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Publications
- Y. Park, D. Maddix, F. Aubet, K. Kan, J. Gasthaus, Y. Wang, Learning quantile functions without quantile crossing for distribution-free time series forecasting, International Conference on Artificial Intelligence and Statistics (2022), Github.
- K. Kan, F. Auber, T. Januschowski, Y. Park, K. Benidis, L. Ruthotto, J. Gasthaus, Multivariate quantile function forecaster, International Conference on Artificial Intelligence and Statistics (2022). Github
- K. Kan, J. Nagy and L.Ruthotto, Avoiding the double descent phenomenon of random feature models using hybrid regularization, submitted, arXiv preprint arXiv:2012.06667, (2020). Github
- K. Kan, S. Wu Fung and L. Ruthotto, PNKH-B: a projected Newton-Krylov method for large-scale bound-constrained optimization, SIAM Journal on Scientific Computing, 43.5 (2021), S704-S726. Github
- R. Chan, K. Kan, M. Nikolova and R. Plemmons, A two-stage method for spectral-spatial classification of hyperspectral images, Journal of Mathematical Imaging and Vision, (2020), 1-18.
- R. Chan, K. Kan and A. Ma, Computation of implementation shortfall for algorithmic trading by sequence alignment, The Journal of Financial Data Science, 1 (2019), 88-97.
- R. Chan, K. Kan and A. Ma, An integer programming based strategy for Asian-style futures arbitrage over the settlement period, Algorithmic Finance, 7 (2018), 31-42.
- R. Chan, K. Kan and A. Ma, An upper bound for ex-post Sharpe ratio with application in performance measurement, The Journal of Performance Measurement, 22 (2017), 7-19.
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