ACML 2022

83 papers

3D Manifold Topology Based Medical Image Data Augmentation Jisui Huang, Na Lei

A Novel Differentiable Mixed-Precision Quantization Search Framework for Alleviating the Matthew Effect and Improving Robustness Hengyi Zhou, Hongyi He, Wanchen Liu, Yuhai Li, Haonan Zhang, Longjun Liu

A Novel Graph Aggregation Method Based on Feature Distribution Around Each Ego-Node for Heterophily Shuichiro Haruta, Tatsuya Konishi, Mori Kurokawa

A Self-Improving Skin Lesions Diagnosis Framework via Pseudo-Labeling and Self-Distillation Shaochang Deng, Mengxiao Yin, Feng Yang

A Two-Stream Convolution Architecture for ESC Based on Audio Feature Distanglement Zhenghao Chang, Ruhan He, Yongsheng Yu, Zili Zhang, GeLi Bai

Adversarial Laser Spot: Robust and Covert Physical-World Attack to DNNs Chengyin Hu, Yilong Wang, Kalibinuer Tiliwalidi, Wen Li

AFRNN: Stable RNN with Top Down Feedback and Antisymmetry Tim Schwabe, Tobias Glasmachers, Maribel Acosta

AIIR-MIX: Multi-Agent Reinforcement Learning Meets Attention Individual Intrinsic Reward Mixing Network Wei Li, Weiyan Liu, Shitong Shao, Shiyi Huang

An Enhanced Human Activity Recognition Algorithm with Positional Attention Chenyang Xu, Jianfei Shen, Feiyi Fan, Tian Qiu, Zhihong Mao

AS-IntroVAE: Adversarial Similarity Distance Makes Robust IntroVAE Lu Changjie, Zheng Shen, Wang Zirui, Dib Omar, Gupta Gaurav

Asynchronous Personalized Federated Learning with Irregular Clients Zichen Ma, Yu Lu, Wenye Li, Shuguang Cui

Auto-Physics-Encoder: Using Physics-Informed Latent Layer Two-Way Physics Flow for Monitoring Systems with Unobservability Priyabrata Sundaray, Yang Weng

Autonomous Myocardial Infarction Detection from Electrocardiogram with a Multi Label Classification Approach Vishwa Mohan Singh, Vibhor Saran, Pooja Kadambi

Balanced Spatial-Temporal Graph Structure Learning for Multivariate Time Series Forecasting: A Trade-Off Between Efficiency and Flexibility Weijun Chen, Yanze Wang, Chengshuo Du, Zhenglong Jia, Feng Liu, Ran Chen

BayesAdapter: Being Bayesian, Inexpensively and Reliably, via Bayesian Fine-Tuning Zhijie Deng, Jun Zhu

Bayesian Change-Point Detection for Bandit Feedback in Non-Stationary Environments Reda Alami

BeautifAI - Personalised Occasion-Based Makeup Recommendation Kshitij Gulati, Gaurav Verma, Mukesh Mohania, Ashish Kundu

BINAS: Bilinear Interpretable Neural Architecture Search Niv Nayman, Yonathan Aflalo, Asaf Noy, Lihi Zelnik-Manor

Bootstrapping a High Quality Multilingual Multimodal Dataset for Bletchley Owais Khan Mohammed, Kriti Aggarwal, Qiang Liu, Saksham Singhal, Johan Bjorck, Subhojit Som

Circulant-Interactive Transformer with Dimension-Aware Fusion for Multimodal Sentiment Analysis Peizhu Gong, Jin Liu, Xiliang Zhang, Xingye Li, Zijun Yu

Constrained Contrastive Reinforcement Learning Haoyu Wang, Xinrui Yang, Yuhang Wang, Lan Xuguang

Constrained Density Matching and Modeling for Cross-Lingual Alignment of Contextualized Representations Wei Zhao, Steffen Eger

Contrastive Inductive Bias Controlling Networks for Reinforcement Learning Dongxu Li, Shaochen Wang, Kang Chen, Bin Li

Cross-Scale Context Extracted Hashing for Fine-Grained Image Binary Encoding Xuetong Xue, Jiaying Shi, Xinxue He, Shenghui Xu, Zhaoming Pan

CVaR-Regret Bounds for Multi-Armed Bandits Chenmien Tan, Paul Weng

DALE: Differential Accumulated Local Effects for Efficient and Accurate Global Explanations Vasilis Gkolemis, Theodore Dalamagas, Christos Diou

