Accepted Papers

Video presentations of the papers can be found on SlidesLive.

Journal

• CMD: Controllable Matrix Decomposition with Global Optimization for Deep Neural Network Compression
  Haonan Zhang (Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University); Longjun Liu (Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University)*; Hengyi Zhou (Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University); Hongbin Sun (Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University); Nanning Zheng (Xi'an Jiaotong University)
• Towards Interpreting Deep Neural Networks via Layer Behavior Understanding
  Jiezhang Cao (South China University of Technology); Jincheng Li (South China University of Technology); Xiping Hu (Lanzhou University); Xiangmiao Wu (SCUT); Mingkui Tan (South China University of Technology)*
• End-to-End Entity-Aware Neural Machine Translation
  Shufang Xie (Gaoling School of Artificial Intelligence, Renmin University of China)*; Yingce Xia (MSRA); Lijun Wu (Microsoft Research); Yiqing Huang (Tsinghua University); Yang Fan (University of Science and Technology of China); Tao Qin (Microsoft Research Asia)
• Online Strongly Convex Optimization with Unknown Delays
  Yuanyu Wan (Nanjing University); Wei-Wei Tu (4Paradigm Inc.); Lijun Zhang (Nanjing University)*
• On the benefits of representation regularization in invariance based domain generalization
  Changjian Shui (Université Laval)*; Boyu Wang (University of Western Ontario); Christian Gagné (Université Laval)
• Improve Generated Adversarial Imitation Learning with Reward Variance Regularization
  Yi-Feng Zhang (State Key Laboratory of Novel Software Technology, Nanjing University)*; Fan-Ming Luo (Nanjing University); Yang Yu (Nanjing University)
• Bayesian Optimization with Partially Specified Queries
  Shogo Hayashi (NEC Corporation)*; Junya Honda (Kyoto University / RIKEN); Hisashi Kashima (Kyoto University)
• A Study of BERT for Context-Aware Neural Machine Translation
  Xueqing Wu (University of Illinois Urbana-Champaign); Yingce Xia (Microsoft Research Asia)*; Jinhua Zhu (University of Science and Technology of China); Lijun Wu (Microsoft Research); Shufang Xie (Microsoft Research Asia); Tao Qin (Microsoft Research Asia)
• Switching: Understanding the Class-reversed Sampling in Tail Sample Memorization
  Chi Zhang (Xi'an Jiaotong Univiersity)*; Benyi Hu (Xi'an Jiaotong University); Yuhang Liuzhang (Xi'an Jiaotong University); Le Wang (Xi'an Jiaotong University); Li Liu (Inception Institute of Artificial Intelligence); Yuehu Liu (Xi'an Jiaotong University)
• Improving Deep Label Noise Learning with Dual Active Label Correction
  Shao-Yuan Li (Nanjing University of Aeronautics and Astronautics)*; Ye Shi (Nanjing University of Aeronautics and Astronautics); Sheng-Jun Huang (Nanjing University of Aeronautics and Astronautics); Songcan Chen (Nanjing University of Aeronautics and Astronautics)
• The Flowing Nature Matters: Feature Learning from the Control Flow Graph of Source Code for Bug Localization
  Yi-Fan Ma (Nanjing University)*; Ming Li (Nanjing University)
• Exploring the Common Principal Subspace of Deep Features in Neural Networks
  Haoran Liu (Texas A&M University); Haoyi Xiong (Baidu Research)*; Yaqing Wang (Baidu Research); Haozhe An (Baidu Research); Dongrui Wu (Huazhong University of Science and Technology); Dejing Dou (Baidu)
• Worst-case Regret Analysis of Computationally Budgeted Online Kernel Selection
  Junfan Li (Tianjin University); Shizhong Liao (Tianjin University)*
• Multiple Partitions Alignment via Spectral Rotation
  Shudong Huang (Sichuan University)*; Ivor Tsang (University of Technology Sydney); Zenglin Xu (Harbin Institute of Technology); Jiancheng Lv (Sichuan University)
