ECML-PKDD 2021

210 papers

A Bayesian Convolutional Neural Network for Robust Galaxy Ellipticity Regression Claire Theobald, Bastien Arcelin, Frédéric Pennerath, Brieuc Conan-Guez, Miguel Couceiro, Amedeo Napoli

A Mixed Noise and Constraint-Based Approach to Causal Inference in Time Series Charles K. Assaad, Emilie Devijver, Éric Gaussier, Ali Aït-Bachir

A Unified Batch Selection Policy for Active Metric Learning Priyadarshini Kumari, Siddhartha Chaudhuri, Vivek S. Borkar, Subhasis Chaudhuri

A Variance Controlled Stochastic Method with Biased Estimation for Faster Non-Convex Optimization Jia Bi, Steve R. Gunn

Action Set Based Policy Optimization for Safe Power Grid Management Bo Zhou, Hongsheng Zeng, Yuecheng Liu, Kejiao Li, Fan Wang, Hao Tian

Active Learning in Gaussian Process State Space Model Hon Sum Alec Yu, Dingling Yao, Christoph Zimmer, Marc Toussaint, Duy Nguyen-Tuong

Adaptive Learning Rate and Momentum for Training Deep Neural Networks Zhiyong Hao, Yixuan Jiang, Huihua Yu, Hsiao-Dong Chiang

Adaptive Node Embedding Propagation for Semi-Supervised Classification Yuya Ogawa, Seiji Maekawa, Yuya Sasaki, Yasuhiro Fujiwara, Makoto Onizuka

Adaptive Optimizers with Sparse Group Lasso for Neural Networks in CTR Prediction Yun Yue, Yongchao Liu, Suo Tong, Minghao Li, Zhen Zhang, Chunyang Wen, Huanjun Bao, Lihong Gu, Jinjie Gu, Yixiang Mu

Adversarial Representation Learning with Closed-Form Solvers Bashir Sadeghi, Lan Wang, Vishnu Naresh Boddeti

AIMED-RL: Exploring Adversarial Malware Examples with Reinforcement Learning Raphael Labaca Castro, Sebastian Franz, Gabi Dreo Rodosek

An Optimized NL2SQL System for Enterprise Data Mart Kaiwen Dong, Kai Lu, Xin Xia, David A. Cieslak, Nitesh V. Chawla

Analyzing Research Trends in Inorganic Materials Literature Using NLP Fusataka Kuniyoshi, Jun Ozawa, Makoto Miwa

Anomaly Detection: How to Artificially Increase Your F1-Score with a Biased Evaluation Protocol Damien Fourure, Muhammad Usama Javaid, Nicolas Posocco, Simon Tihon

Approximation Algorithms for Confidence Bands for Time Series Nikolaj Tatti

Asymptotic Statistical Analysis of Sparse Group LASSO via Approximate Message Passing Kan Chen, Zhiqi Bu, Shiyun Xu

ATOM: Robustifying Out-of-Distribution Detection Using Outlier Mining Jiefeng Chen, Yixuan Li, Xi Wu, Yingyu Liang, Somesh Jha

Attack Transferability Characterization for Adversarially Robust Multi-Label Classification Zhuo Yang, Yufei Han, Xiangliang Zhang

Augmenting Open-Domain Event Detection with Synthetic Data from GPT-2 Amir Pouran Ben Veyseh, Minh Van Nguyen, Bonan Min, Thien Huu Nguyen

Automated Machine Learning for Satellite Data: Integrating Remote Sensing Pre-Trained Models into AutoML Systems Nelly Rosaura Palacios Salinas, Mitra Baratchi, Jan N. van Rijn, Andreas Vollrath

Automatic Acoustic Mosquito Tagging with Bayesian Neural Networks Ivan Kiskin, Adam D. Cobb, Marianne Sinka, Kathy Willis, Stephen J. Roberts

AutoML Meets Time Series Regression Design and Analysis of the AutoSeries Challenge Zhen Xu, Wei-Wei Tu, Isabelle Guyon

Balancing Speed and Accuracy in Neural-Enhanced Phonetic Name Matching Philip Blair, Carmel Eliav, Fiona Hasanaj, Kfir Bar

Bayesian Crowdsourcing with Constraints Panagiotis A. Traganitis, Georgios B. Giannakis

Bayesian Optimization with a Prior for the Optimum Artur L. F. Souza, Luigi Nardi, Leonardo B. Oliveira, Kunle Olukotun, Marius Lindauer, Frank Hutter