Deep Reinforcement Learning for High-Frequency Market Making Pankaj Kumar

Domain Alignment Meets Fully Test-Time Adaptation Kowshik Thopalli, Pavan Turaga, Jayaraman J Thiagarajan

Dynamic Forward and Backward Sparse Training (DFBST): Accelerated Deep Learning Through Completely Sparse Training Schedule Tejas Pote, Muhammad Athar Ganaie, Atif Hassan, Swanand Khare

EENAS: An Eﬀicient Evolutionary Algorithm for Neural Architecture Search Zheng Jian, Han Wenran, Zhang Ying, Ji Shufan

Efficient Deep Clustering of Human Activities and How to Improve Evaluation Louis Mahon, Thomas Lukasiewicz

Embedding Adaptation Network with Transformer for Few-Shot Action Recognition Rongrong Jin, Xiao Wang, Guangge Wang, Yang Lu, Hai-Miao Hu, Hanzi Wang

Evaluating the Perceived Safety of Urban City via Maximum Entropy Deep Inverse Reinforcement Learning Yaxuan Wang, Zhixin Zeng, Qijun Zhao

Example or Prototype? Learning Concept-Based Explanations in Time-Series Christoph Obermair, Alexander Fuchs, Franz Pernkopf, Lukas Felsberger, Andrea Apollonio, Daniel Wollmann

Fairness Trade-Offs and Partial Debiasing Francois Buet-Golfouse, Islam Utyagulov

Feature Distribution Matching for Federated Domain Generalization Yuwei Sun, Ng Chong, Hideya Ochiai

FF-Net: An End-to-End Feature-Fusion Network for Double JPEG Detection and Localization Bo Liu, Ranglei Wu, Xiuli Bi, Bin Xiao

FLVoogd: Robust and Privacy Preserving Federated Learning Tian Yuhang, Wang Rui, Qiao Yanqi, Panaousis Emmanouil, Liang Kaitai

Graph Annotation Generative Adversarial Networks Yoann Boget, Magda Gregorova, Alexandros Kalousis

Hashing2Vec: Fast Embedding Generation for SARS-CoV-2 Spike Sequence Classification Murad Taslim, Chourasia Prakash, Ali Sarwan, Patterson Murray

Interpretable Representation Learning from Temporal Multi-View Data Lin Qiu, Vernon M. Chinchilli, Lin Lin

Kernelized Multi-Graph Matching François-Xavier Dupé, Rohit Yadav, Guillaume Auzias, Sylvain Takerkart

Layer-Wise Adaptive Graph Convolution Networks Using Generalized Pagerank Kishan Wimalawarne, Taiji Suzuki

Learning Disentangled Representation in Pruning for Real-Time UAV Tracking Siyu Ma, Yuting Liu, Dan Zeng, Yaxin Liao, Xiaoyu Xu, Shuiwang Li

Learning Practical Communication Strategies in Cooperative Multi-Agent Reinforcement Learning Diyi Hu, Chi Zhang, Viktor Prasanna, Bhaskar Krishnamachari

Learning with Domain Knowledge to Develop Justifiable Convolutional Networks Rimmon Bhosale, Mrinal Das

Learning with Interactive Models over Decision-Dependent Distributions Man-Jie Yuan, Wei Gao

Locally Differentially Private Reinforcement Learning for Linear Mixture Markov Decision Processes Chonghua Liao, Jiafan He, Quanquan Gu

Margin Calibration for Long-Tailed Visual Recognition Yidong Wang, Bowen Zhang, Wenxin Hou, Zhen Wu, Jindong Wang, Takahiro Shinozaki

Multi Label Loss Correction Against Missing and Corrupted Labels Amirmasoud Ghiassi, Robert Birke, Lydia.Y Chen

Multi-Class Classification from Multiple Unlabeled Datasets with Partial Risk Regularization Yuting Tang, Nan Lu, Tianyi Zhang, Masashi Sugiyama

Multi-Scale Anomaly Detection for Time Series with Attention-Based Recurrent Autoencoders Lu Qingning, Li Wenzhong, Zhu Chuanze, Chen Yizhou, Wang Yinke, Zhang Zhijie, Shen Linshan, Lu Sanglu

Multi-Scale Progressive Gated Transformer for Physiological Signal Classification Wei Zhou, Hao Wang, Yiling Zhang, Cheng Long, Yan Yang, Dongjie Wang

Multiple Imputation with Neural Network Gaussian Process for High-Dimensional Incomplete Data Zongyu Dai, Zhiqi Bu, Qi Long