• Improving Kernel Online Learning with a Snapshot Memory
  Trung Le (Monash University)*; Khanh Nguyen (HCMUP); Dinh Phung (Monash University)

Conference

• Vector Transport Free Riemannian LBFGS for Optimization on Symmetric Positive Definite Matrix Manifolds
  Reza Godaz (Ferdowsi University of Mashhad); Benyamin Ghojogh (University of Waterloo); Reshad Hosseini (University of Tehran)*; Reza Monsefi (Ferdowsi University of Mashhad); Fakhri Karray (University of Waterloo); Mark Crowley (University of Waterloo)
• Unsupervised cycle-consistent network for removing susceptibility artifacts in single-shot EPI
  Weida Xie (Wuhan University of Technology)*; 适 陈 (Wuhan University of Technology); Qingjia Bao (Chinese Academy of Sciences); 可文 刘 (Wuhan University of Technology); Zhao Li (State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Wuhan Institute of Physics and Math, Innovation Academy for Precision Measurement Science and Technology. ); Chongxin Bai (Wuhan University of Technology); Otikovs Martins (Weizmann Institute of Science, Rehovot, 76001); Piqiang Li (Wuhan University of Technology); Jie Wang (Chinese Academy of Sciences)
• Hybrid Estimation for Open-Ended Questions with Early-Age Students' Block-Based Programming Answers
  Hao Wu (Zhejiang University City College); Tianyi Chen (Zhejiang University City College); Xianzhe Luo (Zhejiang University City College); Canghong Jin (Zhejiang university city college); Yun Zhang (Zhejiang University City College); Minghui Wu (浙江大学城市学院)*
• Local Aggressive Adversarial Attacks on 3D Point Cloud
  Yiming Sun (Nanjing University of Posts and Telecommunications)*; Feng Chen (Nanjing University of Posts and Telecommunications); Zhiyu Chen (Nanjing University of Posts and Telecommunications); Mingjie Wang (BNU-HKBU United International College)
• The Power of Factorial Powers: New Parameter settings for (Stochastic) Optimization
  Aaron Defazio (Facebook AI Research)*; Robert M Gower (Telecom Paris Tech)
• CTAB-GAN: Effective Table Data Synthesizing
  Zilong Zhao (Delft University of Technology)*; Aditya Kunar (Delft University of Technology); Robert Birke (ABB Research); Lydia Chen (Delft University of Technology)
• Fairness constraint of Fuzzy C-means Clustering improves clustering fairness
  Xia Xu (Southwest University of Science and Technology)*; hui zhang (Southwest University of Science and Technology); Chunming Yang (Southwest University of Science and Technology); xujian zhao (Southwest University of Science and Technology); Bo Li (Southwest University of Science and Technology)
• Meta-Model-Based Meta-Policy Optimization
  Takuya Hiraoka (NEC / AIST / RIKEN)*; Takahisa Imagawa (National Institute of Advanced Industrial Science and Technology); Voot Tangkaratt (RIKEN); Takayuki Osa (Kyushu Institute of Technology / RIKEN); Takashi Onishi (NEC Corporation); Yoshimasa Tsuruoka (The University of Tokyo)
• An Aligned Subgraph Kernel Based on Discrete-Time Quantum Walk
  Kai Liu (National University of Defense Technology); Lulu Wang (National Innovation Institute of Defense Technology)*; Yi Zhang (Central Future Works Technology Co.,Ltd.)
• Encoder-decoder-based image transformation approach for integrating precipitation forecasts
  Hirotaka Hachiya (Wakayama University)*; Yusuke Masumoto (Wakayama University); Yuki Mori (Fujitsu Limited); Naonori Ueda (NTT)
• A Mutual Information Regularization for Adversarial training
  Modeste Atsague (Iowa State University)*; Olukorede J Fakorede (Iowa State University ); Jin Tian (Iowa State University)
• Expressive Neural Voice Cloning
  Paarth Neekhara (UCSD)*; Shehzeen S Hussain (UCSD); Shlomo Dubnov (UC San Diego); Farinaz Koushanfar (UC San Diego); Julian McAuley (University of California, San Diego)