Beyond Low-Pass Filters: Adaptive Feature Propagation on Graphs Shouheng Li, Dongwoo Kim, Qing Wang

Black-Box Optimizer with Stochastic Implicit Natural Gradient Yueming Lyu, Ivor W. Tsang

Bridging Few-Shot Learning and Adaptation: New Challenges of Support-Query Shift Etienne Bennequin, Victor Bouvier, Myriam Tami, Antoine Toubhans, Céline Hudelot

Calling to CNN-LSTM for Rumor Detection: A Deep Multi-Channel Model for Message Veracity Classification in Microblogs Abderrazek Azri, Cécile Favre, Nouria Harbi, Jérôme Darmont, Camille Noûs

Causal Explanation of Convolutional Neural Networks Hichem Debbi

Certification of Model Robustness in Active Class Selection Mirko Bunse, Katharina Morik

Change Detection in Multivariate Datastreams Controlling False Alarms Luca Frittoli, Diego Carrera, Giacomo Boracchi

CHECKER: Detecting Clickbait Thumbnails with Weak Supervision and Co-Teaching Tianyi Xie, Thai Le, Dongwon Lee

Checking Robustness of Representations Learned by Deep Neural Networks Kamil Szyc, Tomasz Walkowiak, Henryk Maciejewski

CMIX: Deep Multi-Agent Reinforcement Learning with Peak and Average Constraints Chenyi Liu, Nan Geng, Vaneet Aggarwal, Tian Lan, Yuan Yang, Mingwei Xu

ConCAD: Contrastive Learning-Based Cross Attention for Sleep Apnea Detection Guanjie Huang, Fenglong Ma

Conditional Neural Relational Inference for Interacting Systems Joao A. Candido Ramos, Lionel Blondé, Stéphane Armand, Alexandros Kalousis

Consequence-Aware Sequential Counterfactual Generation Philip Naumann, Eirini Ntoutsi

Conservative Online Convex Optimization Martino Bernasconi de Luca, Edoardo Vittori, Francesco Trovò, Marcello Restelli

Continual Learning with Dual Regularizations Xuejun Han, Yuhong Guo

Continuous-Action Reinforcement Learning for Portfolio Allocation of a Life Insurance Company Carlo Abrate, Alessio Angius, Gianmarco De Francisci Morales, Stefano Cozzini, Francesca Iadanza, Laura Li Puma, Simone Pavanelli, Alan Perotti, Stefano Pignataro, Silvia Ronchiadin

Continuous-Time Markov-Switching GARCH Process with Robust State Path Identification and Volatility Estimation Yinan Li, Fang Liu

Correlation Clustering with Global Weight Bounds Domenico Mandaglio, Andrea Tagarelli, Francesco Gullo

Countrywide Origin-Destination Matrix Prediction and Its Application for COVID-19 Renhe Jiang, Zhaonan Wang, Zekun Cai, Chuang Yang, Zipei Fan, Tianqi Xia, Go Matsubara, Hiroto Mizuseki, Xuan Song, Ryosuke Shibasaki

COVID Edge-Net: Automated COVID-19 Lung Lesion Edge Detection in Chest CT Images Kang Wang, Yang Zhao, Yong Dou, Dong Wen, Zikai Gao

CQNet: A Clustering-Based Quadruplet Network for Decentralized Application Classification via Encrypted Traffic Yu Wang, Gang Xiong, Chang Liu, Zhen Li, Mingxin Cui, Gaopeng Gou

Crowdsourcing Evaluation of Saliency-Based XAI Methods Xiaotian Lu, Arseny Tolmachev, Tatsuya Yamamoto, Koh Takeuchi, Seiji Okajima, Tomoyoshi Takebayashi, Koji Maruhashi, Hisashi Kashima

CycleGAN Through the Lens of (Dynamical) Optimal Transport Emmanuel de Bézenac, Ibrahim Ayed, Patrick Gallinari

Decoupling Sparsity and Smoothness in Dirichlet Belief Networks Yaqiong Li, Xuhui Fan, Ling Chen, Bin Li, Scott A. Sisson

Deep Adaptive Multi-Intention Inverse Reinforcement Learning Ariyan Bighashdel, Panagiotis Meletis, Pavol Jancura, Gijs Dubbelman

Deep Conditional Transformation Models Philipp F. M. Baumann, Torsten Hothorn, David Rügamer

