SDM

Keyphrases

Publications

2023

Ziqiao Meng, Yaoman Li, Peilin Zhao, Yang Yu, Irwin King
Meta-Learning with Motif-based Task Augmentation for Few-Shot Molecular Property Prediction. SDM (2023)
Lutz Oettershagen, Petra Mutzel
An Index For Temporal Closeness Computation in Evolving Graphs. SDM (2023)
Yan Zhou, Murat Kantarcioglu, Chris Clifton
On Improving Fairness of AI Models with Synthetic Minority Oversampling Techniques. SDM (2023)
Sikun Yang, Hongyuan Zha
Estimating Latent Population Flows from Aggregated Data via Inversing Multi-Marginal Optimal Transport. SDM (2023)
Xuechen Zhao, Jiaying Zou, Zhong Zhang, Feng Xie, Bin Zhou, Lei Tian
Feature Enhanced Zero-Shot Stance Detection via Contrastive Learning. SDM (2023)
Dezhi Yang, Guoxian Yu, Jun Wang, Zhongmin Yan, Maozu Guo
Causal Discovery by Graph Attention Reinforcement Learning. SDM (2023)
Yushun Dong, Binchi Zhang, Yiling Yuan, Na Zou, Qi Wang, Jundong Li
RELIANT: Fair Knowledge Distillation for Graph Neural Networks. SDM (2023)
Shan Lu, Mingjun Zhao, Songling Yuan, Xiaoli Wang, Lei Yang, Di Niu
BDA: Bandit-based Transferable AutoAugment. SDM (2023)
Lorenz Kummer, Kevin Sidak, Tabea Reichmann, Wilfried N. Gansterer
Adaptive Precision Training (AdaPT): A dynamic quantized training approach for DNNs. SDM (2023)
Zahra Donyavi, Adriane Serapio, Gustavo Batista
MC-SQ: A Highly Accurate Ensemble for Multi-class Quantification. SDM (2023)
Senzhang Wang, Hao Yan, Jinlong Du, Jun Yin, Junxing Zhu, Chaozhuo Li, Jianxin Wang
Adversarial Hard Negative Generation for Complementary Graph Contrastive Learning. SDM (2023)
Matteo Riondato
Statistically-sound Knowledge Discovery from Data. SDM (2023)
Joshua Tobin, Chin Pang Ho, Mimi Zhang
Reinforced EM Algorithm for Clustering with Gaussian Mixture Models. SDM (2023)
Rui Wang, Chongwei Liu, Xudong Mou, Kai Gao, Xiaohui Guo, Pin Liu, Tianyu Wo, Xudong Liu
Deep Contrastive One-Class Time Series Anomaly Detection. SDM (2023)
Zerun Lin, Yuhan Zhang, Lixin Duan, Le Ou-Yang, Peilin Zhao
MoVAE: A Variational AutoEncoder for Molecular Graph Generation. SDM (2023)
Haoyue Dai, Rui Ding, Yuanyuan Jiang, Shi Han, Dongmei Zhang
ML4C: Seeing Causality Through Latent Vicinity. SDM (2023)
Dongyue Li, Tina Eliassi-Rad, Hongyang R. Zhang
Optimal Intervention on Weighted Networks via Edge Centrality. SDM (2023)
Mansoureh Maadi, Hadi Akbarzadeh Khorshidi, Uwe Aickelin
Uncertainty in Selective Bagging: A Dynamic Bi-objective Optimization Model. SDM (2023)
Guangji Bai, Johnny Torres, Junxiang Wang, Liang Zhao, Cristina L. Abad, Carmen Vaca
Sign-Regularized Multi-Task Learning. SDM (2023)
Rodrigo Randel, Daniel Aloise, Alain Hertz
A Lagrangian-based approach to learn distance metrics for clustering with minimal data transformation. SDM (2023)
Guangtao Zheng, Qiuling Suo, Mengdi Huai, Aidong Zhang
Learning to Learn Task Transformations for Improved Few-Shot Classification. SDM (2023)
Shuai Feng, Wenyu Jiang, Mingcai Chen, Yuntao Du, Hao Cheng, Yuxin Ge, Chongjun Wang
CESED: Exploiting Hyperspherical Predefined Evenly-Distributed Class Centroids for OOD Detection. SDM (2023)
Khandakar Tanvir Ahmed, Sudipto Baul, Yanjie Fu, Wei Zhang
Attention-Based Multi-modal Missing Value Imputation for Time Series Data with High Missing Rate. SDM (2023)
Tian Xia, Sarp Aykent, Wei-Shinn Ku
Extrinsic-Intrinsic Representation Learning Framework for Drug Discovery. SDM (2023)
Zhiyu Xue
Group AdaBoost with Fairness Constraint. SDM (2023)
Zhong Zhuang, Kai Ming Ting, Guansong Pang, Shuaibin Song
Subgraph Centralization: A Necessary Step for Graph Anomaly Detection. SDM (2023)
Xiusi Chen, Yu Zhang, Jinliang Deng, Jyun-Yu Jiang, Wei Wang
Gotta: Generative Few-shot Question Answering by Prompt-based Cloze Data Augmentation. SDM (2023)
Lena G. M. Bauer, Collin Leiber, Christian Böhm, Claudia Plant