• SPDE-Net: Neural Network based prediction of stabilization parameter for SUPG technique
  Sangeeta Yadav (Indian Institute of Science)*; Sashikumaar Ganesan (Indian Institute of Science)
• DDSAS: Dynamic and Differentiable Space-Architecture Search
  Longxing Yang (Institute of Computing Technology, Chinese Academy of Sciences); Yu Hu (Institute of Computing Technology, Chinese Academy of Sciences)*; Shun Lu (Institute of Computing Technology, Chinese Academy of Sciences); Zihao Sun (Institute of Computing Technology, Chinese Academy of Sciences); Jilin Mei (Institute of Computing Technology, Chinese Academy of Sciences); Yiming Zeng (Tecent ADlab); Zhiping Shi (Capital Normal University); Yinhe Han (Institute of Computing Technology Chinese Academy of Sciences); Xiaowei Li (Institute Of Computing Technology Chinese Academy Of Sciences)
• Uplift Modeling with High Class Imbalance
  Otto E Nyberg (University of Helsinki)*; Tomasz Kuśmierczyk (University of Helsinki); Arto Klami (University of Helsinki)
• Penalty Method for Inversion-Free Deep Bilevel Optimization
  Akshay Mehra (Tulane University)*; Jihun Hamm (Tulane University)
• Temporal Relation based Attentive Prototype Network for Few-shot Action Recognition
  Guangge Wang (Xiamen University); Haihui Ye (Xiamen University); Xiao Wang (Xiamen University); Weirong Ye (Xiamen University); Hanzi Wang (Xiamen University)*
• Building Decision Tree for Imbalanced Classification via Deep Reinforcement Learning
  Guixuan Wen (Chongqing University)*; Kaigui Wu (Chongqing University)
• S2TNet: Spatio-Temporal Transformer Networks for Trajectory Prediction in Autonomous Driving
  Weihuang Chen (Xi'an Jiaotong University); Fangfang Wang (Xi'an Jiaotong University); Hongbin Sun (Xi'an Jiaotong University)*
• DPOQ: Dynamic Precision Onion Quantization
  Bowen Li (Zhejiang University)*; kai huang (Zhejiang University); Siang Chen (Zhejiang University); Dongliang Xiong (Zhejiang University); luc claesen (UHasselt)
• A Causal Approach for Unfair Edge Prioritization and Discrimination Removal
  Pavan Ravishankar (IIT Madras)*; Pranshu Malviya (Indian Institute of Technology, Madras); Balaraman Ravindran (Indian Institute of Technology, Madras)
• Spatial Temporal Enhanced Contrastive and Pretext Learning for Skeleton-based Action Representation
  Yiwen Zhan (Beijing University of Posts and Telecommunications); Yuchen Chen (Beijing University of Posts and Telecommunications)*; Pengfei Ren (Beijing University of Posts and Telecommunications); Haifeng Sun (Beijing university of posts and telecommunications); Jingyu Wang (Beijing University of Posts and Telecommunications); Qi Qi (Beijing University of Posts and Telecommunications); Jianxin Liao (beijing university of posts and telecommunications)
• Max-Utility Based Arm Selection Strategy For Sequential Query Recommendations
  Shameem A Puthiya Parambath (University of Glasgow)*; Christos Anagnostopoulos (University of Glasgow); Roderick Murray-Smith (University of Glasgow); Sean MacAvaney (University of Glasgow); Evangelos Zervas (University of West Attica)
• Multi-task Actor-Critic with Knowledge Transfer via a Shared Critic
  Gengzhi Zhang (ChongQing University); Yaqing Hou (Dalian University of Technology); Liang Feng (Chongqing University, China)*
• Pyramid Correlation based Deep Hough Voting for Visual Object Tracking
  Ying Wang (Beijing Institute of Technology)*; Tingfa Xu (Beijing Institute of Technology); Jianan Li (Beijing Institute of Technology); Shenwang Jiang (Beijing Institute of Technology); Junjie Chen (Beijing Institute of Technology)
• Calibrated Adversarial Training
  Tianjin Huang (Eindhoven University of Technology)*; Vlado Menkovski (Eindhoven University of Technology); Yulong Pei (TU Eindhoven); Mykola Pechenizkiy (TU Eindhoven)
