biomedical Image Segmentation Using Barlow Twins with U-Net Models Narinder Singh Punn, Sonali Agarwal

Clustered and Deep Echo State Networks for Signal Noise Reduction Laercio de Oliveira Junior, Florian Stelzer, Liang Zhao

CMD: Controllable Matrix Decomposition with Global Optimization for Deep Neural Network Compression Haonan Zhang, Longjun Liu, Hengyi Zhou, Hongbin Sun, Nanning Zheng

Context-Aware Spatio-Temporal Event Prediction via Convolutional Hawkes Processes Maya Okawa, Tomoharu Iwata, Yusuke Tanaka, Takeshi Kurashima, Hiroyuki Toda, Hisashi Kashima

DEFT: Distilling Entangled Factors by Preventing Information Diffusion Jiantao Wu, Lin Wang, Bo Yang, Fanqi Li, Chunxiuzi Liu, Jin Zhou

Detect, Understand, Act: A Neuro-Symbolic Hierarchical Reinforcement Learning Framework Ludovico Mitchener, David Tuckey, Matthew Crosby, Alessandra Russo

Dual-Domain Graph Convolutional Networks for Skeleton-Based Action Recognition Shuo Chen, Ke Xu, Zhongjie Mi, Xinghao Jiang, Tanfeng Sun

Efficient Fair Principal Component Analysis Mohammad Mahdi Kamani, Farzin Haddadpour, Rana Forsati, Mehrdad Mahdavi

Efficient SVDD Sampling with Approximation Guarantees for the Decision Boundary Adrian Englhardt, Holger Trittenbach, Daniel Kottke, Bernhard Sick, Klemens Böhm

Embed2Detect: Temporally Clustered Embedded Words for Event Detection in Social Media Hansi Hettiarachchi, Mariam Adedoyin-Olowe, Jagdev Bhogal, Mohamed Medhat Gaber

Embedding and Extraction of Knowledge in Tree Ensemble Classifiers Wei Huang, Xingyu Zhao, Xiaowei Huang

End-to-End Entity-Aware Neural Machine Translation Shufang Xie, Yingce Xia, Lijun Wu, Yiqing Huang, Yang Fan, Tao Qin

Explainable Online Ensemble of Deep Neural Network Pruning for Time Series Forecasting Amal Saadallah, Matthias Jakobs, Katharina Morik

Exploring the Common Principal Subspace of Deep Features in Neural Networks Haoran Liu, Haoyi Xiong, Yaqing Wang, Haozhe An, Dejing Dou, Dongrui Wu

Fast Spectral Analysis for Approximate Nearest Neighbor Search Jing Wang, Jie Shen

Few-Shot Learning for Spatial Regression via Neural Embedding-Based Gaussian Processes Tomoharu Iwata, Yusuke Tanaka

Generalized Vec Trick for Fast Learning of Pairwise Kernel Models Markus Viljanen, Antti Airola, Tapio Pahikkala

Generating Contrastive Explanations for Inductive Logic Programming Based on a near Miss Approach Johannes Rabold, Michael Siebers, Ute Schmid

GENs: Generative Encoding Networks Surojit Saha, Shireen Y. Elhabian, Ross T. Whitaker

Greedy Structure Learning from Data That Contain Systematic Missing Values Yang Liu, Anthony C. Constantinou

Handling Epistemic and Aleatory Uncertainties in Probabilistic Circuits Federico Cerutti, Lance M. Kaplan, Angelika Kimmig, Murat Sensoy

Hierarchical Optimal Transport for Unsupervised Domain Adaptation Mourad El Hamri, Younès Bennani, Issam Falih

High-Dimensional Correlation Matrix Estimation for General Continuous Data with Bagging Technique Chaojie Wang, Jin Du, Xiaodan Fan

How to Measure Uncertainty in Uncertainty Sampling for Active Learning Vu-Linh Nguyen, Mohammad Hossein Shaker, Eyke Hüllermeier

Improve Generated Adversarial Imitation Learning with Reward Variance Regularization Yi-Feng Zhang, Fan-Ming Luo, Yang Yu

Improving Deep Label Noise Learning with Dual Active Label Correction Shaoyuan Li, Ye Shi, Sheng-Jun Huang, Songcan Chen

Improving Kernel Online Learning with a Snapshot Memory Trung Le, Khanh Nguyen, Dinh Q. Phung

Improving Sequential Latent Variable Models with Autoregressive Flows Joseph Marino, Lei Chen, Jiawei He, Stephan Mandt

Inclusion of Domain-Knowledge into GNNs Using Mode-Directed Inverse Entailment Tirtharaj Dash, Ashwin Srinivasan, A. Baskar

Inductive Logic Programming at 30 Andrew Cropper, Sebastijan Dumancic, Richard Evans, Stephen H. Muggleton