Deep Model Compression via Two-Stage Deep Reinforcement Learning Huixin Zhan, Wei-Ming Lin, Yongcan Cao

Deep Multi-Task Augmented Feature Learning via Hierarchical Graph Neural Network Pengxin Guo, Chang Deng, Linjie Xu, Xiaonan Huang, Yu Zhang

Deep Structural Point Process for Learning Temporal Interaction Networks Jiangxia Cao, Xixun Lin, Xin Cong, Shu Guo, Hengzhu Tang, Tingwen Liu, Bin Wang

DeepPE: Emulating Parameterization in Numerical Weather Forecast Model Through Bidirectional Network Fengyang Xu, Wencheng Shi, Yunfei Du, Zhiguang Chen, Yutong Lu

DeFraudNet: An End-to-End Weak Supervision Framework to Detect Fraud in Online Food Delivery Jose Mathew, Meghana Negi, Rutvik Vijjali, Jairaj Sathyanarayana

Dep-L0: Improving L0-Based Network Sparsification via Dependency Modeling Yang Li, Shihao Ji

Deviation-Based Marked Temporal Point Process for Marker Prediction Anand Vir Singh Chauhan, Shivshankar Reddy, Maneet Singh, Karamjit Singh, Tanmoy Bhowmik

Differentiable Feature Selection, a Reparameterization Approach Jérémie Donà, Patrick Gallinari

Disagreement Options: Task Adaptation Through Temporally Extended Actions Matthias Hutsebaut-Buysse, Tom De Schepper, Kevin Mets, Steven Latré

Discovering Proper Neighbors to Improve Session-Based Recommendation Lin Liu, Li Wang, Tao Lian

Disentanglement and Local Directions of Variance Alexander Rakowski, Christoph Lippert

Disparity Between Batches as a Signal for Early Stopping Mahsa Forouzesh, Patrick Thiran

Diversity-Aware K-Median: Clustering with Fair Center Representation Suhas Thejaswi, Bruno Ordozgoiti, Aristides Gionis

Dropout's Dream Land: Generalization from Learned Simulators to Reality Zac Wellmer, James T. Kwok

Dynamic Heterogeneous Graph Embedding via Heterogeneous Hawkes Process Yugang Ji, Tianrui Jia, Yuan Fang, Chuan Shi

EARLIN: Early Out-of-Distribution Detection for Resource-Efficient Collaborative Inference Sumaiya Tabassum Nimi, Md. Adnan Arefeen, Md. Yusuf Sarwar Uddin, Yugyung Lee

Effects of Boundary Conditions in Fully Convolutional Networks for Learning Spatio-Temporal Dynamics Antonio Alguacil, Wagner Gonçalves Pinto, Michael Bauerheim, Marc C. Jacob, Stéphane Moreau

Efficient and Less Centralized Federated Learning Li Chou, Zichang Liu, Zhuang Wang, Anshumali Shrivastava

Embedding Knowledge Graphs Attentive to Positional and Centrality Qualities Afshin Sadeghi, Diego Collarana, Damien Graux, Jens Lehmann

Enabling Machine Learning on the Edge Using SRAM Conserving Efficient Neural Networks Execution Approach Bharath Sudharsan, Pankesh Patel, John G. Breslin, Muhammad Intizar Ali

Energy and Emission Prediction for Mixed-Vehicle Transit Fleets Using Multi-Task and Inductive Transfer Learning Michael Wilbur, Ayan Mukhopadhyay, Sayyed Vazirizade, Philip Pugliese, Aron Laszka, Abhishek Dubey

Enhancing Summarization with Text Classification via Topic Consistency Jingzhou Liu, Yiming Yang

Ensemble and Auxiliary Tasks for Data-Efficient Deep Reinforcement Learning Muhammad Rizki Maulana, Wee Sun Lee

Ensemble of Local Decision Trees for Anomaly Detection in Mixed Data Sunil Aryal, Jonathan R. Wells

Ensembling Shift Detectors: An Extensive Empirical Evaluation Simona Maggio, Léo Dreyfus-Schmidt

Estimating the Electrical Power Output of Industrial Devices with End-to-End Time-Series Classification in the Presence of Label Noise Andrea Castellani, Sebastian Schmitt, Barbara Hammer

Explainable Abusive Language Classification Leveraging User and Network Data Maximilian Wich, Edoardo Mosca, Adrian Gorniak, Johannes Hingerl, Georg Groh

