Routine Bandits: Minimizing Regret on Recurring Problems
Hassan Saber, Léo Saci, Odalric-Ambrym Maillard, Audrey Durand
Conservative Online Convex Optimization
Martino Bernasconi de Luca, Edoardo Vittori, Francesco Trovò, Marcello Restelli
Knowledge Infused Policy Gradients with Upper Confidence Bound for Relational Bandits
Kaushik Roy, Qi Zhang, Manas Gaur, Amit Sheth
Exploiting History Data for Nonstationary Multi-armed Bandit
Gerlando Re, Fabio Chiusano, Francesco Trovò, Diego Carrera, Giacomo Boracchi, Marcello Restelli
High-probability Kernel Alignment Regret Bounds for Online Kernel Selection
Shizhong Liao, Junfan Li
Periodic Intra-Ensemble Knowledge Distillation for Reinforcement Learning
Zhang-Wei~Hong, Prabhat~Nagarajan, Guilherme~Maeda
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
Ensemble and Auxiliary Tasks for Data-Efficient Deep Reinforcement Learning
Muhammad Rizki Maulana, Wee Sun Lee
Multi-Agent Imitation Learning with Copulas
Hongwei Wang, Lantao Yu, Zhangjie Cao, Stefano Ermon
CMIX: Deep Multi-agent Reinforcement Learning with Peak and Average Constraints
Chenyi Liu, Nan Geng\and Vaneet Aggarwal, Tian Lan, Yuan Yang, Mingwei Xu
Model-based Offline Policy Optimization with Distribution Correcting Regularization
Jian Shen, Mingcheng Chen, Zhicheng Zhang, Zhengyu Yang, \\ Weinan Zhang , Yong Yu
Disagreement Options: Task Adaptation Through Temporally Extended Actions
Matthias Hutsebaut-Buysse, Tom De Schepper, Kevin Mets, Steven Latr\'e
Deep Adaptive Multi-Intention Inverse Reinforcement Learning
Ariyan Bighashdel, Panagiotis Meletis, Pavol Jancura, Gijs Dubbelman
Unsupervised Task Clustering for\\ Multi-Task Reinforcement Learning
Johannes Ackermann, Oliver Richter, Roger~Wattenhofer
Deep Model Compression Via Two-Stage Deep Reinforcement Learning
Huixin Zhan, Wei-Ming Lin, Yongcan Cao
Dropout's Dream Land: Generalization from Learned Simulators to Reality
Zac Wellmer, James T. Kwok
Goal Modelling for Deep Reinforcement Learning Agents
Jonathan Leung , Zhiqi Shen, Zhiwei Zeng, Chunyan Miao
Deviation-based Marked Temporal Point Process for Marker Prediction
Anand Vir Singh Chauhan, Shivshankar Reddy, Maneet Singh, Karamjit Singh, Tanmoy Bhowmik
Deep Structural Point Process for Learning Temporal Interaction Networks
Jiangxia Cao, Xixun Lin, Xin Cong, Shu Guo\and Hengzhu Tang, Tingwen Liu, Bin Wang
Holistic Prediction for Public Transport Crowd Flows: A Spatio Dynamic Graph Network Approach
Bingjie He, Shukai Li, Chen Zhang, Baihua Zheng, Fugee Tsung
Discovering proper neighbors to improve session-based recommendation
Lin Liu, Li Wang, Tao Lian
Continuous-time Markov-switching GARCH Process with Robust State Path Identification and Volatility Estimation
Yinan Li , Fang LiuYinan Li
Dynamic Heterogeneous Graph Embedding via Heterogeneous Hawkes Process
Yugang Ji, Tianrui Jia , Yuan Fang, Chuan Shi
Explainable Online Deep Neural Network Selection using Adaptive Saliency Maps for Time Series Forecasting
Amal Saadallah, Matthias Jakobs, Katharina Morik
Change Detection in Multivariate Datastreams Controlling False Alarms
Luca Frittoli, Diego Carrera , Giacomo Boracchi
A Mixed Noise and Constraint-based Approach to Causal Inference in Time Series
Karim Assaad , Emilie Devijver , Eric Gaussier, Ali Ait-Bachir
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
Multi-task Learning Curve Forecasting Across Hyperparameter Configurations and Datasets
Shayan Jawed, Hadi Jomaa, Lars Schmidt-Thieme, Josif Grabocka
Unifying Domain Adaptation and Domain Generalization for Transfer among Racial Groups across Medical Systems
Farzaneh Khoshnevisan, Min Chi
Deep Multi-Task Augmented Feature Learning via Hierarchical Graph Neural Network