InfoGram and Admissible Machine Learning Subhadeep Mukhopadhyay

JGPR: A Computationally Efficient Multi-Target Gaussian Process Regression Algorithm Mohammad Nabati, Seyed Ali Ghorashi, Reza Shahbazian

Large Scale Tensor Regression Using Kernels and Variational Inference Robert Hu, Geoff K. Nicholls, Dino Sejdinovic

Large-Scale Pinball Twin Support Vector Machines Mohammad Tanveer, Aruna Tiwari, Rahul Choudhary, M. A. Ganaie

Lead-Lag Detection and Network Clustering for Multivariate Time Series with an Application to the US Equity Market Stefanos Bennett, Mihai Cucuringu, Gesine Reinert

Learning Any Memory-Less Discrete Semantics for Dynamical Systems Represented by Logic Programs Tony Ribeiro, Maxime Folschette, Morgan Magnin, Katsumi Inoue

Learning Explanations for Biological Feedback with Delays Using an Event Calculus Ashwin Srinivasan, Michael Bain, A. Baskar

Learning from Interpretation Transition Using Differentiable Logic Programming Semantics Kun Gao, Hanpin Wang, Yongzhi Cao, Katsumi Inoue

Learning with Risks Based on M-Location Matthew J. Holland

Lifted Model Checking for Relational MDPs Wen-Chi Yang, Jean-François Raskin, Luc De Raedt

Lifting Symmetry Breaking Constraints with Inductive Logic Programming Alice Tarzariol, Martin Gebser, Konstantin Schekotihin

Lipschitzness Is All You Need to Tame Off-Policy Generative Adversarial Imitation Learning Lionel Blondé, Pablo Strasser, Alexandros Kalousis

Machine Learning in Corporate Credit Rating Assessment Using the Expanded Audit Report Nora Muñoz-Izquierdo, María Jesús Segovia-Vargas, María-del-Mar Camacho-Miñano, Yolanda Pérez-Pérez

Machine Unlearning: Linear Filtration for Logit-Based Classifiers Thomas Baumhauer, Pascal Schöttle, Matthias Zeppelzauer

MAGMA: Inference and Prediction Using Multi-Task Gaussian Processes with Common Mean Arthur Leroy, Pierre Latouche, Benjamin Guedj, Servane Gey

Maintaining AUC and H-Measure over Time Nikolaj Tatti

Matrix-Wise ℓ 0-Constrained Sparse Nonnegative Least Squares Nicolas Nadisic, Jeremy E. Cohen, Arnaud Vandaele, Nicolas Gillis

Meta-Interpretive Learning as Metarule Specialisation Stassa Patsantzis, Stephen H. Muggleton

Model Selection in Reconciling Hierarchical Time Series Mahdi Abolghasemi, Rob J. Hyndman, Evangelos Spiliotis, Christoph Bergmeir

Modelling Spatiotemporal Dynamics from Earth Observation Data with Neural Differential Equations Ibrahim Ayed, Emmanuel de Bézenac, Arthur Pajot, Patrick Gallinari

Multi-Target Prediction for Dummies Using Two-Branch Neural Networks Dimitrios Iliadis, Bernard De Baets, Willem Waegeman

Multiple Partitions Alignment via Spectral Rotation Shudong Huang, Ivor W. Tsang, Zenglin Xu, Jiancheng Lv

Multiway P-Spectral Graph Cuts on Grassmann Manifolds Dimosthenis Pasadakis, Christie Louis Alappat, Olaf Schenk, Gerhard Wellein

Nested Aggregation of Experts Using Inducing Points for Approximated Gaussian Process Regression Ayano Nakai-Kasai, Toshiyuki Tanaka

Non-Technical Losses Detection in Energy Consumption Focusing on Energy Recovery and Explainability Bernat Coma-Puig, Josep Carmona

Nyström Landmark Sampling and Regularized Christoffel Functions Michaël Fanuel, Joachim Schreurs, Johan A. K. Suykens

On the Benefits of Representation Regularization in Invariance Based Domain Generalization Changjian Shui, Boyu Wang, Christian Gagné

On the Robustness of Randomized Classifiers to Adversarial Examples Rafael Pinot, Laurent Meunier, Florian Yger, Cédric Gouy-Pailler, Yann Chevaleyre, Jamal Atif

One-Stage Tree: End-to-End Tree Builder and Pruner Zhuoer Xu, Guanghui Zhu, Chunfeng Yuan, Yihua Huang

Online Active Classification via Margin-Based and Feature-Based Label Queries Tingting Zhai, Frédéric Koriche, Yang Gao, Junwu Zhu, Bin Li

Online Strongly Convex Optimization with Unknown Delays Yuanyu Wan, Wei-Wei Tu, Lijun Zhang