Explainable Multiple Instance Learning with Instance Selection Randomized Trees Tomás Komárek, Jan Brabec, Petr Somol

Explainable Online Deep Neural Network Selection Using Adaptive Saliency Maps for Time Series Forecasting Amal Saadallah, Matthias Jakobs, Katharina Morik

Exploiting History Data for Nonstationary Multi-Armed Bandit Gerlando Re, Fabio Chiusano, Francesco Trovò, Diego Carrera, Giacomo Boracchi, Marcello Restelli

Fast Conditional Network Compression Using Bayesian HyperNetworks Phuoc Nguyen, Truyen Tran, Ky Le, Sunil Gupta, Santu Rana, Dang Nguyen, Trong Nguyen, Shannon Ryan, Svetha Venkatesh

Feature Enhanced Capsule Networks for Robust Automatic Essay Scoring Arushi Sharma, Anubha Kabra, Rajiv Kapoor

FedDNA: Federated Learning with Decoupled Normalization-Layer Aggregation for Non-IID Data Jian-Hui Duan, Wenzhong Li, Sanglu Lu

FedPHP: Federated Personalization with Inherited Private Models Xin-Chun Li, De-Chuan Zhan, Yunfeng Shao, Bingshuai Li, Shaoming Song

Finding High-Value Training Data Subset Through Differentiable Convex Programming Soumi Das, Arshdeep Singh, Saptarshi Chatterjee, Suparna Bhattacharya, Sourangshu Bhattacharya

Follow Your Path: A Progressive Method for Knowledge Distillation Wenxian Shi, Yuxuan Song, Hao Zhou, Bohan Li, Lei Li

Gaussian Process Encoders: VAEs with Reliable Latent-Space Uncertainty Judith Bütepage, Lucas Maystre, Mounia Lalmas

Generating Multi-Type Temporal Sequences to Mitigate Class-Imbalanced Problem Lun Jiang, Nima Salehi Sadghiani, Zhuo Tao, Andrew Cohen

Generative Max-Mahalanobis Classifiers for Image Classification, Generation and More Xiulong Yang, Hui Ye, Yang Ye, Xiang Li, Shihao Ji

Getting Your Package to the Right Place: Supervised Machine Learning for Geolocation George Forman

Goal Modelling for Deep Reinforcement Learning Agents Jonathan Leung, Zhiqi Shen, Zhiwei Zeng, Chunyan Miao

Gradient-Based Label Binning in Multi-Label Classification Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz, Eyke Hüllermeier

Graph Fraud Detection Based on Accessibility Score Distributions Minji Yoon

GraphAnoGAN: Detecting Anomalous Snapshots from Attributed Graphs Siddharth Bhatia, Yiwei Wang, Bryan Hooi, Tanmoy Chakraborty

GraphSVX: Shapley Value Explanations for Graph Neural Networks Alexandre Duval, Fragkiskos D. Malliaros

High-Probability Kernel Alignment Regret Bounds for Online Kernel Selection Shizhong Liao, Junfan Li

Holistic Prediction for Public Transport Crowd Flows: A Spatio Dynamic Graph Network Approach Bingjie He, Shukai Li, Chen Zhang, Baihua Zheng, Fugee Tsung

Hyper-Parameter Optimization for Latent Spaces Bruno Veloso, Luciano Caroprese, Matthias König, Sónia Teixeira, Giuseppe Manco, Holger H. Hoos, João Gama

Improving Ambulance Dispatching with Machine Learning and Simulation Nikki Theeuwes, Geert-Jan van Houtum, Yingqian Zhang

Inductive Link Prediction with Interactive Structure Learning on Attributed Graph Shuo Yang, Binbin Hu, Zhiqiang Zhang, Wang Sun, Yang Wang, Jun Zhou, Hongyu Shan, Yuetian Cao, Borui Ye, Yanming Fang, Quan Yu

Information Interaction Profile of Choice Adoption Gaël Poux-Médard, Julien Velcin, Sabine Loudcher

Inter-Domain Multi-Relational Link Prediction Luu Huu Phuc, Koh Takeuchi, Seiji Okajima, Arseny Tolmachev, Tomoyoshi Takebayashi, Koji Maruhashi, Hisashi Kashima

Interpretable Counterfactual Explanations Guided by Prototypes Arnaud Van Looveren, Janis Klaise