Pengxin Guo, Chang Deng, Linjie Xu, Xiaonan Huang, Yu Zhang
Bridging Few-Shot Learning and Adaptation: New Challenges of Support-Query Shift
Etienne Bennequin , Victor Bouvier, Myriam Tami , Antoine Toubhans , C\'eline Hudelot
FedPHP: Federated Personalization with Inherited Private Models
Xin-Chun Li, De-Chuan Zhan, Yunfeng Shao ,
Rumour Detection via Zero-shot Cross-lingual Transfer Learning
Lin Tian, Xiuzhen Zhang , Jey Han Lau
EARLIN: Early Out-of-Distribution Detection for Resource-efficient Collaborative Inference
Sumaiya Tabassum Nimi, Md Adnan Arefeen, Md Yusuf Sarwar Uddin, Yugyung Lee
LSMI-Sinkhorn: Semi-supervised Mutual Information Estimation with Optimal Transport
Yanbin Liu, Makoto Yamada, Yao-Hung Hubert Tsai, Tam Le, Ruslan Salakhutdinov, Yi Yang
Spatial Contrastive Learning for Few-Shot Classification
Yassine Ouali, Céline Hudelot, Myriam Tami
Ensemble of Local Decision Trees for Anomaly Detection in Mixed Data
Sunil Aryal, Jonathan R. Wells
Optimal Teaching Curricula with Compositional Simplicity Priors
Manuel Garcia-Piqueras , José~Hernàndez-Orallo
FedDNA: Federated Learning with Decoupled Normalization-Layer Aggregation for Non-IID Data
Jian-Hui Duan, Wenzhong Li, Sanglu Lu
The Curious Case of Convex Neural Networks
Sarath Sivaprasad, Ankur Singh, Naresh Manwani,, Vineet Gandhi
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
Efficient and Less Centralized Federated Learning
Li Chou, Zichang Liu, Zhuang Wang , Anshumali Shrivastava
Topological Anomaly Detection in Dynamic Multilayer Blockchain Networks
Dorcas Ofori-Boateng, Ignacio Segovia Dominguez, Cuneyt Akcora, Murat Kantarcioglu, Yulia Gel
Non-Exhaustive Learning Using Gaussian Mixture Generative Adversarial Networks
Jun Zhuang , Mohammad Al Hasan
Unsupervised Learning of Joint Embeddings for Node Representation and Community Detection
Rayyan Ahmad Khan, Muhammad Umer Anwaar, Omran Kaddah, Zhiwei Han, Martin Kleinsteuber
GraphAnoGAN: Detecting Anomalous Snapshots from Attributed Graphs
Siddharth Bhatia , Yiwei Wang, Bryan Hooi, Tanmoy Chakraborty
The Bures Metric for Generative Adversarial Networks
Hannes De Meulemeester , Joachim Schreurs, Micha\"el Fanuel, Bart De Moor, Johan A.K. Suykens
Generative Max-Mahalanobis Classifiers for Image Classification, Generation and More
Xiulong Yang, Hui Ye, Yang Ye, Xiang Li, Shihao Ji
Gaussian Process Encoders: VAEs with Reliable Latent-Space Uncertainty
Judith B\"utepage , Lucas Maystre, Mounia Lalmas
Variational Hyper-Encoding Networks
Phuoc Nguyen , Truyen Tran, Sunil Gupta , Santu Rana, Hieu-Chi Dam , Svetha Venkatesh
Principled Interpolation in Normalizing Flows
Samuel~G.~Fadel, Sebastian~Mair, Ricardo~da~S.~Torres, Ulf~Brefeld
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
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
Midpoint Regularization: from High Uncertainty Training Labels to Conservative Classification Decisions
Hongyu Guo
Learning Weakly Convex Sets in Metric Spaces
Eike Stadtl\"{a}nder, Tam\'{a}s Horv\'{a}th, Stefan Wrobel
Disparity Between Batches as a Signal for Early Stopping
Mahsa Forouzesh, Patrick Thiran
Knowledge Distillation with Distribution Mismatch
Dang Nguyen, Sunil Gupta, Trong Nguyen, Santu Rana, Phuoc Nguyen, Truyen Tran, Ky Le, Shannon Ryan, Svetha Venkatesh
Certification of Model Robustness in~Active~Class~Selection
Mirko~Bunse, Katharina~Morik
Inter-domain Multi-relational Link Prediction
Luu Huu Phuc, Koh Takeuchi, Seiji Okajima, Arseny Tolmachev, Tomoyoshi Takebayashi, Koji Maruhashi, Hisashi Kashima
GraphSVX: Shapley Value Explanations for Graph Neural Networks
Alexandre Duval, Fragkiskos D. Malliaros
Multi-View Self-Supervised Heterogeneous Graph Embedding
Jianan Zhao, Qianlong Wen, Shiyu Sun , Yanfang Ye , Chuxu Zhang