• ASD-Conv: Monocular 3D object detection network based on Asymmetrical Segmentation Depth-aware Convolution
  Xingyuan Yu (Wuhan University); Neng Du (Wuhan University); Ge Gao (Wuhan University)*; Fan Wen (Wuhan University)
• Convolutional Hypercomplex Embeddings for Link Prediction
  Caglar Demir (Paderborn University)*; Diego Moussallem (Paderborn Univerisity); Stefan Heindorf (Paderborn University); Axel-Cyrille Ngonga Ngomo (Paderborn University)
• Hybrid Summarization with Semantic Weighting Reward and Latent Structure Detector
  Mingyang Song (Beijing Jiaotong University)*; Liping Jing (Beijing Jiaotong University); Yi Feng (Beijing Jiaotong University); Zhiwei Sun (Beijing Jiaotong University); Lin Xiao (Beijing Jiaotong University)
• Slice-sampling based 3D Object Classification
  Xiangwen Zhao (Shandong University); Liqun Yang (Florida International University)*; Yijun Yang (Xi’an Jiaotong University); Wei Zeng (Xi'an Jiaotong University); Yao Wang (Shandong University)
• Video Action Recognition with Neural Architecture Search
  Yuanding Zhou (Dalian University of Technology); Baopu Li (BAIDU USA LLC)*; zhihui wang (Dalian University of Technology); Haojie Li (Dalian University of Technology)
• Multi-Branch Network for Cross-Subject EEG-based Emotion Recognition
  Guang Lin (Hangzhou Dianzi University); Li Zhu (Hangzhou Dianzi University); Bin Ren (Hangzhou Dianzi University); YiTeng Hu (Hangzhou Dianzi University); Jianhai Zhang (Hangzhou Dianzi University)*
• Domain Adaptive YOLO for One-Stage Cross-Domain Detection
  Shizhao Zhang (Shanghai Jiao Tong University); Hongya Tuo (Shanghai Jiaotong University); Jian Hu (Shanghai Jiaotong University); Zhongliang Jing (Shanghai Jiaotong University)*
• Improving Hashing Algorithms for Similarity Search via MLE and the Control Variates Trick
  Keegan Kang (SUTD)*; Sergey Kushnarev (JHU); Weipin Wong (SUTD); Rameshwar Pratap Yadav (IIT Mandi); Haikal Yeo (Ministry of Education); Yijia Chen (Singapore University of Technology and Design)
• Feature Convolutional Networks
  He Hu (Renmin University of China)*
• Multi-factor Memory Attentive Model for Knowledge Tracing
  Liu Congjie (Liaoning University); Xiaoguang Li (Liaoning University)*
• Asymptotically Exact and Fast Gaussian Copula Models for Imputation of Mixed Data Types
  Benjamin Christoffersen (KTH)*; Mark Clements (Karolinska Institutet); Keith Humphreys (Karolinska Institutet); Hedvig Kjellström (KTH Royal Institute of Technology)
• Greedy Search Algorithm for Mixed Precision in Post-Training Quantization of Convolutional Neural Network Inspired by Submodular Optimization
  Satoki Tsuji (Fujitsu Labratories Ltd.)*; Hiroshi Kawaguchi (Kobe University); Atsuki Inoue (Kobe University); Yasufumi Sakai (Fujitsu Laboratories Ltd.); Fuyuka Yamada (Fujitsu Laboratories Ltd.)
• ExNN-SMOTE: Extended Natural Neighbors Based SMOTE to Deal with Imbalanced Data
  Hongjiao Guan (Qilu University of Technology (Shandong Academy of Sciences))*; Yingtao Zhang (Harbin Institute of Technology); Xianglong Tang (Harbin Institute of Technology); Bin Ma (Qilu University of Technology)
• Augmenting Imbalanced Time-series Data via Adversarial Perturbation in Latent Space
  Beomsoo Kim (Korea Advanced Institute of Science and Technology)*; Jaegul Choo (Korea Advanced Institute of Science and Technology); Jang-Ho Choi (Electronics and Telecommunications Research Institute)
• Dynamic Popularity-Aware Contrastive Learning for Recommendation
  Fangquan Lin (Alibaba Group); Wei Jiang (Alibaba Group)*; Jihai Zhang (Alibaba Group); Cheng Yang (Alibaba Group)
• Ensembling With a Fixed Parameter Budget: When Does It Help and Why?
