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13th ACML 2021: Virtual Event
- Vineeth N. Balasubramanian, Ivor W. Tsang
:
Asian Conference on Machine Learning, ACML 2021, 17-19 November 2021, Virtual Event. Proceedings of Machine Learning Research 157, PMLR 2021 - Preface / Frontmatter. i-xiii
- Reza Godaz, Benyamin Ghojogh, Reshad Hosseini, Reza Monsefi, Fakhri Karray, Mark Crowley:
Vector Transport Free Riemannian LBFGS for Optimization on Symmetric Positive Definite Matrix Manifolds. 1-16 - Jun-Kun Wang, Jacob D. Abernethy:
Understanding How Over-Parametrization Leads to Acceleration: A case of learning a single teacher neuron. 17-32 - Hao Wu, Tianyi Chen, Xianzhe Luo, Canghong Jin, Yun Zhang, Minghui Wu:
Hybrid Estimation for Open-Ended Questions with Early-Age Students' Block-Based Programming Answers. 33-48 - Aaron Defazio, Robert M. Gower:
The Power of Factorial Powers: New Parameter settings for (Stochastic) Optimization. 49-64 - Yiming Sun, Feng Chen, Zhiyu Chen, Mingjie Wang:
Local Aggressive Adversarial Attacks on 3D Point Cloud. 65-80 - Shaoyuan Weng, Jin Gou, Zongwen Fan:
h-DBSCAN: A simple fast DBSCAN algorithm for big data. 81-96 - Zilong Zhao
CTAB-GAN: Effective Table Data Synthesizing. 97-112 - Xia Xu, Hui Zhang, Chunming Yang, Xujian Zhao, Bo Li:
Fairness constraint of Fuzzy C-means Clustering improves clustering fairness. 113-128 - Takuya Hiraoka, Takahisa Imagawa, Voot Tangkaratt, Takayuki Osa, Takashi Onishi, Yoshimasa Tsuruoka:
Meta-Model-Based Meta-Policy Optimization. 129-144 - Kai Liu, Lulu Wang, Yi Zhang:
An Aligned Subgraph Kernel Based on Discrete-Time Quantum Walk. 145-157 - Tatsuya Matsuoka, Naoto Ohsaka, Akihiro Yabe:
On the Convex Combination of Determinantal Point Processes. 158-173 - Hirotaka Hachiya, Yusuke Masumoto, Yuki Mori, Naonori Ueda:
Encoder-decoder-based image transformation approach for integrating precipitation forecasts. 174-188 - Modeste Atsague, Olukorede Fakorede, Jin Tian:
A Mutual Information Regularization for Adversarial Training. 188-203 - Chi Zhang, Sanmukh R. Kuppannagari, Viktor K. Prasanna:
BRAC+: Improved Behavior Regularized Actor Critic for Offline Reinforcement Learning. 204-219 - Lingwei Zhu, Toshinori Kitamura, Takamitsu Matsubara:
Cautious Actor-Critic. 220-235 - Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Q. Phung:
Quaternion Graph Neural Networks. 236-251 - Paarth Neekhara, Shehzeen Hussain, Shlomo Dubnov, Farinaz Koushanfar, Julian J. McAuley:
Expressive Neural Voice Cloning. 252-267 - Sangeeta Yadav
SPDE-Net: Neural Network based prediction of stabilization parameter for SUPG technique. 268-283 - Longxing Yang, Yu Hu, Shun Lu, Zihao Sun, Jilin Mei, Yiming Zeng, Zhiping Shi, Yinhe Han, Xiaowei Li:
DDSAS: Dynamic and Differentiable Space-Architecture Search. 284-299 - Yumou Wei:
Sinusoidal Flow: A Fast Invertible Autoregressive Flow. 299-314 - Otto Nyberg, Tomasz Kusmierczyk, Arto Klami:
Uplift Modeling with High Class Imbalance. 315-330 - Yao Zeng, Xusheng Liu, Lintan Sun, Wenzhong Li, Yuchu Fang, Sanglu Lu:
Iterative Deep Model Compression and Acceleration in the Frequency Domain. 331-346 - Akshay Mehra, Jihun Hamm:
Penalty Method for Inversion-Free Deep Bilevel Optimization. 347-362 - Yongshuai Liu, Xin Liu:
CTS2: Time Series Smoothing with Constrained Reinforcement Learning. 363-378 - Ilya Krylov, Sergei Nosov, Vladislav Sovrasov:
Open Images V5 Text Annotation and Yet Another Mask Text Spotter. 379-389 - Goodger Nikolaj, Peter Vamplew, Cameron Foale, Richard Dazeley:
Language Representations for Generalization in Reinforcement Learning. 390-405 - Guangge Wang, Haihui Ye, Xiao Wang, Weirong Ye, Hanzi Wang:
Temporal Relation based Attentive Prototype Network for Few-shot Action Recognition. 406-421 - Jun-Kun Wang, Xiaoyun Li, Belhal Karimi, Ping Li:
An Optimistic Acceleration of AMSGrad for Nonconvex Optimization. 422-437 - Chapman Siu, Jason Traish, Richard Yi Da Xu:
Dynamic Coordination Graph for Cooperative Multi-Agent Reinforcement Learning. 438-453 - Weihuang Chen, Fangfang Wang, Hongbin Sun:
S2TNet: Spatio-Temporal Transformer Networks for Trajectory Prediction in Autonomous Driving. 454-469 - Sunny Tran, Pranav Krishna, Ishan Pakuwal, Prabhakar Kafle, Nikhil Singh
Solving Machine Learning Problems. 470-485 - Sarah Mokhtar, Matthew Beveridge, Yumeng Melody Cao, Iddo Drori:
Pedestrian Wind Factor Estimation in Complex Urban Environments. 486-501 - Bowen Li, Kai Huang, Siang Chen, Dongliang Xiong, Luc Claesen:
DPOQ: Dynamic Precision Onion Quantization. 502-517 - Pavan Ravishankar, Pranshu Malviya, Balaraman Ravindran:
A Causal Approach for Unfair Edge Prioritization and Discrimination Removal. 518-533 - Yiwen Zhan, Yuchen Chen, Pengfei Ren, Haifeng Sun, Jingyu Wang
Spatial Temporal Enhanced Contrastive and Pretext Learning for Skeleton-based Action Representation. 534-547 - Taraneh Younesian, Zilong Zhao, Amirmasoud Ghiassi, Robert Birke, Lydia Y. Chen:
QActor: Active Learning on Noisy Labels. 548-563 - Shameem A. Puthiya Parambath, Christos Anagnostopoulos, Roderick Murray-Smith, Sean MacAvaney, Evangelos Zervas:
Max-Utility Based Arm Selection Strategy For Sequential Query Recommendations. 564-579 - Gengzhi Zhang, Liang Feng, Yaqing Hou:
Multi-task Actor-Critic with Knowledge Transfer via a Shared Critic. 580-593 - Konstantinos Kallidromitis, Denis A. Gudovskiy, Kazuki Kozuka, Ohama Iku, Luca Rigazio:
Contrastive Neural Processes for Self-Supervised Learning. 594-609 - Ying Wang, Tingfa Xu, Shenwang Jiang
Pyramid Correlation based Deep Hough Voting for Visual Object Tracking. 610-625 - Tianjin Huang, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy:
calibrated adversarial training. 626-641 - Xingyuan Yu, Neng Du, Ge Gao, Fan Wen:
ASD-Conv: Monocular 3D object detection network based on Asymmetrical Segmentation Depth-aware Convolution. 642-655 - Caglar Demir, Diego Moussallem, Stefan Heindorf
Convolutional Hypercomplex Embeddings for Link Prediction. 656-671 - Hadi Abdullah, Muhammad Sajidur Rahman, Christian Peeters, Cassidy Gibson, Washington Garcia, Vincent Bindschaedler, Thomas Shrimpton, Patrick Traynor:
Beyond Lp Clipping: Equalization based Psychoacoustic Attacks against ASRs. 672-688 - Xiangwen Zhao, Yi-Jun Yang, Wei Zeng, Liqun Yang, Yao Wang:
Slice-sampling based 3D Object Classification. 689-704 - Guang Lin, Li Zhu, Bin Ren, Yiteng Hu, Jianhai Zhang:
Multi-Branch Network for Cross-Subject EEG-based Emotion Recognition. 705-720 - Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Ikko Yamane:
Skew-symmetrically perturbed gradient flow for convex optimization. 721-736 - Benoit Gaujac, Ilya Feige, David Barber:
Improving Gaussian mixture latent variable model convergence with Optimal Transport. 737-752 - Guohang Zeng, Yousef Kowsar, Sarah M. Erfani, James Bailey:
Generating Deep Networks Explanations with Robust Attribution Alignment. 753-768 - Futoshi Futami:
Scalable gradient matching based on state space Gaussian Processes. 769-784 - Shizhao Zhang, Hongya Tuo, Jian Hu, Zhongliang Jing:
Domain Adaptive YOLO for One-Stage Cross-Domain Detection. 785-797 - Lu Yin, Vlado Menkovski, Shiwei Liu, Mykola Pechenizkiy:
Hierarchical Semantic Segmentation using Psychometric Learning. 798-813 - Keegan Kang
Improving Hashing Algorithms for Similarity Search \textitvia MLE and the Control Variates Trick. 814-829 - He Hu:
Feature Convolutional Networks. 830-839 - Yixuan Zhang, Feng Zhou, Zhidong Li, Yang Wang, Fang Chen:
Bias-tolerant Fair Classification. 840-855 - Congjie Liu, Xiaoguang Li:
Multi-factor Memory Attentive Model for Knowledge Tracing. 856-869 - Benjamin Christoffersen, Mark Clements, Keith Humphreys, Hedvig Kjellström:
Asymptotically Exact and Fast Gaussian Copula Models for Imputation of Mixed Data Types. 870-885 - Satoki Tsuji, Hiroshi Kawaguchi, Atsuki Inoue, Yasufumi Sakai, Fuyuka Yamada:
Greedy Search Algorithm for Mixed Precision in Post-Training Quantization of Convolutional Neural Network Inspired by Submodular Optimization. 886-901 - Hongjiao Guan, Bin Ma, Yingtao Zhang, Xianglong Tang:
ExNN-SMOTE: Extended Natural Neighbors Based SMOTE to Deal with Imbalanced Data. 902-917 - Toshinori Kitamura, Lingwei Zhu, Takamitsu Matsubara:
Geometric Value Iteration: Dynamic Error-Aware KL Regularization for Reinforcement Learning. 918-931 - Akira Imakura, Xiucai Ye, Tetsuya Sakurai:
Collaborative Novelty Detection for Distributed Data by a Probabilistic Method. 932-947 - Vladimir Braverman, Dan Feldman, Harry Lang, Adiel Statman, Samson Zhou:
Efficient Coreset Constructions via Sensitivity Sampling. 948-963 - Fangquan Lin, Wei Jiang
Dynamic Popularity-Aware Contrastive Learning for Recommendation. 964-968 - Chuanyan Zhang, Xiaoguang Hong:
Neural Graph Filtering for Context-aware Recommendation. 969-984 - Haoran Li, Aditya Krishnan, Jingfeng Wu, Soheil Kolouri, Praveen K. Pilly, Vladimir Braverman:
Lifelong Learning with Sketched Structural Regularization. 985-1000 - Julian Lienen, Nils Nommensen, Ralph Ewerth, Eyke Hüllermeier:
Robust Regression for Monocular Depth Estimation. 1001-1016 - Ocean Wu, Yun Sing Koh, Gillian Dobbie, Thomas Lacombe
Transfer Learning with Adaptive Online TrAdaBoost for Data Streams. 1017-1032 - Hojae Han, Youngwon Lee, Minsoo Kim, Seung-won Hwang:
Bridging Code-Text Representation Gap using Explanation. 1033-1048 - Chenran Zhao, Dianxi Shi, Yaowen Zhang, Huanhuan Yang, Shaowu Yang, Yongjun Zhang:
ContriQ: Ally-Focused Cooperation and Enemy-Concentrated Confrontation in Multi-Agent Reinforcement Learning. 1049-1064 - Ansh Kumar Sharma
DAGSurv: Directed Ayclic Graph Based Survival Analysis Using Deep Neural Networks. 1065-1080 - Ville Tanskanen, Chang Rajani, Homayun Afrabandpey, Aini Putkonen, Aurélien Nioche
Modeling Risky Choices in Unknown Environments. 1081-1096 - Yaxiong Liu, Xuanke Jiang, Kohei Hatano, Eiji Takimoto:
Expert advice problem with noisy low rank loss. 1097-1112 - Yaxiong Liu, Ken-ichiro Moridomi, Kohei Hatano, Eiji Takimoto:
An online semi-definite programming with a generalised log-determinant regularizer and its applications. 1113-1128 - Chien Lu, Jaakko Peltonen, Timo Nummenmaa, Jyrki Nummenmaa, Kalervo Jäarvelin:
Cross-structural Factor-topic Model: Document Analysis with Sophisticated Covariates. 1129-1144 - Bo Peng, Wenjie Zhu:
Deep Structural Contrastive Subspace Clustering. 1145-1160 - Yi-Shan Wu, Yi-Te Hong, Chi-Jen Lu:
Lifelong Learning with Branching Experts. 1161-1175 - Didan Deng, Bertram Emil Shi:
Ensembling With a Fixed Parameter Budget: When Does It Help and Why? 1176-1191 - Maciej Skorski
Revisiting Weight Initialization of Deep Neural Networks. 1192-1207 - Wanpeng Zhang, Xiaoyan Cao, Yao Yao, Zhicheng An, Xi Xiao, Dijun Luo:
Robust Model-based Reinforcement Learning for Autonomous Greenhouse Control. 1208-1223 - Xinwei Xue, Zexuan Li, Long Ma, Risheng Liu, Xin Fan:
Physics-inspired Learning for Structure-Aware Texture-Sensitive Underwater Image Enhancement. 1224-1236 - Chenyang Zhao
Robust Domain Randomised Reinforcement Learning through Peer-to-Peer Distillation. 1237-1252 - Zichen Ma, Yu Lu, Wenye Li, Jinfeng Yi, Shuguang Cui:
PFedAtt: Attention-based Personalized Federated Learning on Heterogeneous Clients. 1253-1268 - Sujun Hong, Hirotaka Hachiya:
Multi-stream based marked point process. 1269-1284 - Zerui Tao, Xuyang Zhao, Toshihisa Tanaka, Qibin Zhao:
Bayesian Latent Factor Model for Higher-order Data. 1285-1300 - Jingyan Sui, Shizhe Ding, Ruizhi Liu, Liming Xu, Dongbo Bu:
Learning 3-opt heuristics for traveling salesman problem via deep reinforcement learning. 1301-1316 - Marijn van Knippenberg, Mike Holenderski, Vlado Menkovski:
Time-Constrained Multi-Agent Path Finding in Non-Lattice Graphs with Deep Reinforcement Learning. 1317-1332 - Napoleon Costilla-Enriquez, Yang Weng:
Exposing Cyber-Physical System Weaknesses by Implicitly Learning their Underlying Models. 1333-1348 - Yoichi Hirose, Nozomu Yoshinari, Shinichi Shirakawa:
NAS-HPO-Bench-II: A Benchmark Dataset on Joint Optimization of Convolutional Neural Network Architecture and Training Hyperparameters. 1349-1364 - Rajan Kumar Soni, Karthick Seshadri, Balaraman Ravindran:
Metric Learning for comparison of HMMs using Graph Neural Networks. 1365-1380 - James O'Neill, Greg Ver Steeg, Aram Galstyan:
Layer-Wise Neural Network Compression via Layer Fusion. 1381-1396 - Mariia Vladimirova, Julyan Arbel, Stéphane Girard:
Bayesian neural network unit priors and generalized Weibull-tail property. 1397-1412 - Wenpeng Liu, Li Wang, Jie Chen, Yu Zhou, Ruirui Zheng, Jianjun He:
A Partial Label Metric Learning Algorithm for Class Imbalanced Data. 1413-1428 - Thomas Lavastida, Kefu Lu, Benjamin Moseley, Yuyan Wang:
Scaling Average-Linkage via Sparse Cluster Embeddings. 1429-1444 - Houru Chen, Caijuan Shi, Wei Li, Changyu Duan, jinwei Yan:
Multi-scale Salient Instance Segmentation based on Encoder-Decoder. 1445-1460 - Haoran Yang, Wanjing Zhang, Wai Lam:
A Two-Stage Training Framework with Feature-Label Matching Mechanism for Learning from Label Proportions. 1461-1476 - Huixin Zhan, Kun Zhang, Chenyi Hu, Victor S. Sheng:
K2-GNN: Multiple Users' Comments Integration with Probabilistic K-Hop Knowledge Graph Neural Networks. 1477-1492 - Yutao Chen, Yu Zhang, Fei Yang:
Learn to Predict Vertical Track Irregularity with Extremely Imbalanced Data. 1493-1504 - Li Zhang, Yanzeng Li
Semi-Open Attribute Extraction from Chinese Functional Description Text. 1505-1520 - Ruihong Yang, Junchao Tian, Yu Zhang:
Regularized Mutual Learning for Personalized Federated Learning. 1521-1536 - Tianyu Chen, Zhixin Li, Tiantao Xian, Canlong Zhang, Huifang Ma:
Relation Also Need Attention: Integrating Relation Information Into Image Captioning. 1537-1552 - Grant Getzelman, Prasanna Balaprakash:
Learning to Switch Optimizers for Quadratic Programming. 1553-1568 - Shibo Yao, Dantong Yu, Xiangmin Jiao:
Perturbing Eigenvalues with Residual Learning in Graph Convolutional Neural Networks. 1569-1584 - Masahiro Nakano, Yasuhiro Fujiwara, Akisato Kimura, Takeshi Yamada, Naonori Ueda:
Bayesian nonparametric model for arbitrary cubic partitioning. 1585-1600 - Anton Mallasto, Markus Heinonen, Samuel Kaski:
Bayesian Inference for Optimal Transport with Stochastic Cost. 1601-1616 - Honghan Zhou, Weiling Cai, Le Xu, Yang Ming:
Multi-view Latent Subspace Clustering based on both Global and Local Structure. 1617-1632 - Beomsoo Kim, Jang-Ho Choi, Jaegul Choo:
Augmenting Imbalanced Time-series Data via Adversarial Perturbation in Latent Space. 1633-1644 - Guixuan Wen, Kaigui Wu:
Building Decision Tree for Imbalanced Classification via Deep Reinforcement Learning. 1645-1659 - Baihan Lin, Xinxin Zhang:
Speaker Diarization as a Fully Online Bandit Learning Problem in MiniVox. 1660-1674 - Yuanding Zhou, Baopu Li, Zhihui Wang, Haojie Li:
Video Action Recognition with Neural Architecture Search. 1675-1690 - Vojtech Franc, Andrii Yermakov
Learning Maximum Margin Markov Networks from examples with missing labels. 1691-1706 - Tatsuya Matsuoka, Naoto Ohsaka:
Maximization of Monotone k-Submodular Functions with Bounded Curvature and Non-k-Submodular Functions. 1707-1722 - Weida Xie, Shi Chen, Qingjia Bao, Kewen Liu, Zhao Li, Xiaojun Li, Chongxin Bai, Piqiang Li, Chaoyang Liu, Otikovs Martins:
Unsupervised Cycle-Consistent Network for Removing Susceptibility Artifacts in Single-shot EPI. 1723-1738 - Mingyang Song
Hybrid Summarization with Semantic Weighting Reward and Latent Structure Detector. 1739-1754 - Juliette Achddou, Olivier Cappé, Aurélien Garivier:
Fast Rate Learning in Stochastic First Price Bidding. 1754-1769
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