Semantic-Specific Hierarchical Alignment Network for Heterogeneous Graph Adaptation
YuanXin Zhuang, Chuan Shi, Cheng Yang, Fuzhen Zhuang, Yangqiu Song
The KL-Divergence between a Graph Model and its Fair I-Projection as a Fairness Regularizer
Maarten Buyl, Tijl De Bie
On Generalization of Graph Autoencoders with Adversarial Training
Tianjin Huang, Yulong Pei, Vlado Menkovski, Mykola Pechenizkiy
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
Representation Learning on Multi-Layered Heterogeneous Network
Delvin Ce Zhang, Hady W. Lauw
Adaptive Node Embedding Propagation for Semi-Supervised Classification
Yuya Ogawa, Seiji Maekawa , Yuya Sasaki , Yasuhiro Fujiwara, Makoto Onizuka
Probing Negative Sampling Strategies to Learn Graph Representations via Unsupervised Contrastive Learning
Shiyi~Chen, Ziao~Wang , Xinni~Zhang , Xiaofeng~Zhang, Dan~Peng
Beyond Low-Pass Filters: Adaptive Feature Propagation on Graphs
Shouheng Li, Dongwoo Kim , Qing Wang
Zero-Shot Scene Graph Relation Prediction through Commonsense Knowledge Integration
Xuan Kan, Hejie Cui, Carl Yan
Correlation Clustering with Global Weight Bounds
Domenico Mandaglio , Andrea Tagarelli , Francesco Gullo
Modeling Multi-factor and Multi-faceted Preferences over Sequential Networks for Next Item Recommendation
Yingpeng Du, Hongzhi Liu, Zhonghai Wu
PATHATTACK: Attacking Shortest Paths in Complex Networks
Benjamin~A.~Miller, Zohair~Shafi, Wheeler~Ruml, Yevgeniy~Vorobeychik, Tina~Eliassi-Rad, Scott~Alfeld
Embedding Knowledge Graphs Attentive to Positional and Centrality Qualities
Afshin Sadeghi, Diego Collarana, Damien Graux, Jens Lehmann
Reconnaissance for Reinforcement Learning with Safety Constraints
Shin-ichi~Maeda , Hayato~Watahiki, Yi~Ouyang , Shintarou~Okada, Masanori~Koyama , Prabhat~Nagarajan
VeriDL: Integrity Verification of Outsourced Deep Learning Services
Boxiang Dong, Bo Zhangt , Hui (Wendy) Wang
A Unified Batch Selection Policy for Active Metric Learning
Priyadarshini K, Siddhartha Chaudhuri, Vivek Borkar, Subhasis Chaudhuri
Off-Policy Differentiable Logic Reinforcement Learning
Li Zhang , Xin Li, Mingzhong Wang , Andong Tian
Interpretable Counterfactual Explanations Guided by Prototypes
Arnaud~Van~Looveren, Janis~Klaise
Finding High-Value Training Data Subset through Differentiable Convex Programming
Soumi Das, Arshdeep Singh , Saptarshi Chatterjee, Suparna Bhattacharya, Sourangshu Bhattacharya
Studying and Exploiting the Relationship Between Model Accuracy and Explanation Quality
Yunzhe Jia , Eibe Frank, Bernhard Pfahringer, Albert Bifet, Nick Lim
Explainable Multiple Instance Learning with Instance Selection Randomized Trees
Tom\'{a}\v{s} Kom\'{a}rek , Jan Brabec , Petr Somol
Adversarial Representation Learning With Closed-Form Solvers
Bashir~Sadeghi, Lan~Wang, Vishnu~Naresh~Boddeti
Learning Unbiased Representations via R\'enyi Minimization
Vincent Grari, Oualid El Hajouji, Sylvain Lamprier, Marcin Detyniecki
Diversity-aware k-median: Clustering with fair center representation
Suhas Thejaswi, Bruno Ordozgoiti , Aristides Gionis
Privacy Amplification via Iteration for Shuffled and Online PNSGD
Matteo Sordello , Zhiqi Bu, Jinshuo Dong
Deep Conditional Transformation Models
Philipp F. M. Baumann, Torsten Hothorn\and David Rügamer
Disentanglement and Local Directions of Variance
Alexander Rakowski, Christoph Lippert
Neural Topic Models for Hierarchical Topic Detection and Visualization
Dang Pham, Tuan M. V. Le
Semi-structured Document Annotation using Entity and Relation Types
Arpita Kundu, Subhasish Ghosh , Indrajit Bhattacharya
Learning disentangled representations with the Wasserstein Autoencoder
Benoit Gaujac, Ilya Feige, David Barber
Which Minimizer Does My Neural Network Converge To?