  Didan Deng (Hong Kong University of Science and Technology)*; Bertram E Shi (ECE Department of Hong Kong University of Science and Technology)
• Lifelong Learning with Sketched Structural Regularization
  Haoran Li (Johns Hopkins University); Aditya R Krishnan (Johns Hopkins University); Jingfeng Wu (Johns Hopkins University); Soheil Kolouri (Vanderbilt University); Praveen Pilly (HRL Laboratories LLC); Vladimir Braverman (Johns Hopkins University)*
• Transfer Learning with Adaptive Online TrAdaBoost for Data Streams
  Ocean Wu (The University of Auckland)*; Yun Sing Koh (The University of Auckland, New Zealand); Gillian Dobbie ("Univ. of Auckland, New Zealand"); Thomas Lacombe (The University of Auckland)
• Bridging Code-Text Representation Gap using Explanation
  Hojae Han (Seoul National University)*; Youngwon Lee (Seoul National University); Minsoo Kim (Yonsei University); Seung-won Hwang (Seoul National University)
• ContriQ: Ally-Focused Cooperation and Enemy-Concentrated Confrontation in Multi-Agent Reinforcement Learning
  Chenran Zhao (National University of Defense Technology); Dianxi Shi (National Innovation Institute of Defense Technology;Tianjin Artificial Intelligence Innovation Center)*; Yaowen Zhang (National Innovation Institute of Defense Technology (NIIDT)); Huanhuan Yang (National University of Defense Technology); Shaowu Yang (National University of Defense Technology); Yongjun Zhang (National Innovation Institute of Defense Technology)
• Expert advice problem with noisy low rank loss
  Yaxiong Liu (Kyushu University)*; Xuanke Jiang (Kyushu university); Kohei Hatano (Kyushu University / RIKEN AIP); Eiji Takimoto (Kyushu University)
• An online semi-definite programming with a generalised log-determinant regularizer and its applications
  Yaxiong Liu (Kyushu University)*; Ken-ichiro Moridomi (So-net Media Networks); Kohei Hatano (Kyushu University / RIKEN AIP); Eiji Takimoto (Kyushu University)
• Lifelong Learning with Branching Experts
  Yi-Shan Wu (Academia Sinica); Yi-Te Hong (Academia Sinica)*; Chi-Jen Lu (Academia Sinica)
• Physics-inspired Learning for Structure-Aware Texture-Sensitive Underwater Image Enhancement
  Xinwei Xue (Dalian University of Technology)*; Zexuan Li (Dalian University of Technology ); Long Ma (Dalian University of Technology); Risheng Liu (Dalian University of Technology); Xin Fan (Dalian University of Technology)
• Robust Domain Randomised Reinforcement Learning through Peer-to-Peer Distillation
  Chenyang Zhao (University of Edinburgh)*; Timothy Hospedales (Edinburgh University)
• Learning 3-opt heuristics for traveling salesman problem via deep reinforcement learning
  Jingyan Sui (Institute of Computing Technology, Chinese Academy of Sciences)*; Shi-Zhe Ding (Institute of Computing Technology, Chinese Academy of Sciences); Ruizhi Liu (Institute of Computing Technology, Chinese Academy of Sciences); Liming Xu (Institute of Computing Technology, Chinese Academy of Sciences); Dongbo Bu (Insitute of Computing Technology, Chinese Academy of Sciences)
• Time-Constrained Multi-Agent Path Finding in Non-Lattice Graphs with Deep Reinforcement Learning
  Marijn van Knippenberg (Eindhoven University of Technology)*; Mike Holenderski (Einhoven University of Technology); Vlado Menkovski (Eindhoven University of Technology)
• Metric Learning for comparison of HMMs using Graph Neural Networks
  rajan kumar soni (Indian Institute of technology, madras)*; Karthick Seshadri (NIT Andhra Pradesh); Balaraman Ravindran (Indian Institute of Technology, Madras)
• Layer-Wise Neural Network Compression via Layer Fusion
  James T O' Neill (University of Liverpool)*; Aram Galstyan (USC Information Sciences Institute); Greg Ver Steeg (USC Information Sciences Institute)
• Bayesian neural network unit priors and generalized Weibull-tail property
  Mariia Vladimirova (Inria Grenoble Rhone-Alpes)*; Julyan Arbel (Inria Grenoble Rhone-Alpes); Stephane Girard (INRIA)
• A Partial Label Metric Learning Algorithm for Class Imbalanced Data
  Wenpeng Liu (Dalian Minzu University); Li Wang (Dalian Minzu University); Jie Chen (Dalian Minzu University); Yu Zhou (Dalian Minzu University); ruirui Zheng (Dalian Minzu University); Jianjun He (Dalian Minzu University)*