Invertible Manifold Learning for Dimension Reduction Siyuan Li, Haitao Lin, Zelin Zang, Lirong Wu, Jun Xia, Stan Z. Li

Iterated Matrix Reordering Gauthier Van Vracem, Siegfried Nijssen

Joint Geometric and Topological Analysis of Hierarchical Datasets Lior Aloni, Omer Bobrowski, Ronen Talmon

Joslim: Joint Widths and Weights Optimization for Slimmable Neural Networks Ting-Wu Chin, Ari S. Morcos, Diana Marculescu

Knowledge Distillation with Distribution Mismatch Dang Nguyen, Sunil Gupta, Trong Nguyen, Santu Rana, Phuoc Nguyen, Truyen Tran, Ky Le, Shannon Ryan, Svetha Venkatesh

Knowledge Infused Policy Gradients with Upper Confidence Bound for Relational Bandits Kaushik Roy, Qi Zhang, Manas Gaur, Amit P. Sheth

Label-Assisted Memory Autoencoder for Unsupervised Out-of-Distribution Detection Shuyi Zhang, Chao Pan, Liyan Song, Xiaoyu Wu, Zheng Hu, Ke Pei, Peter Tino, Xin Yao

Learning Disentangled Representations with the Wasserstein Autoencoder Benoit Gaujac, Ilya Feige, David Barber

Learning Explainable Representations of Malware Behavior Paul Prasse, Jan Brabec, Jan Kohout, Martin Kopp, Lukás Bajer, Tobias Scheffer

Learning from Noisy Similar and Dissimilar Data Soham Dan, Han Bao, Masashi Sugiyama

Learning to Build High-Fidelity and Robust Environment Models Weinan Zhang, Zhengyu Yang, Jian Shen, Minghuan Liu, Yimin Huang, Xing Zhang, Ruiming Tang, Zhenguo Li

Learning Unbiased Representations via Rényi Minimization Vincent Grari, Oualid El Hajouji, Sylvain Lamprier, Marcin Detyniecki

Learning Weakly Convex Sets in Metric Spaces Eike Stadtländer, Tamás Horváth, Stefan Wrobel

LSMI-Sinkhorn: Semi-Supervised Mutual Information Estimation with Optimal Transport Yanbin Liu, Makoto Yamada, Yao-Hung Hubert Tsai, Tam Le, Ruslan Salakhutdinov, Yi Yang

Machine Learning Guided Optimization for Demand Responsive Transport Systems Louis Zigrand, Pegah Alizadeh, Emiliano Traversi, Roberto Wolfler Calvo

MaxVA: Fast Adaptation of Step Sizes by Maximizing Observed Variance of Gradients Chen Zhu, Yu Cheng, Zhe Gan, Furong Huang, Jingjing Liu, Tom Goldstein

Methods for Automatic Machine-Learning Workflow Analysis Lorenz Wendlinger, Emanuel Berndl, Michael Granitzer

Midpoint Regularization: From High Uncertainty Training Labels to Conservative Classification Decisions Hongyu Guo

Mining Anomalies in Subspaces of High-Dimensional Time Series for Financial Transactional Data Jingzhu He, Chin-Chia Michael Yeh, Yanhong Wu, Liang Wang, Wei Zhang

MMNet: Multi-Granularity Multi-Mode Network for Item-Level Share Rate Prediction Haomin Yu, Mingfei Liang, Ruobing Xie, Zhenlong Sun, Bo Zhang, Leyu Lin

Model-Based Offline Policy Optimization with Distribution Correcting Regularization Jian Shen, Mingcheng Chen, Zhicheng Zhang, Zhengyu Yang, Weinan Zhang, Yong Yu

Modeling Multi-Factor and Multi-Faceted Preferences over Sequential Networks for Next Item Recommendation Yingpeng Du, Hongzhi Liu, Zhonghai Wu

Monte Carlo Search Algorithms for Network Traffic Engineering Chen Dang, Cristina Bazgan, Tristan Cazenave, Morgan Chopin, Pierre-Henri Wuillemin

More General and Effective Model Compression via an Additive Combination of Compressions Yerlan Idelbayev, Miguel Á. Carreira-Perpiñán

Multi-Agent Deep Reinforcement Learning with Spatio-Temporal Feature Fusion for Traffic Signal Control Xin Du, Jiahai Wang, Siyuan Chen, Zhiyue Liu

Multi-Agent Imitation Learning with Copulas Hongwei Wang, Lantao Yu, Zhangjie Cao, Stefano Ermon

