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Yongdai Kim

  1. Learning fair representation with a parametric integral probability metric
    2022/02/07 by Dong Ha Kim, Kim, Dongha, Kunwoong Kim +7 · 6 citations
    Social Sciences · Computer Science · #Ethics and Social Impacts of AI #Adversarial Robustness in Machine Learning
  2. Improving Adversarial Robustness by Putting More Regularizations on Less Robust Samples
    2022/06/07 by Dong‐Yoon Yang, Yang, Dongyoon, Insung Kong +3 · 3 citations
    Computer Science · Medicine · #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #COVID-19 diagnosis using AI #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  3. ODIM: Outlier Detection via Likelihood of Under-Fitted Generative Models
    2023/01/11 by Dongha Kim, Jae‐Sung Hwang, Kim, Dongha +7 · 2 citations
    Computer Science · #Anomaly Detection Techniques and Applications #Generative Adversarial Networks and Image Synthesis #Digital Media Forensic Detection
  4. Masked Bayesian Neural Networks : Theoretical Guarantee and its Posterior Inference
    2023/05/24 by Insung Kong, Kong, Insung, Dong‐Yoon Yang +9 · 3 citations
    Computer Science · Engineering · #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Fault Detection and Control Systems #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms
  5. Nonconvex sparse regularization for deep neural networks and its optimality
    2020/03/26 by Ilsang Ohn, Yongdai Kim, Ohn, Ilsang +1 · 1 citation
    Engineering · Computer Science · Mathematics · #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques #Statistical Methods and Inference
  6. SLIDE: a surrogate fairness constraint to ensure fairness consistency
    2022/02/07 by Kunwoong Kim, Ilsang Ohn, Kim, Kunwoong +5 · 1 citation
    Social Sciences · #Ethics and Social Impacts of AI #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  7. META-ANOVA: Screening interactions for interpretable machine learning
    2024/08/02 by Yongchan Choi, Seokhun Park, Choi, Yongchan +6 · 2 citations
    Computer Science · #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistics Theory (math.ST)
  8. Fair Representation Learning for Continuous Sensitive Attributes using Expectation of Integral Probability Metrics
    2025/05/09 by Insung Kong, Kunwoong Kim, Kong, Insung +3 · 3 citations
    Computer Science · Social Sciences · #Ethics and Social Impacts of AI #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Mobile Crowdsensing and Crowdsourcing
  9. Tensor Product Neural Networks for Functional ANOVA Model
    2025/02/21 by Seokhun Park, Insung Kong, Park, Seokhun +6 · 2 citations
    Computer Science · Mathematics · #Computational Physics and Python Applications #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistics Theory (math.ST) #Tensor decomposition and applications
  10. Fairness Through Matching
    2025/01/06 by K. Kim, Kim, Kunwoong, Insung Kong +9 · 2 citations
    Social Sciences · #Artificial Intelligence (cs.AI) #Experimental Behavioral Economics Studies #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Qualitative Comparative Analysis Research
  11. COVAriance-Induced Fairness Gap Penalty for Subgroup-Fair Clustering
    2026/07/20 by Kyungseon Lee, Hankyo Jeong, Kunwoong Kim +2
    #stat.ML #cs.LG