ACML 2021

114 papers

$h$-DBSCAN: A Simple Fast DBSCAN Algorithm for Big Data Shaoyuan Weng, Jin Gou, Zongwen Fan

$K^2$-GNN: Multiple Users’ Comments Integration with Probabilistic K-Hop Knowledge Graph Neural Networks Huixin Zhan, Kun Zhang, Chenyi Hu, Victor Sheng

A Causal Approach for Unfair Edge Prioritization and Discrimination Removal Balaraman Ravindran Pavan Ravishankar

A Mutual Information Regularization for Adversarial Training Modeste Atsague, Olukorede Fakorede, Jin Tian

A Partial Label Metric Learning Algorithm for Class Imbalanced Data Wenpeng Liu, Li Wang, Jie Chen, Yu Zhou, Ruirui Zheng, Jianjun He

A Two-Stage Training Framework with Feature-Label Matching Mechanism for Learning from Label Proportions Haoran Yang, Wanjing Zhang, Wai Lam

An Aligned Subgraph Kernel Based on Discrete-Time Quantum Walk Kai Liu, Lulu Wang, Yi Zhang

An Online Semi-Definite Programming with a Generalised Log-Determinant Regularizer and Its Applications Yaxiong Liu, Ken-ichiro Moridomi, Kohei Hatano, Eiji Takimoto

An Optimistic Acceleration of AMSGrad for Nonconvex Optimization Jun-Kun Wang, Xiaoyun Li, Belhal Karimi, Ping Li

ASD-Conv: Monocular 3D Object Detection Network Based on Asymmetrical Segmentation Depth-Aware Convolution Yu Xingyuan, Du Neng, Gao Ge, Wen Fan

Asymptotically Exact and Fast Gaussian Copula Models for Imputation of Mixed Data Types Benjamin Christoffersen, Mark Clements, Keith Humphreys, Hedvig Kjellström

Augmenting Imbalanced Time-Series Data via Adversarial Perturbation in Latent Space Beomsoo Kim, Jang-Ho Choi, Jaegul Choo

Bayesian Inference for Optimal Transport with Stochastic Cost Anton Mallasto, Markus Heinonen, Samuel Kaski

Bayesian Latent Factor Model for Higher-Order Data Zerui Tao, Xuyang Zhao, Toshihisa Tanaka, Qibin Zhao

Bayesian Neural Network Unit Priors and Generalized Weibull-Tail Property Mariia Vladimirova, Julyan Arbel, Stéphane Girard

Bayesian Nonparametric Model for Arbitrary Cubic Partitioning Masahiro Nakano, Yasuhiro Fujiwara, Akisato Kimura, Takeshi Yamada, Naonori Ueda

Beyond $L_p$ Clipping: Equalization Based Psychoacoustic Attacks Against ASRs Hadi Abdullah, Muhammad Sajidur Rahman, Christian Peeters, Cassidy Gibson, Washington Garcia, Vincent Bindschaedler, Thomas Shrimpton, Patrick Traynor

Bias-Tolerant Fair Classification Yixuan Zhang, Feng Zhou, Zhidong Li, Yang Wang, Fang Chen

BRAC+: Improved Behavior Regularized Actor Critic for Offline Reinforcement Learning Chi Zhang, Sanmukh Kuppannagari, Prasanna Viktor

Bridging Code-Text Representation Gap Using Explanation Hojae Han, Youngwon Lee, Minsoo Kim, Hwang Seung-won

Building Decision Tree for Imbalanced Classification via Deep Reinforcement Learning Guixuan Wen, Kaigui Wu

Calibrated Adversarial Training Tianjin Huang, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy

Cautious Actor-Critic Lingwei Zhu, Toshinori Kitamura, Matsubara Takamitsu

Collaborative Novelty Detection for Distributed Data by a Probabilistic Method Akira Imakura, Xiucai Ye, Tetsuya Sakurai

Contrastive Neural Processes for Self-Supervised Learning Konstantinos Kallidromitis, Denis Gudovskiy, Kozuka Kazuki, Ohama Iku, Luca Rigazio

ContriQ: Ally-Focused Cooperation and Enemy-Concentrated Confrontation in Multi-Agent Reinforcement Learning Zhao Chenran, Shi Dianxi, Zhang Yaowen, Yang Huanhuan, Yang Shaowu, Zhang Yongjun

Convolutional Hypercomplex Embeddings for Link Prediction Caglar Demir, Diego Moussallem, Stefan Heindorf, Axel-Cyrille Ngonga Ngomo