Multi-Task Learning Curve Forecasting Across Hyperparameter Configurations and Datasets Shayan Jawed, Hadi S. Jomaa, Lars Schmidt-Thieme, Josif Grabocka

Multi-Task Learning for User Engagement and Adoption in Live Video Streaming Events Stefanos Antaris, Dimitrios Rafailidis, Romina Arriaza

Multi-View Self-Supervised Heterogeneous Graph Embedding Jianan Zhao, Qianlong Wen, Shiyu Sun, Yanfang Ye, Chuxu Zhang

Multitask Recalibrated Aggregation Network for Medical Code Prediction Wei Sun, Shaoxiong Ji, Erik Cambria, Pekka Marttinen

NA-Aware Machine Reading Comprehension for Document-Level Relation Extraction Zhenyu Zhang, Bowen Yu, Xiaobo Shu, Tingwen Liu

Neural Topic Models for Hierarchical Topic Detection and Visualization Dang Pham, Tuan M. V. Le

Non-Exhaustive Learning Using Gaussian Mixture Generative Adversarial Networks Jun Zhuang, Mohammad Al Hasan

OBELISC: Oscillator-Based Modelling and Control Using Efficient Neural Learning for Intelligent Road Traffic Signal Calculation Cristian Axenie, Rongye Shi, Daniele Foroni, Alexander Wieder, Mohamad Al Hajj Hassan, Paolo Sottovia, Margherita Grossi, Stefano Bortoli, Götz Brasche

Off-Policy Differentiable Logic Reinforcement Learning Li Zhang, Xin Li, Mingzhong Wang, Andong Tian

On Generalization of Graph Autoencoders with Adversarial Training Tianjin Huang, Yulong Pei, Vlado Menkovski, Mykola Pechenizkiy

On Inferring a Meaningful Similarity Metric for Customer Behaviour Sophie van den Berg, Marwan Hassani

Open Data Science to Fight COVID-19: Winning the 500k XPRIZE Pandemic Response Challenge Miguel Angel Lozano, Òscar Garibo i Orts, Eloy Piñol, Miguel Rebollo, Kristina Polotskaya, Miguel Ángel García-March, J. Alberto Conejero, Francisco Escolano, Nuria Oliver

Optimal Teaching Curricula with Compositional Simplicity Priors Manuel Garcia-Piqueras, José Hernández-Orallo

PATHATTACK: Attacking Shortest Paths in Complex Networks Benjamin A. Miller, Zohair Shafi, Wheeler Ruml, Yevgeniy Vorobeychik, Tina Eliassi-Rad, Scott Alfeld

Periodic Intra-Ensemble Knowledge Distillation for Reinforcement Learning Zhang-Wei Hong, Prabhat Nagarajan, Guilherme Maeda

Physics Knowledge Discovery via Neural Differential Equation Embedding Yexiang Xue, Md. Nasim, Maosen Zhang, Cuncai Fan, Xinghang Zhang, Anter El-Azab

Precise Weather Parameter Predictions for Target Regions via Neural Networks Yihe Zhang, Xu Yuan, Sytske K. Kimball, Eric Rappin, Li Chen, Paul J. Darby Iii, Tom Johnsten, Lu Peng, Boisy Pitre, David Bourrie, Nian-Feng Tzeng

Principled Interpolation in Normalizing Flows Samuel G. Fadel, Sebastian Mair, Ricardo da Silva Torres, Ulf Brefeld

Privacy Amplification via Iteration for Shuffled and Online PNSGD Matteo Sordello, Zhiqi Bu, Jinshuo Dong

Probing Negative Sampling for Contrastive Learning to Learn Graph Representations Shiyi Chen, Ziao Wang, Xinni Zhang, Xiaofeng Zhang, Dan Peng

PuzzleShuffle: Undesirable Feature Learning for Semantic Shift Detection Yusuke Kanebako, Kazuki Tsukamoto

Quantifying Explanations of Neural Networks in E-Commerce Based on LRP Anna Nguyen, Franz Krause, Daniel Hagenmayer, Michael Färber

Quantized Gromov-Wasserstein Samir Chowdhury, David Miller, Tom Needham

Rank Aggregation for Non-Stationary Data Streams Ekhine Irurozki, Aritz Pérez, Jesus L. Lobo, Javier Del Ser

Recognizing Skeleton-Based Hand Gestures by a Spatio-Temporal Network Xin Li, Jun Liao, Li Liu