• Scaling Average-Linkage via Sparse Cluster Embeddings
  Thomas Lavastida (Carnegie Mellon University)*; Kefu Lu (Washington and Lee University); Benjamin Moseley (Carnegie Mellon University); Yuyan Wang (Carnegie Mellon University)
• Multi-scale Salient Instance Segmentation based on Encoder-Decoder
  Houru Chen (North China University of Science and Technology); Caijuan Shi (North China University of Science and Technology)*; Wei Li (North China University of Science and Technology); Changyu Duan (North China University of Science and Technology); Jinwei Yan ( North China University of Science and Technology)
• A Two-Stage Training Framework with Feature-Label Matching Mechanism for Learning from Label Proportions
  Haoran Yang (The Chinese University of Hong Kong)*; Wanjing Zhang (Central University of Finance and Economics ); Wai Lam (The Chinese University of Hong Kong)
• K2-GNN: Multiple Users' Comments Integration with Probabilistic K-Hop Knowledge Graph Neural Networks
  Huixin Zhan (Texas Tech University); Kun Zhang (XAVIER UNIVERSITY OF LOUISIANA); Chenyi Hu (University of Central Arkansas); Victor S. Sheng (Texas Tech University)*
• Learn to Predict Vertical Track Irregularity with Extremely Imbalanced Data
  Yutao Chen (Beijing University of Posts and Telecommunications)*; Yu Zhang (China Academy of Railway Sciences Corporation Limited); Fei Yang (China Academy of Railway Sciences Corporation Limited)
• Semi-Open Attribute Extraction from Chinese Functional Description Text
  li zhang (UCI); Yanzeng Li (Peking University)*; Ruoyu Zhang (Peking University); Wenjie Li (Wangxuan Institute of Computer Technology, Peking University)
• Relation Also Need Attention: Integrating Relation Information Into Image Captioning
  Tianyu Chen (Guangxi Normal University); Zhixin Li (Guangxi Normal University)*; tiantao xian (Guangxi Normal University); Canlong Zhang (Guangxi Normal University); Ma Huifang (Northwest Normal University)
• Learning to Switch Optimizers for Quadratic Programming
  Grant E Getzelman (Argonne National Lab)*; Prasanna Balaprakash (Argonne National Laboratory)
• Perturbing Eigenvalues with Residual Learning in Graph Convolutional Neural Networks
  Shibo Yao (New Jersey Institute of Technology)*; Dantong Yu (New Jersey Institute of Technology); XIANGMIN JIAO (Stony Brook University)
• Understanding How Over-Parametrization Leads to Acceleration: A case of learning a single teacher neuron
  Jun-Kun Wang (Yale University)*; Jacob D Abernethy (Georgia Institute of Technolog)
• h-DBSCAN: A simple fast DBSCAN algorithm for big data
  邵源 翁 (华侨大学)*; Jin Gou (College of Computer Science and Technology, Huaqiao University, Xiamen, China)
• On the Convex Combination of Determinantal Point Processes
  Tatsuya Matsuoka (NEC Corporation)*; Naoto Ohsaka (NEC Corporation); Akihiro Yabe (Fanfare Inc.)
• BRAC+: Improved Behavior Regularized Actor Critic for Offline Reinforcement Learning
  Chi Zhang (University of Southern California)*; Sanmukh Rao Kuppannagari (University of Southern California); Viktor K Prasanna (Unversity of Southern California)
• Cautious Actor-Critic
  lingwei zhu (NAIST)*; Toshinori Kitamura (NAIST); Takamitsu Matsubara (NAIST)
• Quaternion Graph Neural Networks
  Dai Quoc Nguyen (Monash University)*; Tu Dinh Nguyen (VinAI Research); Dinh Phung (Monash University)
• DAGSurv: Directed Ayclic Graph Based Survival Analysis Using Deep Neural Networks
  Rahul Kukreja (IIITD); Ansh Kumar Sharma (IIITD); Ranjitha Prasad (IIIT Delhi)*; Shilpa Rao (IIIT Guwahati)
• Dynamic Coordination Graph for Cooperative Multi-Agent Reinforcement Learning
  Chapman Siu (University of Technology Sydney)*; Jason Traish (University of Technology Sydney ); Richard Yi Da Xu (University of Technology, Sydney)
• An Optimistic Acceleration of AMSGrad for Nonconvex Optimization
  Jun-Kun Wang (Yale University); Xiaoyun Li (Baidu Research); Belhal Karimi (Baidu Research)*; Ping Li (Baidu)
• Sinusoidal Flow: A Fast Invertible Autoregressive Flow
  Yumou Wei (University of Michigan)*
• Iterative Deep Model Compression and Acceleration in the Frequency Domain