Cross-Structural Factor-Topic Model: Document Analysis with Sophisticated Covariates Chien Lu, Jaakko Peltonen, Timo Nummenmaa, Jyrki Nummenmaa, Kalervo Järvelin

CTAB-GAN: Effective Table Data Synthesizing Zilong Zhao, Aditya Kunar, Robert Birke, Lydia Y. Chen

CTS2: Time Series Smoothing with Constrained Reinforcement Learning Yongshuai Liu, Xin Liu

DAGSurv: Directed Ayclic Graph Based Survival Analysis Using Deep Neural Networks Ansh Kumar Sharma, Rahul Kukreja, Ranjitha Prasad, Shilpa Rao

DDSAS: Dynamic and Differentiable Space-Architecture Search Longxing Yang, Yu Hu, Shun Lu, Zihao Sun, Jilin Mei, Yiming Zeng, Zhiping Shi, Yinhe Han, Xiaowei Li

Deep Structural Contrastive Subspace Clustering Bo Peng, Wenjie Zhu

Domain Adaptive YOLO for One-Stage Cross-Domain Detection Shizhao Zhang, Hongya Tuo, Jian Hu, Zhongliang Jing

DPOQ: Dynamic Precision Onion Quantization Bowen Li, Kai Huang, Siang Chen, Dongliang Xiong, Luc Claesen

Dynamic Coordination Graph for Cooperative Multi-Agent Reinforcement Learning Chapman Siu, Jason Traish, Richard Yi Da Xu

Dynamic Popularity-Aware Contrastive Learning for Recommendation Fangquan Lin, Wei Jiang, Jihai Zhang, Cheng Yang

Efficient Coreset Constructions via Sensitivity Sampling Vladimir Braverman, Dan Feldman, Harry Lang, Adiel Statman, Samson Zhou

Encoder-Decoder-Based Image Transformation Approach for Integrating Precipitation Forecasts Hirotaka Hachiya, Yusuke Masumoto, Yuki Mori, Naonori Ueda

Ensembling with a Fixed Parameter Budget: When Does It Help and Why? Didan Deng, Emil Bertram Shi

ExNN-SMOTE: Extended Natural Neighbors Based SMOTE to Deal with Imbalanced Data Hongjiao Guan, Bin Ma, Yingtao Zhang, Xianglong Tang

Expert Advice Problem with Noisy Low Rank Loss Yaxiong Liu, Xuanke Jiang, Kohei Hatano, Eiji Takimoto

Exposing Cyber-Physical System Weaknesses by Implicitly Learning Their Underlying Models Napoleon Costilla-Enriquez, Yang Weng

Expressive Neural Voice Cloning Paarth Neekhara, Shehzeen Hussain, Shlomo Dubnov, Farinaz Koushanfar, Julian McAuley

Fairness Constraint of Fuzzy C-Means Clustering Improves Clustering Fairness Xu Xia, Zhang Hui, Ynag Chunming, Zhao Xujian, Li Bo

Fast Rate Learning in Stochastic First Price Bidding Juliette Achddou, Olivier Cappé, Aurélien Garivier

Feature Convolutional Networks He Hu

Generating Deep Networks Explanations with Robust Attribution Alignment Guohang Zeng, Yousef Kowsar, Sarah Erfani, James Bailey

Geometric Value Iteration: Dynamic Error-Aware KL Regularization for Reinforcement Learning Toshinori Kitamura, Lingwei Zhu, Takamitsu Matsubara

Greedy Search Algorithm for Mixed Precision in Post-Training Quantization of Convolutional Neural Network Inspired by Submodular Optimization Tsuji Satoki, Kawaguchi Hiroshi, Inoue Atsuki, Sakai Yasufumi, Yamada Fuyuka

Hierarchical Semantic Segmentation Using Psychometric Learning Lu Yin, Vlado Menkovski, Shwei Liu, Mykola Pechenizkiy

Hybrid Estimation for Open-Ended Questions with Early-Age Students’ Block-Based Programming Answers Hao Wu, Tianyi Chen, Xianzhe Luo, Canghong Jin, Yun Zhang, Minghui Wu

Hybrid Summarization with Semantic Weighting Reward and Latent Structure Detector Mingyang Song, Liping Jing, Yi Feng, Zhiwei Sun, Lin Xiao

Improving Gaussian Mixture Latent Variable Model Convergence with Optimal Transport Benoit Gaujac, Ilya Feige, David Barber

Improving Hashing Algorithms for Similarity Search via MLE and the Control Variates Trick Keegan Kang, Sergey Kushnarev, Wei Pin Wong, Rameshwar Pratap, Haikal Yeo, Chen Yijia