Reconnaissance for Reinforcement Learning with Safety Constraints Shin-ichi Maeda, Hayato Watahiki, Yi Ouyang, Shintarou Okada, Masanori Koyama, Prabhat Nagarajan

Reparameterized Sampling for Generative Adversarial Networks Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin

Representation Learning on Multi-Layered Heterogeneous Network Delvin Ce Zhang, Hady W. Lauw

Reservoir Pattern Sampling in Data Streams Arnaud Giacometti, Arnaud Soulet

Robust Learning for Text Classification with Multi-Source Noise Simulation and Hard Example Mining Guowei Xu, Wenbiao Ding, Weiping Fu, Zhongqin Wu, Zitao Liu

Robust Regression via Model Based Methods Armin Moharrer, Khashayar Kamran, Edmund Yeh, Stratis Ioannidis

Robust Selection Stability Estimation in Correlated Spaces Victor Hamer, Pierre Dupont

Routine Bandits: Minimizing Regret on Recurring Problems Hassan Saber, Léo Saci, Odalric-Ambrym Maillard, Audrey Durand

Rumour Detection via Zero-Shot Cross-Lingual Transfer Learning Lin Tian, Xiuzhen Zhang, Jey Han Lau

Self-Bounding Majority Vote Learning Algorithms by the Direct Minimization of a Tight PAC-Bayesian C-Bound Paul Viallard, Pascal Germain, Amaury Habrard, Emilie Morvant

Self-Disclosure on Twitter During the COVID-19 Pandemic: A Network Perspective Prasanna Umar, Chandan Akiti, Anna Cinzia Squicciarini, Sarah Michele Rajtmajer

Self-Supervised Multi-Task Representation Learning for Sequential Medical Images Nanqing Dong, Michael Kampffmeyer, Irina Voiculescu

Semantic-Specific Hierarchical Alignment Network for Heterogeneous Graph Adaptation Yuanxin Zhuang, Chuan Shi, Cheng Yang, Fuzhen Zhuang, Yangqiu Song

Semi-Structured Document Annotation Using Entity and Relation Types Arpita Kundu, Subhasis Ghosh, Indrajit Bhattacharya

Semi-Supervised Semantic Visualization for Networked Documents Delvin Ce Zhang, Hady W. Lauw

Sibling Regression for Generalized Linear Models Shiv Shankar, Daniel Sheldon

Single Model for Influenza Forecasting of Multiple Countries by Multi-Task Learning Taichi Murayama, Shoko Wakamiya, Eiji Aramaki

Small-Vote Sample Selection for Label-Noise Learning Youze Xu, Yan Yan, Jing-Hao Xue, Yang Lu, Hanzi Wang

Smurf-Based Anti-Money Laundering in Time-Evolving Transaction Networks Michele Starnini, Charalampos E. Tsourakakis, Maryam Zamanipour, André Panisson, Walter Allasia, Marco Fornasiero, Laura Li Puma, Valeria Ricci, Silvia Ronchiadin, Angela Ugrinoska, Marco Varetto, Dario Moncalvo

Source Hypothesis Transfer for Zero-Shot Domain Adaptation Tomoya Sakai

Sparse Information Filter for Fast Gaussian Process Regression Lucas Kania, Manuel Schürch, Dario Azzimonti, Alessio Benavoli

Spatial Contrastive Learning for Few-Shot Classification Yassine Ouali, Céline Hudelot, Myriam Tami

Spatio-Temporal Multi-Graph Networks for Demand Forecasting in Online Marketplaces Ankit Gandhi, Aakanksha, Sivaramakrishnan Kaveri, Vineet Chaoji

SPOT: A Framework for Selection of Prototypes Using Optimal Transport Karthik S. Gurumoorthy, Pratik Jawanpuria, Bamdev Mishra

Strategic Mitigation Against Wireless Attacks on Autonomous Platoons Guoxin Sun, Tansu Alpcan, Benjamin I. P. Rubinstein, Seyit Camtepe

Streaming Decision Trees for Lifelong Learning Lukasz Korycki, Bartosz Krawczyk

Studying and Exploiting the Relationship Between Model Accuracy and Explanation Quality Yunzhe Jia, Eibe Frank, Bernhard Pfahringer, Albert Bifet, Nick Jin Sean Lim

Subspace Clustering Based Analysis of Neural Networks Uday Singh Saini, Pravallika Devineni, Evangelos E. Papalexakis

