AI & ML Confernce Papers

• Li, Z., Cao, Y., Gao, C., He, Y., Liu, H., Klusowski, J., Fan, J., Wang, M. (2024).  
  One-Layer Transformer Provably Learns One-Nearest Neighbor In Context.  
  Neural Information Processing Systems (NeurIPS'24)
• Gao, C.,   Cao, Y.,  Li, Z.,  He, Y.,  Wang, M., Liu, H.,  Klusowski, J., and  Fan (2024). 
  Global Convergence in Training Large-Scale Transformers
  Neural Information Processing Systems (NeurIPS'24).
• Ge, J.,  Mukherjee, D., and Fan, J. (2024).   
  Optimal Aggregation of Prediction Intervals under Unsupervised Domain Shift
  Neural Information Processing Systems (NeurIPS'24).
• Ge, J., Tang, S., Fan, J. and Jin, C.  (2024).
  On the Provable Advantage of Unsupervised Pretraining.
  International Conference on Learning Representations (ICLR 2024).
• Ge, J., Tang, S., Fan, J., Ma, C., and Jin, C. (2024).
  Maximum Likelihood Estimation is All You Need for Well-Specified Covariate Shift.
  International Conference on Learning Representations (ICLR 2024).
• Fan, Z., Wei, Z., Li, Z., Wang, S., Shan, H., Huang, X., Fan, J. (2022). 
  Constructing Phrase-level Semantic Labels to Form Multi-Grained Supervision for Image-Text Retrieval.
  ICMR'22: Proceedings of the 2022 International Conference on Multimedia Retrieval, 137-145.
• Wang, B., Yan, Y., and Fan, J. (2021). 
  Sample-efficient reinforcement learning for linearly-parameterized MDPs with a generative model.
  Neural Information Processing Systems (NeurIPS'21)
• Zhang, J., Wei, Z., Fan, J., Peng, J. (2021). 
  Curriculum Learning for Vision-and-Language Navigation.
  Neural Information Processing Systems (NeurIPS'21)
• Fan, J., Wang, Z., Xie, Y., and Yang, Z. (2020, July). 
  A theoretical analysis of deep Q-learning. 
  In Learning for Dynamics and Control (pp. 486-489). PMLR.
• Fan, J., Gong, W, Li, J., and Sun, Q. (2018). 
  Statistical sparse online regression: A dffusion approximation perspective. 
  Proceedings of Machine Learning Research (AISTATS 2018), 84,

AI & ML Interdisciplinary Applications

• Fan, J., Ke, Z., Liao, Y., and Neuhierl (2022).
  Structural Deep Learning in Conditional Asset Pricing.
  Journal of Finance, under revision. 
• Ait-Sahalia, Y., Fan, J., Xue, L., and Zhou, Y. (2022).  
  How and When are High-Frequency Stock Returns Predictable?
  Management Science under revision. 
• Fan J., Liu, Q., and Zheng, K. (2025). 
  Unearthing Financial Statement Fraud: Insights from News Coverage Analysis.
  Management Science, to appear. 
• Chen, M.,  Mei, S., Fan, J. and Wang, M. (2024). 
  Opportunities and Challenges of Diffusion Models for Generative AI.  
  National Science Review, 11 (12), nwae348.
• Fan, J., Xue, L., and Zhou, Y. (2024).  
  How much can machines learn finance from Chinese text data?
  Management Science, 70 (12), 8962–8987                                                   Manuscript
• Almeida, C., Fan, J., Freire, G., and Tang, F. (2023).  
  Can a Machine Correct Option Pricing Models? 
  Journal of Business and Economics Statistics, 41, 995-1009.
• Zhou, Y., Xue, L., Shi, Z., Wu, L., and Fan, J. (2022). 
  Measuring housing vitality from multi-source big data and machine learning.  
  Journal of American Statistical Association, 117, 1045-1059 Manuscript
• Fan, J., Ke, Y., and Liao, Y. (2021). 
  Augmented Factor Models with Applications to Validating Market Risk Factors and Forecasting Bond Risk Premia.  
  Journal of Econometrics , 22, 269-294. Manuscript 
• Chiang, C.H., Dai, W., Fan, J., Hong, H.G., Tu, J. (2019). 
  Robust Measures of Earnings Surprisess.
  Journal of Finance , 74, 943-983. Manuscript
• Fan, J., Furger, A., and Xiu, D. (2016).  
  Incorporating global industrial classification standard into portfolio allocation: A simple factor-based large covariance matrix estimator with high frequency data.
  Journal of Business and Economics Statistics, 34, 489-503. Manuscript
• Fan, J., Liao, Y. and Yao, J. (2015). 
  Power Enhancement in High Dimensional Cross-Sectional Tests.
  Econometrica , 83, 1497-1541 
  An older version: Large panel test of factor pricing models.
• Ait-Sahalia, Y., Fan, J., and Li, Y. (2013).
  The leverage effect puzzle: disentangling sources of bias in high frequency inference.
  Journal of Financial Economics 109, 224-249. (Manuscript)
  Vast portfolio selection with gross-exposure constraints.
  Journal of American Statistical Association, 107, 592-606. (Manuscript) 
• Fan, J. and Mancini, L. (2009).
  Option Pricing with aggregation of physical models and nonparametric statistical learning.
  Journal of American Statistical Association, 104, 1351-1372. 
  Manuscript.