Manuel Nonnenmacher, David Reeb, Ingo Steinwart
Information Interaction Profile of Choice Adoption
Gael Poux-Medard, Julien Velcin, Sabine Loudcher
Joslim: Joint Widths and Weights Optimization for SLIMmable Neural Networks
Ting-Wu Chin, Ari S. Morcos, Diana Marculescu
A Variance Controlled Stochastic Method with Biased Estimation for Faster Non-convex Optimization
Jia Bi, Steve R. Gunn
Very Fast Streaming Submodular Function Maximization
Sebastian Buschjäger, Philipp-Jan Honysz, Lukas Pfahler, Katharina Morik
Dep-L_0: Improving L_0-based Network Sparsification via Dependency Modeling
Yang Li, Shihao Ji
Variance Reduced Stochastic Proximal Algorithm for AUC Maximization
Soham Dan, Dushyant Sahoo
Robust Regression via Model Based Methods
Armin Moharrer, Khashayar Kamran, Edmund Yeh, Stratis Ioannidis
Black-box Optimizer with Stochastic Implicit Natural Gradient
Yueming Lyu, Ivor W. Tsang
More General and Effective Model Compression via an Additive Combination of Compressions
Yerlan Idelbayev, Miguel {\'A} Carreira-Perpi{\~n}{\'a}n
Hyper-Parameter Optimization for Latent Spaces in Dynamic Recommender Systems
Bruno Veloso, Luciano Caroprese, Matthias K\"{o}nig , S\'onia Teixeira , Giuseppe Manco , Holger H. Hoos , Jo\~ao Gama
Bayesian Optimization with a Prior for the Optimum
Artur Souza, Luigi Nardi, Leonardo B. Oliveira, Kunle Olukotun, Marius Lindauer, Frank Hutter
Rank aggregation for non-stationary data streams
Ekhine Irurozki, Aritz Perez , Jesus Lobo, Javier Del Ser
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
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
Active Learning in Gaussian Process State Space Model
Hon Sum Alec Yu , Dingling Yao , Christoph Zimmer , Marc Toussaint, Duy Nguyen-Tuong
Ensembling Shift Detectors: an Extensive Empirical Evaluation
Simona Maggio, Léo Dreyfus-Schmidt
Adaptive Learning Rate and Momentum for Training Deep Neural Networks
Zhiyong Hao, Yixuan Jiang, Huihua Yu , Hsiao-Dong Chiang
Attack Transferability-Robust Multi-label Classification
Zhuo Yang, Yufei Han, Xiangliang Zhang
Differentiable Feature Selection, a Reparameterization Approach
Jérémie Dona' , Patrick Gallinari
ATOM: Robustifying Out-of-distribution Detection Using Outlier Mining
Jiefeng Chen, Yixuan Li, Xi Wu, Yingyu Liang, Somesh Jha
Robust Selection Stability Estimation in Correlated Spaces
Victor Hamer, Pierre Dupont
Gradient-based Label Binning in Multi-label Classification
Michael Rapp, Eneldo Loza Menc\'ia, Johannes F\"urnkranz, Eyke H\"ullermeier
Joint Geometric and Topological Analysis of Hierarchical Datasets
Lior Aloni, Omer Bobrowski, Ronen Talmon
Reparameterized Sampling for Generative Adversarial Networks
Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin
Asymptotic Statistical Analysis of Sparse Group LASSO via Approximate Message Passing
Kan Chen, Zhiqi Bu, Shiyun Xu
Sparse Information Filter for Fast Gaussian Process Regression
Lucas Kania, Manuel Sch\"urch, Dario Azzimonti, Alessio Benavoli
Bayesian Crowdsourcing with Constraints
Panagiotis A. Traganitis , Georgios B. Giannakis
VOGUE: Answer Verbalization through Multi-Task Learning
Endri Kacupaj, Shyamnath Premnadh, Kuldeep Singh , Jens Lehmann, Maria Maleshkova
NA-Aware Machine Reading Comprehension for Document-Level Relation Extraction
Zhenyu Zhang, Bowen Yu, Xiaobo Shu, Tingwen Liu