  Yao Zeng (Nanjing University); Xusheng Liu (State Grid Customer Service Center ); Lintan Sun (State Grid Customer Service Center ); Wenzhong Li (Nanjing University)*; Yuchu Fang (Nanjing University); Qingning Lu (Nanjing University); Sanglu Lu (NJU)
• CTS2: Time Series Smoothing with Constrained Reinforcement Learning
  Yongshuai Liu (University of California, Davis)*; Xin Liu (University of California)
• Open Images V5 Text Annotation and Yet Another Mask Text Spotter
  Ilya Krylov (Intel)*; Sergei Nosov (Intel); Vladislav Sovrasov (Lobachevsky State University of Nizhny Novgorod)
• Language Representations for Generalization in Reinforcement Learning
  Nikolaj S Goodger (Federation University Australia)*; Peter Vamplew (Federation University); Cameron Foale (Federation University); Richard Dazeley (Deakin University)
• Solving Machine Learning Problems
  Sunny Tran (MIT)*; Pranav S Krishna (Massachusetts Institute of Technology); Ishan Pakuwal (MIT); Prabhakar Kafle (MIT); Nikhil Singh (MIT Media Lab); Jayson Lynch (University of Waterloo); Iddo Drori (MIT)
• Pedestrian Wind Factor Estimation in Complex Urban Environments
  Sarah Mokhtar (MIT)*; Matthew Beveridge (Massachusetts Institute of Technology); Yumeng Cao (MIT); Iddo Drori (MIT)
• Bayesian Inference for Optimal Transport with Stochastic Cost
  Anton Mallasto (Aalto University)*; Markus Heinonen (Aalto University ); Samuel Kaski (Aalto University and University of Manchester)
• QActor: Active Learning on Noisy Labels
  Taraneh Younesian (TU Delft)*; Zilong Zhao (Delft University of Technology); Amirmasoud Ghiassi (TU Delft); Robert Birke (ABB Research); Lydia Chen (TU Delft)
• Contrastive Neural Processes for Self-Supervised Learning
  Konstantinos Kallidromitis (Panasonic)*; Denis A Gudovskiy (Panasonic); Kazuki Kozuka (Panasonic Corporation); Iku Ohama (Panasonic); Luca Rigazio (Panasonic)
• Generating Deep Networks Explanations with Robust Attribution Alignment
  Guohang Zeng (The University of Melbourne)*; Yousef Kowsar (The University of Melbourne); Sarah Erfani (University of Melbourne); James Bailey (THE UNIVERSITY OF MELBOURNE)
• Improving Gaussian mixture latent variable model convergence with Optimal Transport
  Benoit Gaujac (UCL)*; Ilya Feige (Faculty); David Barber (UCL)
• Cross-structural Factor-topic Model: Document Analysis with Sophisticated Covariates
  Chien Lu (Tampere University)*; Jaakko Peltonen (Tampere University); Timo Nummenmaa (Tampere University); Jyrki Nummenmaa (Tampere University); Kalervo järvelin (Tampere University)
• Beyond L_p clipping: Equalization based Psychoacoustic Attacks against ASRs
  Hadi Abdullah (University of Florida)*; Muhammad Sajidur Rahman (University of Florida); Christian Peeters (University of Florida); Cassidy L Gibson (University of Florida); Washington Garcia (University of Florida); Vincent Bindschaedler (University of Florida); Thomas Shrimpton (University of Florida); Patrick G Traynor (University of Florida)
• Maximization of Monotone k-Submodular Functions with Bounded Curvature and Non-k-Submodular Functions
  Tatsuya Matsuoka (NEC Corporation)*; Naoto Ohsaka (NEC Corporation)
• Speaker Diarization as a Fully Online Bandit Learning Problem in MiniVox
  Baihan Lin (Columbia University)*; Xinxin Zhang (University of Washington)
• Skew-symmetrically perturbed gradient flow for convex optimization
  Futoshi Futami (NTT)*; Tomoharu Iwata (NTT); Naonori Ueda (NTT); Ikko Yamane (Université Paris Dauphine - PSL/RIKEN)
• Scalable gradient matching based on state space Gaussian Processes
  Futoshi Futami (NTT)*
• Robust Regression for Monocular Depth Estimation
  Julian Lienen (Paderborn University)*; Nils Nommensen (TIB - Leibniz Information Center for Science and Technology); Ralph Ewerth (TIB - Leibniz Information Center for Science and Technology); Eyke Hüllermeier (University of Munich)
• Fast Rate Learning in Stochastic First Price Bidding
  Juliette Achddou (ENS Paris)*; Olivier Cappé (ENS Paris); Aurélien Garivier (ENS Lyon)
• Multi-view Latent Subspace Clustering based on both Global and Local Structure
  honghan zhou (nanjing normal university); Weiling Cai (Nanjing Normal University)*; LE Xu ( Nanjing Normal University)
• Hierarchical Semantic Segmentation using Psychometric Learning
