P
Pengkun Yang
Researcher at Tsinghua University
Publications - 30
Citations - 851
Pengkun Yang is an academic researcher from Tsinghua University. The author has contributed to research in topics: Computer science & Polynomial. The author has an hindex of 11, co-authored 23 publications receiving 615 citations. Previous affiliations of Pengkun Yang include Princeton University & University of Illinois at Urbana–Champaign.
Papers
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Journal ArticleDOI
Minimax Rates of Entropy Estimation on Large Alphabets via Best Polynomial Approximation
Yihong Wu,Pengkun Yang +1 more
TL;DR: It is shown that the minimax mean-square error is within the universal multiplicative constant factors of (k/n log k)2 t log2 k/n if n exceeds a constant factor of ( k/log k); otherwise, there exists no consistent estimator.
Proceedings ArticleDOI
Per-packet load-balanced, low-latency routing for clos-based data center networks
Jiaxin Cao,Rui Xia,Pengkun Yang,Chuanxiong Guo,Guohan Lu,Lihua Yuan,Yixin Zheng,Haitao Wu,Yongqiang Xiong,David A. Maltz +9 more
TL;DR: Digit-Reversal Bouncing achieves perfect packet interleaving and results in smaller and bounded queues even when traffic load approaches 100%, and it uses smaller re-sequencing buffer for absorbing out-of-order packet arrivals.
Journal ArticleDOI
Utilization of text mining as a big data analysis tool for food science and nutrition.
Dandan Tao,Pengkun Yang,Hao Feng +2 more
TL;DR: An overview of the data sources, computational methods, and applications of text data in the food industry to provide insights for intelligent decision-making to improve food production, food safety, and human nutrition is provided.
Journal ArticleDOI
Chebyshev polynomials, moment matching, and optimal estimation of the unseen
Yihong Wu,Pengkun Yang +1 more
TL;DR: In this paper, the authors considered the problem of estimating the support size of a discrete distribution whose minimum nonzero mass is at least ε(1/k) and showed that the sample complexity to achieve an additive error with probability at least 0.1 is within universal constant factors.
Journal ArticleDOI
Optimal estimation of Gaussian mixtures via denoised method of moments
Yihong Wu,Pengkun Yang +1 more
TL;DR: By proving new moment comparison theorems in the Wasserstein distance via polynomial interpolation and majorization techniques, this paper establishes the statistical guarantees and adaptive optimality of the proposed procedure, as well as oracle inequality in misspecified models.