Iterative Deep Model Compression and Acceleration in the Frequency Domain Yao Zeng, Xusheng Liu, Lintan Sun, Wenzhong Li, Yuchu Fang, Sanglu Lu

Language Representations for Generalization in Reinforcement Learning Nikolaj Goodger, Peter Vamplew, Cameron Foale, Richard Dazeley

Layer-Wise Neural Network Compression via Layer Fusion James O’Neill, Greg V. Steeg, Aram Galstyan

Learn to Predict Vertical Track Irregularity with Extremely Imbalanced Data Yutao Chen, Yu Zhang, Fei Yang

Learning 3-Opt Heuristics for Traveling Salesman Problem via Deep Reinforcement Learning Jingyan Sui, Shizhe Ding, Ruizhi Liu, Liming Xu, Dongbo Bu

Learning Maximum Margin Markov Networks from Examples with Missing Labels Vojtech Franc, Andrii Yermakov

Learning to Switch Optimizers for Quadratic Programming Grant Getzelman, Prasanna Balaprakash

Lifelong Learning with Branching Experts Yi-Shan Wu, Yi-Te Hong, Chi-Jen Lu

Lifelong Learning with Sketched Structural Regularization Haoran Li, Aditya Krishnan, Jingfeng Wu, Soheil Kolouri, Praveen K. Pilly, Vladimir Braverman

Local Aggressive Adversarial Attacks on 3D Point Cloud Yiming Sun, Feng Chen, Zhiyu Chen, Mingjie Wang

Max-Utility Based Arm Selection Strategy for Sequential Query Recommendations Shameem Puthiya Parambath, Christos Anagnostopoulos, Roderick Murray-Smith, Sean MacAvaney, Evangelos Zervas

Maximization of Monotone $k$-Submodular Functions with Bounded Curvature and Non-$k$-Submodular Functions Tatsuya Matsuoka, Naoto Ohsaka

Meta-Model-Based Meta-Policy Optimization Takuya Hiraoka, Takahisa Imagawa, Voot Tangkaratt, Takayuki Osa, Takashi Onishi, Yoshimasa Tsuruoka

Metric Learning for Comparison of HMMs Using Graph Neural Networks Rajan Kumar Soni, Karthick Seshadri, Balaraman Ravindran

Modeling Risky Choices in Unknown Environments Ville Tanskanen, Chang Rajani, Homayun Afrabandpey, Aini Putkonen, Aurélien Nioche, Arto Klami

Multi-Branch Network for Cross-Subject EEG-Based Emotion Recognition Guang Lin, Li Zhu, Bin Ren, Yiteng Hu, Jianhai Zhang

Multi-Factor Memory Attentive Model for Knowledge Tracing Congjie Liu, Xiaoguang Li

Multi-Scale Salient Instance Segmentation Based on Encoder-Decoder Houru Chen, Caijuan Shi, Wei Li, Changyu Duan, Jinwei Yan

Multi-Stream Based Marked Point Process Sujun Hong, Hirotaka Hachiya

Multi-Task Actor-Critic with Knowledge Transfer via a Shared Critic Gengzhi Zhang, Liang Feng, Yaqing Hou

Multi-View Latent Subspace Clustering Based on Both Global and Local Structure Zhou Honghan, Cai Weiling, Xu Le, Yang Ming

NAS-HPO-Bench-II: A Benchmark Dataset on Joint Optimization of Convolutional Neural Network Architecture and Training Hyperparameters Yoichi Hirose, Nozomu Yoshinari, Shinichi Shirakawa

Neural Graph Filtering for Context-Aware Recommendation Zhang Chuanyan, Hong Xiaoguang

On the Convex Combination of Determinantal Point Processes Tatsuya Matsuoka, Naoto Ohsaka, Akihiro Yabe

Open Images V5 Text Annotation and yet Another Mask Text Spotter Ilya Krylov, Sergei Nosov, Vladislav Sovrasov

Pedestrian Wind Factor Estimation in Complex Urban Environments Sarah Mokhtar, Matt Beveridge, Yumeng Cao, Iddo Drori

Penalty Method for Inversion-Free Deep Bilevel Optimization Akshay Mehra, Jihun Hamm

Perturbing Eigenvalues with Residual Learning in Graph Convolutional Neural Networks Shibo Yao, Dantong Yu, Xiangmin Jiao

PFedAtt: Attention-Based Personalized Federated Learning on Heterogeneous Clients Zichen Ma, Yu Lu, Wenye Li, Jinfeng Yi, Shuguang Cui

Physics-Inspired Learning for Structure-Aware Texture-Sensitive Underwater Image Enhancement Xinwei Xue, Zexuan Li, Long Ma, Risheng Liu, Xin Fan