  Lu Yin (Eindhoven University of Technology)*; Vlado Menkovski (Eindhoven University of Technology); Shiwei Liu (Eindhoven University of Technology); Mykola Pechenizkiy (TU Eindhoven)
• Bias-Tolerant Fair Classification
  Yixuan Zhang ( University of Technology Sydney)*; Feng Zhou (Tsinghua University); Zhidong Li (UTS); Yang Wang (UTS); Fang Chen (UTS)
• Geometric Value Iteration: Dynamic Error-Aware KL Regularization for Reinforcement Learning
  Toshinori Kitamura (NAIST)*; lingwei zhu (NAIST); Takamitsu Matsubara (NAIST)
• Collaborative Novelty Detection for Distributed Data by a Probabilistic Method
  Akira Imakura (University of Tsukuba)*; Xiucai Ye (University of Tsukuba); Tetsuya Sakurai (University of Tsukuba)
• Efficient Coreset Constructions via Sensitivity Sampling
  Vladimir Braverman (Johns Hopkins University); Dan Feldman (The University of Haifa); Harry Lang (Johns Hopkins University); Adiel Statman (The University of Haifa); Samson Zhou (Carnegie Mellon University)*
• Neural Graph Filtering for Context-aware Recommendation
  Chuanyan Zhang (Shandong University)*; Xiaoguang Hong (Shandong University)
• Modeling Risky Choices in Unknown Environments
  Ville Tanskanen (University of Helsinki)*; Chang Rajani (University of Helsinki); Homayun Afrabandpey (Nokia); Aini Putkonen (Aalto University); Aurélien Nioche (Aalto University); Arto Klami (University of Helsinki)
• Deep Structural Contrastive Subspace Clustering
  Bo Peng (The University of Queensland); Wenjie Zhu (China Jiliang University)*
• Revisiting Weight Initialization of Deep Neural Networks
  Maciej Skorski (University of Luxembourg)*; Martin Theobald (University of Luxembourg); Alessandro. Temperoni (University of Luxembourg)
• Robust Model-based Reinforcement Learning for Autonomous Greenhouse Control
  Wanpeng Zhang (Tsinghua University)*; Xiaoyan Cao (Xiamen University); Yao Yao (Tsinghua-Berkeley Shenzhen Institute, Tsinghua Shenzhen International Graduate School, Tsinghua University); Zhicheng An (Tsinghua-Berkeley Shenzhen Institute, Tsinghua Shenzhen International Graduate School, Tsinghua University); Dijun Luo (Tencent); Xi Xiao (Tsinghua University)
• PFedAtt: Attention-based Personalized Federated Learning on Heterogeneous Clients
  Zichen Ma (The Chinese University of Hong Kong, Shenzhen)*; Yu Lu (The Chinese University of Hong Kong, Shenzhen); Wenye Li (The Chinese University of Hong Kong, Shenzhen); Jinfeng Yi (JD AI Research); Shuguang Cui (The Chinese University of Hong Kong, Shenzhen )
• Multi-stream based Marked Point Process
  Sujun Hong (Graduate School of System Engineering, Wakayama University)*; Hirotaka Hachiya (Wakayama University)
• Bayesian Latent Factor Model for Higher-order Data
  Zerui Tao (Tokyo University of Agriculture and Technology)*; Xuyang ZHAO (Tokyo University of Agriculture and Technology); Toshihisa Tanaka (Tokyo University of Agriculture and Technology); Qibin Zhao (RIKEN AIP)
• Exposing Cyber-Physical System Weaknesses by Implicitly Learning their Underlying Models
  Napoleon Costilla-Enriquez (Arizona State University)*; Yang Weng (Arizona State University)
• NAS-HPO-Bench-II: A Benchmark Dataset on Joint Optimization of Convolutional Neural Network Architecture and Training Hyperparameters
  Yoichi Hirose (Yokohama National University)*; Nozomu Yoshinari (Yokohama National University); Shinichi Shirakawa (Yokohama National University)
• Learning Maximum Margin Markov Networks from examples with missing labels
  Vojtech Franc (Center for Machine Perception)*; Andrii Yermakov (Czech Technical University in Prague)
• Regularized Mutual Learning for Personalized Federated Learning
  Ruihong Yang (Southern University of Science and Technology)*; Junchao Tian (Southern University of Science and Technology); Yu Zhang (Southern University of Science and Technology)
• Bayesian nonparametric model for arbitrary cubic partitioning
  Masahiro Nakano (NTT communication science laboratories)*; Yasuhiro Fujiwara (NTT Communication Science Laboratories); Akisato Kimura (NTT Communication Science Laboratories); Takeshi Yamada (NTT Communication Science Laboratories); Naonori Ueda (NTT Communication Science Labs.)