Follow Your Path: a Progressive Method for Knowledge Distillation
Wenxian Shi, Yuxuan Song, Hao Zhou, Bohan Li, Lei Li
TaxoRef: Embeddings Evaluation for AI-driven Taxonomy Refinement
Lorenzo Malandri , Fabio Mercorio , Mario Mezzanzanica , Navid Nobani
MaxVA: Fast Adaptation of Step Sizes by Maximizing Observed Variance of Gradients
Chen Zhu\and Yu Cheng\and Zhe Gan, Furong Huang, Jingjing Liu , Tom Goldstein
Augmenting Open-Domain Event Detection with Synthetic Data from GPT-2
Amir Pouran Ben Veyseh, Minh Van Nguyen , Bonan Min, Thien Huu Nguyen
Enhancing Summarization with Text Classification via Topic Consistency
Jingzhou Liu, Yiming Yang
Transformers: ``The End of History'' for Natural Language Processing?
Anton Chernyavskiy, Dmitry Ilvovsky, Preslav Nakov
Subspace Clustering Based Analysis of Neural Networks
Uday Singh Saini , Pravallika Devineni , Evangelos E. Papalexakis
Invertible Manifold Learning for Dimension Reduction
Siyuan Li, Haitao Lin, Zelin Zang, Lirong Wu, Jun Xia , Stan Z. Li
Small-Vote Sample Selection for Label-Noise Learning
Youze Xu, Yan Yan, Jing-Hao Xue, Yang Lu, Hanzi Wang
Semi-Supervised Semantic Visualization for Networked Documents
Delvin Ce Zhang, Hady W. Lauw
Self-Supervised Multi-Task Representation Learning for Sequential Medical Images
Nanqing Dong, Michael Kampffmeyer , Irina Voiculescu
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
Anomaly Detection: How to Artificially Increase your F1-Score with a Biased Evaluation Protocol
Damien Fourure, Muhammad Usama Javaid, Nicolas Posocco, Simon Tihon
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
AIMED-RL: Exploring Adversarial Malware Examples with Reinforcement Learning
Raphael Labaca-Castro, Sebastian Franz, Gabi Dreo Rodosek
Learning Explainable Representations of Malware Behavior
Paul Prasse, Jan Brabec, Jan Kohout, Martin Kopp, Lukas Bajer, Tobias Scheffer
Strategic mitigation against wireless attacks on autonomous platoons
Guoxin Sun , Tansu Alpcan, Benjamin I. P. Rubinstein, Seyit Camtepe
DeFraudNet: An End-to-End Weak Supervision Framework to Detect Fraud in Online Food Delivery
Jose Mathew, Meghana Negi, Rutvik Vijjali , Jairaj Sathyanarayana
Time series forecasting with Gaussian Processes needs priors
Giorgio Corani, Alessio Benavoli, Marco Zaffalon
Task Embedding Temporal Convolution Networks for Transfer Learning Problems in Renewable Power Time Series Forecast
Jens~Schreiber , Stephan~Vogt, Bernhard~Sick
Generating Multi-type Temporal Sequences to Mitigate Class-imbalanced Problem
Lun Jiang, Nima Salehi Sadghiani , Zhuo Tao, Andrew Cohen
Recognizing Skeleton-Based Hand Gestures by a Spatio-Temporal Network
Xin Li , Jun Liao, Li Liu
Smurf-based Anti-Money Laundering in Time-Evolving Transaction Networks
Michele Starnini, Charalampos E. Tsourakakis , Maryam Zamanipour, Andr\'e Panisson , Walter Allasia , Marco Fornasiero , Laura Li Puma , Valeria Ricci , Silvia Ronchiadin , Angela Ugrinoska , Marco Varetto , Dario Moncalvo
Spatio-temporal Multi-graph Networks for Demand Forecasting in Online Marketplaces
Ankit Gandhi, Aakanksha, Sivaramakrishnan Kaveri, Vineet Chaoji
The Limit Order Book Recreation Model (LOBRM): An Extended Analysis
Zijian Shi, John Cartlidge
Taking Over the Stock Market: Adversarial Perturbations Against Algorithmic Traders