Extension of the Dip-test Repertoire - Efficient and Differentiable p-value Calculation for Clustering. SDM (2023)
Kwei-Herng Lai, Lan Wang, Huiyuan Chen, Kaixiong Zhou, Fei Wang, Hao Yang, Xia Hu
Context-aware Domain Adaptation for Time Series Anomaly Detection. SDM (2023)
Fred X. Han, Keith G. Mills, Fabian Chudak, Parsa Riahi, Mohammad Salameh, Jialin Zhang, Wei Lu, Shangling Jui, Di Niu
A General-Purpose Transferable Predictor for Neural Architecture Search. SDM (2023)
Ningjing Wang, Deqing Wang, Ting Jiang, Chenguang Du, Chuyu Fang, Fuzhen Zhuang
Hierarchical Neural Topic Model with Embedding Cluster and Neural Variational Inference. SDM (2023)
Xu Ye, Meng Xiao, Zhiyuan Ning, Weiwei Dai, Wenjuan Cui, Yi Du, Yuanchun Zhou
NEEDED: Introducing Hierarchical Transformer to Eye Diseases Diagnosis. SDM (2023)
Junyang Chen, Yidan Dai, Xianhui Chen, Yingshan Shen, Yan Luximon, Hailiang Wang, Yuxin He, Wenjun Ma, Xiaomao Fan
StAGN: Spatial-Temporal Adaptive Graph Network via Contrastive Learning for Sleep Stage Classification. SDM (2023)
Guangji Bai, Chen Ling, Yuyang Gao, Liang Zhao
Saliency-Augmented Memory Completion for Continual Learning. SDM (2023)
Somya Sharma, Rahul Ghosh, Arvind Renganathan, Xiang Li, Snigdhansu Chatterjee, John Nieber, Christopher J. Duffy, Vipin Kumar
Probabilistic Inverse Modeling: An Application in Hydrology. SDM (2023)
Aleksandr Rubashevskii, Daria Kotova, Maxim Panov
Scalable Batch Acquisition for Deep Bayesian Active Learning. SDM (2023)
Xiaowei Jia, Shengyu Chen, Can Zheng, Yiqun Xie, Zhe Jiang, Nasrin Kalanat
Physics-guided Graph Diffusion Network for Combining Heterogeneous Simulated Data: An Application in Predicting Stream Water Temperature. SDM (2023)
Yuhu Shang, Xuexiong Luo, Lihong Wang, Hao Peng, Xiankun Zhang, Yimeng Ren, Kun Liang
Reinforcement Learning Guided Multi-Objective Exam Paper Generation. SDM (2023)
Peng Liu, Yi Liu, Rui Zhu, Linglong Kong, Bei Jiang, Di Niu
Optimal Smooth Approximation for Quantile Matrix Factorization. SDM (2023)
Boris Wiegand, Dietrich Klakow, Jilles Vreeken
Why Are We Waiting? Discovering Interpretable Models for Predicting Sojourn and Waiting Times. SDM (2023)
Jinfeng Xiao, Mohab Elkaref, Nathan Herr, Geeth De Mel, Jiawei Han
Taxonomy-Guided Fine-Grained Entity Set Expansion. SDM (2023)
Zhixuan Chu, Mechelle Claridy, José Cordero, Sheng Li, Stephen L. Rathbun
Estimating Propensity Scores with Deep Adaptive Variable Selection. SDM (2023)
Jonatan Møller Nuutinen Gøttcke, Colin Bellinger, Paula Branco, Arthur Zimek
An Interpretable Measure of Dataset Complexity for Imbalanced Classification Problems. SDM (2023)
Bo Yan, Cheng Yang, Chuan Shi, Jiawei Liu, Xiaochen Wang
Abnormal Event Detection via Hypergraph Contrastive Learning. SDM (2023)
Zehong Wang, Qi Li, Donghua Yu, Xiaolong Han, Xiao-Zhi Gao, Shigen Shen
Heterogeneous Graph Contrastive Multi-view Learning. SDM (2023)
Jia-Hao Syu, Jerry Chun-Wei Lin, Philip S. Yu
Anomaly Detection Networks and Fuzzy Control Modules for Energy Grid Management with Q-Learning-Based Decision Making. SDM (2023)
Lu Wang, Yuhai Song, Zhe Wang, Haoxiang Wang, Yu Li, Weiwei Zhou, Haoming Dang, Mona Shao, Xiwei Zhao, Zhangang Lin, Jinghe Hu, Jingping Shao
Pluggable Deep Thompson Sampling with Applications to Recommendation. SDM (2023)
Ravdeep S. Pasricha, Uday Singh Saini, Nicholas D. Sidiropoulos, Fei Fang, Kevin Chan, Evangelos E. Papalexakis
Harvester: Principled Factorization-based Temporal Tensor Granularity Estimation. SDM (2023)
Li Zhang, Jiahao Ding, Yifeng Gao, Jessica Lin
PMP: Privacy-Aware Matrix Profile against Sensitive Pattern Inference for Time Series. SDM (2023)
Shilei Cao, Yujie Lin, Xianli Zhang, Yufu Chen, Zhen Zhu, Yuxin Chen, Buyue Qian, Feng Wang, Zang Li
Embedding Transfer with Enhanced Correlation Modeling for Cross-Domain Recommendation. SDM (2023)