Nighttime Semantic Segmentation with Unsupervised Learning and Cross Attention Jian Cheng, Yang-Feng Hu, Yu Dai, Xue Qiao, Li Yao, Jun-Yan Yang

Noise Robust Core-Stable Coalitions of Hedonic Games Prashant Trivedi, Nandyala Hemachandra

Noisy Riemannian Gradient Descent for Eigenvalue Computation with Application to Inexact Stochastic Recursive Gradient Algorithm You-Lin Chen, Zhiqiang Xu, Ping Li

On PAC Learning Halfspaces in Non-Interactive Local Privacy Model with Public Unlabeled Data Jinyan Su, Jinhui Xu, Di Wang

On the Convergence of Decentralized Adaptive Gradient Methods Xiangyi Chen, Belhal Karimi, Weijie Zhao, Ping Li

On the Episodic Difficulty of Few-Shot Learning Yunwei Bai, Zhenfeng He, Junfeng Hu

On the Expressivity of Bi-Lipschitz Normalizing Flows Alexandre Verine, Benjamin Negrevergne, Yann Chevaleyre, Fabrice Rossi

On the Interpretability of Attention Networks Lakshmi Narayan Pandey, Rahul Vashisht, Harish G. Ramaswamy

One Gradient Frank-Wolfe for Decentralized Online Convex and Submodular Optimization Tuan-Anh Nguyen, Nguyen Kim Thang, Denis Trystram

Out of Distribution Detection via Neural Network Anchoring Rushil Anirudh, Jayaraman J. Thiagarajan

Pose Guided Human Image Synthesis with Partially Decoupled GAN Jianhan Wu, Shijing Si, Jianzong Wang, Xiaoyang Qu, Xiao Jing

Position-Dependent Partial Convolutions for Supervised Spatial Interpolation Hirotaka Hachiya, Kotaro Nagayoshi, Asako Iwaki, Takahiro Maeda, Naonori Ueda, Hiroyuki Fujiwara

Probabilistic Adaptive Spatial-Temporal Regularized Correlation Filters for UAV Tracking Rui Li, Xiao Li

Probabilistic Fusion of Neural Networks That Incorporates Global Information Peng Xiao, Biao Zhang, Samuel Cheng, Ke Wei, Shuqin Zhang

ProtoBandit: Efficient Prototype Selection via Multi-Armed Bandits Arghya Roy Chaudhuri, Pratik Jawanpuria, Bamdev Mishra

Robust Computation of Optimal Transport by $β$-Potential Regularization Shintaro Nakamura, Han Bao, Masashi Sugiyama

Robust Direct Learning for Causal Data Fusion Xinyu Li, Yilin Li, Qing Cui, Longfei Li, Jun Zhou

Robust Multi-Objective Reinforcement Learning with Dynamic Preferences Francois Buet-Golfouse, Parth Pahwa

Robust Scene Text Detection via Learnable Scene Transformations Yuheng Cao, Mengjie Zhou, Jie Chen

RoLNiP: Robust Learning Using Noisy Pairwise Comparisons Samartha S. Maheshwara, Naresh Manwani

Semantic Cross Attention for Few-Shot Learning Bin Xiao, Chien-Liang Liu, Wen-Hoar Hsaio

Sliced Wasserstein Variational Inference Mingxuan Yi, Song Liu

SNAIL: Semi-Separated Uncertainty Adversarial Learning for Universal Domain Adaptation Zhongyi Han, Wan Su, Rundong He, Yilong Yin

Temporal Aware Multi-Interest Graph Neural Network for Session-Based Recommendation Qi Shen, Shixuan Zhu, Yitong Pang, Yiming Zhang, Zhihua Wei

Towards Data-Free Domain Generalization Ahmed Frikha, Haokun Chen, Denis Krompaß, Thomas Runkler, Volker Tresp

Trusted Loss Correction for Noisy Multi-Label Learning Amirmasoud Ghiassi, Cosmin Octavian Pene, Robert Birke, Lydia.Y Chen

Unsupervised Photo-to-Caricature Generation with Adaptive Select Layer-Instance Normalization and Semi-Cycle Consistency Li Zhiwei, Cai Weiling, Cairun Wang

Value Function Approximations via Kernel Embeddings for No-Regret Reinforcement Learning Sayak Ray Chowdhury, Rafael Oliveira

When to Classify Events in Open Times Series? Youssef Achenchabe, Alexis Bondu, Cornuéjols Antoine, Lemaire Vincent