Elior Nehemya, Yael Mathov , Asaf Shabtai, Yuval Elovici
Continuous-Action Reinforcement Learning for Portfolio Allocation of a Life Insurance Company
Carlo Abrate, Alessio Angius, Gianmarco De Francisci Morales\and Stefano Cozzini\and Francesca Iadanza, Laura Li Puma\and Simone Pavanelli\and Alan Perott, Stefano Pignataro, Silvia Ronchiadin
XRR: Explainable Risk Ranking for Financial Reports
Ting-Wei Lin , Ruei-Yao Sun, Hsuan-Ling Chang\, Chuan-Ju Wang\, Ming-Feng Tsai
Self-disclosure on Twitter during the COVID-19 Pandemic: A Network Perspective
Prasanna Umar, Chandan Akiti, Anna Squicciarini, Sarah Rajtmajer
COVID Edge-Net: Automated COVID-19 Lung Lesion Edge Detection in Chest CT Images
Kang Wang, Yang Zhao, Yong Dou, Dong Wen, Zikai Gao
Improving ambulance dispatching with machine learning and simulation
Nikki~Theeuwes, Geert-Jan~van~Houtum , Yingqian~Zhang
Countrywide Origin-Destination Matrix Prediction and Its Application for COVID-19
Renhe Jiang , Zhaonan Wang, Zekun Cai\and Chuang Yang, Zipei Fan, Tianqi Xia, Go Matsubara, Hiroto Mizuseki, Xuan Song, Ryosuke Shibasaki
Single Model for Influenza Forecasting of Multiple Countries by Multi-task Learning
Taichi Murayama, Shoko Wakamiya, Eiji Aramaki
Automatic Acoustic Mosquito Tagging with Bayesian Neural Networks
Ivan Kiskin, Adam D. Cobb, Marianne Sinka, Kathy Willis, Stephen J. Roberts
Multitask Recalibrated Aggregation Network for Medical Code Prediction
Wei Sun, Shaoxiong Ji, Erik Cambria, Pekka Marttinen
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 Angel Garcia-March, J. Alberto Conejero, Francisco Escolano, Nuria Oliver
Getting Your Package to the Right Place: Supervised Machine Learning for Geolocation
George Forman
Machine Learning Guided Optimization for Demand Responsive Transport Systems
Louis~ZIGRAND, Pegah~ALIZADEH, Emiliano~TRAVERSI, Roberto~WOLFLER~CALVO
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
VAMBC: A Variational Approach for Mobility Behavior Clustering
Mingxuan Yue, Yao-Yi Chiang, Cyrus Shahabi
Multi-Agent Deep Reinforcement Learning with Spatio-Temporal Feature Fusion for Traffic Signal Control
Xin Du, Jiahai Wang, Siyuan Chen, Zhiyue Liu
Monte Carlo Search Algorithms for Network Traffic Engineering
Chen~Dang, Cristina~Bazgan, Tristan~Cazenave, Pierre-Henri~Wuillemin
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
CQNet: A clustering-based quadruplet network for Decentralized Application classification via encrypted traffic
Yu Wang, Gang Xiong\and Chang Liu, Zhen Li\and Mingxin Cuiand, Gaopeng Gou
SPOT: A framework for selection of prototypes using optimal transport
Karthik S. Gurumoorthy, Pratik Jawanpuria, Bamdev Mishra
PuzzleShuffle: Undesirable Feature Learning for Semantic Shift Detection
Yusuke Kanebako, Kazuki Tsukamoto
Enabling Machine Learning on the Edge using SRAM Conserving Efficient Neural Networks Execution Approach
Bharath Sudharsan, Pankesh Patel, John G. Breslin , Muhammad Intizar Ali
AutoML Meets Time Series Regression Design and Analysis of the AutoSeries Challenge
Zhen Xu , Wei-Wei Tu, Isabelle Guyon
Methods for Automatic Machine-Learning Workflow Analysis
Lorenz Wendlinger, Emanuel Berndl, Michael Granitzer
ConCAD: Contrastive Learning-based Cross Attention for Sleep Apnea Detection
Guanjie Huang, Fenglong Ma
DeepPE: Emulating Parameterization in Numerical Weather Forecast Model through Bidirectional Network