Pyramid Correlation Based Deep Hough Voting for Visual Object Tracking Ying Wang, Tingfa Xu, Shenwang Jiang, Junjie Chen, Jianan Li

QActor: Active Learning on Noisy Labels Taraneh Younesian, Zilong Zhao, Amirmasoud Ghiassi, Robert Birke, Lydia Y Chen

Quaternion Graph Neural Networks Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung

Regularized Mutual Learning for Personalized Federated Learning Ruihong Yang, Junchao Tian, Yu Zhang

Relation Also Need Attention: Integrating Relation Information into Image Captioning Tianyu Chen, Zhixin Li, Tiantao Xian, Canlong Zhang, Huifang Ma

Revisiting Weight Initialization of Deep Neural Networks Maciej Skorski, Alessandro Temperoni, Martin Theobald

Robust Domain Randomised Reinforcement Learning Through Peer-to-Peer Distillation Chenyang Zhao, Timothy Hospedales

Robust Model-Based Reinforcement Learning for Autonomous Greenhouse Control Wanpeng Zhang, Xiaoyan Cao, Yao Yao, Zhicheng An, Xi Xiao, Dijun Luo

Robust Regression for Monocular Depth Estimation Julian Lienen, Nils Nommensen, Ralph Ewerth, Eyke Hüllermeier

S2TNet: Spatio-Temporal Transformer Networks for Trajectory Prediction in Autonomous Driving Weihuang Chen, Fangfang Wang, Hongbin Sun

Scalable Gradient Matching Based on State Space Gaussian Processes Futoshi Futami

Scaling Average-Linkage via Sparse Cluster Embeddings Thomas Lavastida, Kefu Lu, Benjamin Moseley, Yuyan Wang

Semi-Open Attribute Extraction from Chinese Functional Description Text Li Zhang, Yanzeng Li, Rouyu Zhang, Wenjie Li

Sinusoidal Flow: A Fast Invertible Autoregressive Flow Yumou Wei

Skew-Symmetrically Perturbed Gradient Flow for Convex Optimization Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Ikko Yamane

Slice-Sampling Based 3D Object Classification Zhao Xiangwen, Yang Yi-Jun, Zeng Wei, Yang Liqun, Wang Yao

Solving Machine Learning Problems Sunny Tran, Pranav Krishna, Ishan Pakuwal, Prabhakar Kafle, Nikhil Singh, Jayson Lynch, Iddo Drori

Spatial Temporal Enhanced Contrastive and Pretext Learning for Skeleton-Based Action Representation Yiwen Zhan, Yuchen Chen, Pengfei Ren, Haifeng Sun, Jingyu Wang, Qi Qi, Jianxin Liao

SPDE-Net: Neural Network Based Prediction of Stabilization Parameter for SUPG Technique Sangeeta Yadav, Sashikumaar Ganesan

Speaker Diarization as a Fully Online Bandit Learning Problem in MiniVox Baihan Lin, Xinxin Zhang

Temporal Relation Based Attentive Prototype Network for Few-Shot Action Recognition Guangge Wang, Haihui Ye, Xiao Wang, Weirong Ye, Hanzi Wang

The Power of Factorial Powers: New Parameter Settings for (Stochastic) Optimization Aaron Defazio, Robert M. Gower

Time-Constrained Multi-Agent Path Finding in Non-Lattice Graphs with Deep Reinforcement Learning Marijn Knippenberg, Mike Holenderski, Vlado Menkovski

Transfer Learning with Adaptive Online TrAdaBoost for Data Streams Ocean Wu, Yun Sing Koh, Gillian Dobbie, Thomas Lacombe

Understanding How Over-Parametrization Leads to Acceleration: A Case of Learning a Single Teacher Neuron Jun-Kun Wang, Jacob Abernethy

Unsupervised Cycle-Consistent Network for Removing Susceptibility Artifacts in Single-Shot EPI Weida Xie, Shi Chen, Qingjia Bao, Kewen Liu, Zhao Li, Xiaojun Li, Chongxin Bai, Piqiang Li, Chaoyang Liu, Otikovs Martins

Uplift Modeling with High Class Imbalance Otto Nyberg, Tomasz Kuśmierczyk, Arto Klami

Vector Transport Free Riemannian LBFGS for Optimization on Symmetric Positive Definite Matrix Manifolds Reza Godaz, Benyamin Ghojogh, Reshad Hosseini, Reza Monsefi, Fakhri Karray, Mark Crowley

Video Action Recognition with Neural Architecture Search Yuanding Zhou, Baopu Li, Zhihui Wang, Haojie Li