Optimal Policy Trees Maxime Amram, Jack Dunn, Ying Daisy Zhuo

Optimal Survival Trees Dimitris Bertsimas, Jack Dunn, Emma Gibson, Agni Orfanoudaki

Optimal Transport for Conditional Domain Matching and Label Shift Alain Rakotomamonjy, Rémi Flamary, Gilles Gasso, M. El Alaya, Maxime Berar, Nicolas Courty

Optimised One-Class Classification Performance Oliver Urs Lenz, Daniel Peralta, Chris Cornelis

Optimistic Optimisation of Composite Objective with Exponentiated Update Weijia Shao, Fikret Sivrikaya, Sahin Albayrak

Order Preserving Hierarchical Agglomerative Clustering Daniel Bakkelund

Partitioned Hybrid Learning of Bayesian Network Structures Jireh Huang, Qing Zhou

Planning for Potential: Efficient Safe Reinforcement Learning Floris den Hengst, Vincent François-Lavet, Mark Hoogendoorn, Frank van Harmelen

Policy Space Identification in Configurable Environments Alberto Maria Metelli, Guglielmo Manneschi, Marcello Restelli

Polynomial-Based Graph Convolutional Neural Networks for Graph Classification Luca Pasa, Nicolò Navarin, Alessandro Sperduti

Predicting Survival Outcomes in the Presence of Unlabeled Data Fateme Nateghi Haredasht, Celine Vens

Pruning Convolutional Neural Networks via Filter Similarity Analysis Lili Geng, Baoning Niu

Quick and Robust Feature Selection: The Strength of Energy-Efficient Sparse Training for Autoencoders Zahra Atashgahi, Ghada Sokar, Tim van der Lee, Elena Mocanu, Decebal Constantin Mocanu, Raymond N. J. Veldhuis, Mykola Pechenizkiy

Randomized Approximate Class-Specific Kernel Spectral Regression Analysis for Large-Scale Face Verification Ke Li, Gang Wu

Re-Thinking Model Robustness from Stability: A New Insight to Defend Adversarial Examples Shufei Zhang, Kaizhu Huang, Zenglin Xu

Receiver Operating Characteristic (ROC) Curves: Equivalences, Beta Model, and Minimum Distance Estimation Tilmann Gneiting, Peter Vogel

Receiver Operating Characteristic (ROC) Movies, Universal ROC (UROC) Curves, and Coefficient of Predictive Ability (CPA) Tilmann Gneiting, Eva-Maria Walz

Recursive Tree Grammar Autoencoders Benjamin Paaßen, Irena Koprinska, Kalina Yacef

Reinforcement Learning for Robotic Manipulation Using Simulated Locomotion Demonstrations Ozsel Kilinc, Giovanni Montana

Relating Instance Hardness to Classification Performance in a Dataset: A Visual Approach Pedro Yuri Arbs Paiva, Camila Castro Moreno, Kate Smith-Miles, Maria Gabriela Valeriano, Ana Carolina Lorena

ReliefE: Feature Ranking in High-Dimensional Spaces via Manifold Embeddings Blaz Skrlj, Saso Dzeroski, Nada Lavrac, Matej Petkovic

Representation Learning for Clustering via Building Consensus Aniket Anand Deshmukh, Jayanth Reddy Regatti, Eren Manavoglu, Ürün Dogan

ResGCN: Attention-Based Deep Residual Modeling for Anomaly Detection on Attributed Networks Yulong Pei, Tianjin Huang, Werner van Ipenburg, Mykola Pechenizkiy

Robust Linear Classification from Limited Training Data Deepayan Chakrabarti

Robust Reputation Independence in Ranking Systems for Multiple Sensitive Attributes Guilherme Ramos, Ludovico Boratto, Mirko Marras

Robustness Verification of ReLU Networks via Quadratic Programming Aleksei Kuvshinov, Stephan Günnemann

ROSE: Robust Online Self-Adjusting Ensemble for Continual Learning on Imbalanced Drifting Data Streams Alberto Cano, Bartosz Krawczyk

SAMBA: Safe Model-Based & Active Reinforcement Learning Alexander I. Cowen-Rivers, Daniel Palenicek, Vincent Moens, Mohammed Amin Abdullah, Aivar Sootla, Jun Wang, Haitham Bou-Ammar

Scaling up Stochastic Gradient Descent for Non-Convex Optimisation Saad Mohamad, Hamad Alamri, Abdelhamid Bouchachia

Scrutinizing XAI Using Linear Ground-Truth Data with Suppressor Variables Rick Wilming, Céline Budding, Klaus-Robert Müller, Stefan Haufe

SDANet: Spatial Deep Attention-Based for Point Cloud Classification and Segmentation Jiangjiang Gao, Jinhui Lan, Bingxu Wang, Feifan Li