Fengyang~Xu, Wencheng~Shi, Yunfei~Du, Zhiguang~Chen, Yutong~Lu
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
Physics Knowledge Discovery via Neural Differential Equation Embedding
Yexiang Xue\and Md Nasim, Maosen Zhang\and Cuncai Fan\and Xinghang Zhang, Anter El-Azab
A Bayesian Convolutional Neural Network for Robust Galaxy Ellipticity Regression
Claire Theobald, Bastien Arcelin , Frédéric Pennerath, Brieuc Conan-Guez , Miguel Couceiro, Amedeo Napoli
Precise Weather Parameter Predictions for Target Regions via Neural Networks
Yihe Zhang, Xu Yuan, Sytske K. Kimball, Eric Rappin, Li Chen, Paul Darby, Tom Johnsten, Lu Peng, Boisy Pitre, David Bourrie, Nian-Feng Tzeng
Action Set Based Policy Optimization for Safe Power Grid Management
Bo Zhou, Hongsheng Zeng, Yuecheng Liu, Kejiao Li, Fan Wang, Hao Tian
Conditional Neural Relational Inference for Interacting Systems
Joao A. Candido Ramos, Lionel Blondé, Stéphane Armand, Alexandros Kalousis
MMNet: Multi-Granularity Multi-Mode Network for Item-Level Share Rate Prediction
Haomin Yu, Mingfei Liang , Ruobing Xie , Zhenlong Sun , Bo Zhang, Leyu Lin
The Joy of Dressing is an Art: Outfit Generation using Self-Attention Bi-LSTM
Manchit Madan , Ankur Chouragade , Sreekanth Vempati
On Inferring a Meaningful Similarity Metric for Customer Behaviour
Sophie van den Berg, Marwan Hassani
Quantifying Explanations of Neural Networks in E-Commerce Based on LRP
Anna Nguyen, Franz Krause, Daniel Hagenmayer, Michael Färber
Balancing Speed and Accuracy in Neural-Enhanced Phonetic Name Matching
Philip Blair, Carmel Eliav , Fiona~Hasanaj , Kfir Bar
Robust Learning for Text Classification with Multi-source Noise Simulation and Hard Example Mining
Guowei Xu, Wenbiao Ding, Weiping Fu, Zhongqin Wu, Zitao Liu
Topic-to-Essay Generation with Comprehensive Knowledge Enhancement
Zhiyue Liu, Jiahai Wang, Zhenghong Li
Analyzing Research Trends in Inorganic Materials Literature Using NLP
Fusataka Kuniyoshi, Jun Ozawa, Makoto Miwa
An optimized NL2SQL system for enterprise data mart
Kaiwen Dong, Kai Lu, Xin Xia, David Cieslak, Nitesh V. Chawla
Time aspect in making an actionable prediction of a conversation breakdown
Piotr~Janiszewski, Mateusz~Lango, Jerzy~Stefanowski
Feature Enhanced Capsule Networks for Robust Automatic Essay Scoring
Arushi Sharma, Anubha Kabra, Rajiv Kapoor
TagRec: Automated Tagging of Questions with Hierarchical Learning Taxonomy
Venktesh V , Mukesh Mohania, Vikram Goya
Checking Robustness of Representations Learned by Deep Neural Networks
Kamil Szyc , Tomasz Walkowiak , Henryk Maciejewski
CHECKER: Detecting Clickbait Thumbnails with Weak Supervision and Co-teaching
Tianyi Xie, Thai Le , Dongwon Lee
Crowdsourcing Evaluation of Saliency-based XAI Methods
Xiaotian Lu, Arseny Tolmachev\and Tatsuya Yamamoto\and Koh Takeuchi, Seiji Okajima\, Tomoyoshi Takebayashi, Koji Maruhashi\and Hisashi Kashima
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
Multi-Task Learning for User Engagement and Adoption in Live Video Streaming Events
Stefanos Antaris, Dimitrios Rafailidis, Romina Arriaza
Explainable Abusive Language Classification Leveraging User and Network Data
Maximilian~Wich, Edoardo~Mosca, Adrian~Gorniak, Johannes~Hingerl, Georg~Groh
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