publications

(*) denotes equal contribution

2024

  1. CLeaR
    Inference of Nonlinear Causal Effects with Application to TWAS with GWAS Summary Data
    Ben Dai*, Chunlin Li*, Haoran Xue, Wei Pan, and Xiaotong Shen
    In Proceedings of the Third Conference on Causal Learning and Reasoning, PMLR, 2024

2023

  1. NeurIPS
    ReHLine: Regularized Composite ReLU-ReHU Loss Minimization with Linear Computation and Linear Convergence
    Ben Dai*, and Yixuan Qiu*
    In Thirty-seventh Conference on Neural Information Processing Systems, 2023
  2. JMLR
    RankSEG: A Consistent Ranking-based Framework for Segmentation
    Ben Dai, and Chunlin Li
    Journal of Machine Learning Research, 2023
  3. TMLR
    Supervised Knowledge May Hurt Novel Class Discovery Performance
    Ziyun Li, Jona Otholt, Ben Dai, Di Hu, Christoph Meinel, and Haojin Yang
    Transactions on Machine Learning Research, 2023
  4. AoAS
    Data-adaptive discriminative feature localization with statistically guaranteed interpretation
    Ben Dai, Xiaotong Shen, Lin Yee Chen, Chunlin Li, and Wei Pan
    The Annals of Applied Statistics, 2023
  5. CVPR
    ImbaGCD: Imbalanced Generalized Category Discovery
    Ziyun Li, Ben Dai, Furkan Simsek, Christoph Meinel, and Haojin Yang
    In The 2nd Workshop on Computer Vision in the Wild, CVPR 2023, 2023

2022

  1. Optica
    Full Poincaré polarimetry enabled through physical inference
    Chao He, Jianyu Lin, Jintao Chang, Jacopo Antonello, Ben Dai, Jingyu Wang, Jiahe Cui, Ji Qi, Min Wu, Daniel S Elson, and 1 more author
    Optica, 2022
  2. IEEE TNNLS
    Significance tests of feature relevance for a black-box learner
    Ben Dai, Xiaotong Shen, and Wei Pan
    IEEE Transactions on Neural Networks and Learning Systems, 2022
  3. AP
    Revealing complex optical phenomena through vectorial metrics
    Chao He, Jintao Chang, Patrick S Salter, Yuanxing Shen, Ben Dai, Pengcheng Li, Yihan Jin, Samlan Chandran Thodika, Mengmeng Li, Aziz Tariq, and 1 more author
    Advanced Photonics, 2022
  4. JASA
    Coupled Generation
    Ben Dai, Xiaotong Shen, and Wing Wong
    Journal of the American Statistical Association, 2022
  5. JASA
    Embedding learning
    Ben Dai, Xiaotong Shen, and Junhui Wang
    Journal of the American Statistical Association, 2022

2021

  1. JASA
    Scalable collaborative ranking for personalized prediction
    Ben Dai, Xiaotong Shen, Junhui Wang, and Annie Qu
    Journal of the American Statistical Association, 2021
  2. EJS
    Two-level monotonic multistage recommender systems
    Ben Dai, Xiaotong Shen, and Wei Pan
    Electronic Journal of Statistics, 2021
  3. EJS
    Sentiment analysis with covariate-assisted word embeddings
    Shirong Xu, Ben Dai, and Junhui Wang
    Electronic Journal of Statistics, 2021

2019

  1. JMLR
    Smooth neighborhood recommender systems
    Ben Dai, Junhui Wang, Xiaotong Shen, and Annie Qu
    Journal of Machine Learning Research, 2019
  2. EJS
    Query-dependent ranking and its asymptotic properties
    Ben Dai, and Junhui Wang
    Electronic Journal of Statistics, 2019
  3. NC
    Complex vectorial optics through gradient index lens cascades
    Chao He, Jintao Chang, Qi Hu, Jingyu Wang, Jacopo Antonello, Honghui He, Shaoxiong Liu, Jianyu Lin, Ben Dai, Daniel S Elson, and 1 more author
    Nature Communications, 2019