Semi-Lipschitz Functions and Machine Learning for Discrete Dynamical Systems on Graphs Hervé Falciani, Enrique Alfonso Sánchez-Pérez

Semi-Parametric Bayes Regression with Network-Valued Covariates Xin Ma, Suprateek Kundu, Jennifer S. Stevens

Semi-Supervised Latent Block Model with Pairwise Constraints Paul Riverain, Simon Fossier, Mohamed Nadif

Semi-Supervised Semantic Segmentation in Earth Observation: The MiniFrance Suite, Dataset Analysis and Multi-Task Network Study Javiera Castillo-Navarro, Bertrand Le Saux, Alexandre Boulch, Nicolas Audebert, Sébastien Lefèvre

Smoothing Graphons for Modelling Exchangeable Relational Data Yaqiong Li, Xuhui Fan, Ling Chen, Bin Li, Scott A. Sisson

Smoothing Policies and Safe Policy Gradients Matteo Papini, Matteo Pirotta, Marcello Restelli

Spatial Dependence Between Training and Test Sets: Another Pitfall of Classification Accuracy Assessment in Remote Sensing Nicolas Karasiak, Jean-Francois Dejoux, Claude Monteil, David Sheeren

Speeding up Neural Network Robustness Verification via Algorithm Configuration and an Optimised Mixed Integer Linear Programming Solver Portfolio Matthias König, Holger H. Hoos, Jan N. van Rijn

Speeding-up One-Versus-All Training for Extreme Classification via Mean-Separating Initialization Erik Schultheis, Rohit Babbar

Stabilize Deep ResNet with a Sharp Scaling Factor Τ Huishuai Zhang, Da Yu, Mingyang Yi, Wei Chen, Tie-Yan Liu

Stateless Neural Meta-Learning Using Second-Order Gradients Mike Huisman, Aske Plaat, Jan N. van Rijn

Stream-Based Active Learning for Sliding Windows Under the Influence of Verification Latency Tuan Pham, Daniel Kottke, Georg Krempl, Bernhard Sick

Stronger Data Poisoning Attacks Break Data Sanitization Defenses Pang Wei Koh, Jacob Steinhardt, Percy Liang

SVRG Meets AdaGrad: Painless Variance Reduction Benjamin Dubois-Taine, Sharan Vaswani, Reza Babanezhad, Mark Schmidt, Simon Lacoste-Julien

Switching: Understanding the Class-Reversed Sampling in Tail Sample Memorization Chi Zhang, Benyi Hu, Yuhang Liuzhang, Le Wang, Li Liu, Yuehu Liu

Symbolic DNN-Tuner Michele Fraccaroli, Evelina Lamma, Fabrizio Riguzzi

The Backbone Method for Ultra-High Dimensional Sparse Machine Learning Dimitris Bertsimas, Vassilis Digalakis

The Flowing Nature Matters: Feature Learning from the Control Flow Graph of Source Code for Bug Localization Yi-Fan Ma, Ming Li

The Pure Exploration Problem with General Reward Functions Depending on Full Distributions Siwei Wang, Wei Chen

Time-Aware Tensor Decomposition for Sparse Tensors Dawon Ahn, Jun-Gi Jang, U Kang

Towards Harnessing Feature Embedding for Robust Learning with Noisy Labels Chuang Zhang, Li Shen, Jian Yang, Chen Gong

Towards Interpreting Deep Neural Networks via Layer Behavior Understanding Jiezhang Cao, Jincheng Li, Xiping Hu, Xiangmiao Wu, Mingkui Tan

Traditional and Context-Specific Spam Detection in Low Resource Settings Kornraphop Kawintiranon, Lisa Singh, Ceren Budak

Understanding Generalization Error of SGD in Nonconvex Optimization Yi Zhou, Yingbin Liang, Huishuai Zhang

Unsupervised Anomaly Detection in Multivariate Time Series with Online Evolving Spiking Neural Networks Dennis Bäßler, Tobias Kortus, Gabriele Gühring

Variance Reduction in Feature Hashing Using MLE and Control Variate Method Bhisham Dev Verma, Rameshwar Pratap, Manoj Thakur

Variance Reduction on General Adaptive Stochastic Mirror Descent Wenjie Li, Zhanyu Wang, Yichen Zhang, Guang Cheng

Wasserstein-Based Fairness Interpretability Framework for Machine Learning Models Alexey Miroshnikov, Konstandinos Kotsiopoulos, Ryan Franks, Arjun Ravi Kannan

Wavelet-Packets for Deepfake Image Analysis and Detection Moritz Wolter, Felix Blanke, Raoul Heese, Jochen Garcke

World-Class Interpretable Poker Dimitris Bertsimas, Alex Paskov

Worst-Case Regret Analysis of Computationally Budgeted Online Kernel Selection Junfan Li, Shizhong Liao