TagRec: Automated Tagging of Questions with Hierarchical Learning Taxonomy Venktesh V, Mukesh K. Mohania, Vikram Goyal

Taking over the Stock Market: Adversarial Perturbations Against Algorithmic Traders Elior Nehemya, Yael Mathov, Asaf Shabtai, Yuval Elovici

Task Embedding Temporal Convolution Networks for Transfer Learning Problems in Renewable Power Time Series Forecast Jens Schreiber, Stephan Vogt, Bernhard Sick

TaxoRef: Embeddings Evaluation for AI-Driven Taxonomy Refinement Lorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica, Navid Nobani

The Bures Metric for Generative Adversarial Networks Hannes De Meulemeester, Joachim Schreurs, Michaël Fanuel, Bart De Moor, Johan A. K. Suykens

The Curious Case of Convex Neural Networks Sarath Sivaprasad, Ankur Singh, Naresh Manwani, Vineet Gandhi

The Joy of Dressing Is an Art: Outfit Generation Using Self-Attention Bi-LSTM Manchit Madan, Ankur Chouragade, Sreekanth Vempati

The KL-Divergence Between a Graph Model and Its Fair I-Projection as a Fairness Regularizer Maarten Buyl, Tijl De Bie

The Limit Order Book Recreation Model (LOBRM): An Extended Analysis Zijian Shi, John Cartlidge

Time Aspect in Making an Actionable Prediction of a Conversation Breakdown Piotr Janiszewski, Mateusz Lango, Jerzy Stefanowski

Time Series Forecasting with Gaussian Processes Needs Priors Giorgio Corani, Alessio Benavoli, Marco Zaffalon

Topic-to-Essay Generation with Comprehensive Knowledge Enhancement Zhiyue Liu, Jiahai Wang, Zhenghong Li

Topological Anomaly Detection in Dynamic Multilayer Blockchain Networks Dorcas Ofori-Boateng, Ignacio Segovia-Dominguez, Cuneyt Gurcan Akcora, Murat Kantarcioglu, Yulia R. Gel

Transformers: "The End of History" for Natural Language Processing? Anton Chernyavskiy, Dmitry Ilvovsky, Preslav Nakov

UCSL : A Machine Learning Expectation-Maximization Framework for Unsupervised Clustering Driven by Supervised Learning Robin Louiset, Pietro Gori, Benoit Dufumier, Josselin Houenou, Antoine Grigis, Edouard Duchesnay

Unifying Domain Adaptation and Domain Generalization for Robust Prediction Across Minority Racial Groups Farzaneh Khoshnevisan, Min Chi

Unsupervised Learning of Joint Embeddings for Node Representation and Community Detection Rayyan Ahmad Khan, Muhammad Umer Anwaar, Omran Kaddah, Zhiwei Han, Martin Kleinsteuber

Unsupervised Task Clustering for Multi-Task Reinforcement Learning Johannes Ackermann, Oliver Richter, Roger Wattenhofer

VAMBC: A Variational Approach for Mobility Behavior Clustering Mingxuan Yue, Yao-Yi Chiang, Cyrus Shahabi

Variance Reduced Stochastic Proximal Algorithm for AUC Maximization Soham Dan, Dushyant Sahoo

Variational Hyper-Encoding Networks Phuoc Nguyen, Truyen Tran, Sunil Gupta, Santu Rana, Hieu-Chi Dam, Svetha Venkatesh

VeriDL: Integrity Verification of Outsourced Deep Learning Services Boxiang Dong, Bo Zhang, Wendy Hui Wang

Very Fast Streaming Submodular Function Maximization Sebastian Buschjäger, Philipp-Jan Honysz, Lukas Pfahler, Katharina Morik

VOGUE: Answer Verbalization Through Multi-Task Learning Endri Kacupaj, Shyamnath Premnadh, Kuldeep Singh, Jens Lehmann, Maria Maleshkova

Which Minimizer Does My Neural Network Converge to? Manuel Nonnenmacher, David Reeb, Ingo Steinwart

XRR: Explainable Risk Ranking for Financial Reports Ting-Wei Lin, Ruei-Yao Sun, Hsuan-Ling Chang, Chuan-Ju Wang, Ming-Feng Tsai

Zero-Shot Scene Graph Relation Prediction Through Commonsense Knowledge Integration Xuan Kan, Hejie Cui, Carl Yang