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- Yuheng Bu, Shaofeng Zou, Yingbin Liang, Venugopal V. Veeravalli
- ArXiv
- 2016

The problem of estimating the Kullback-Leibler divergence D(P‖Q) between two unknown distributions P and Q is studied, under the assumption that the alphabet size k of the distributions can scale to infinity. The estimation is based on m independent samples drawn from P and n independent samples drawn from Q. It is first shown that there does not exist any… (More)

- Yuheng Bu, Shaofeng Zou, Yingbin Liang, Venugopal V. Veeravalli
- 2016 IEEE International Symposium on Information…
- 2016

The problem of estimating the KL divergence between two unknown distributions is studied. The alphabet size k of the distributions can scale to infinity. The estimation is based on m and n independent samples respectively drawn from the two distributions. It is first shown that there does not exist any consistent estimator to guarantee asymptotic small… (More)

- Yuheng Bu, Shaofeng Zou, Yingbin Liang, Venugopal V. Veeravalli
- 2016 IEEE International Conference on Acoustics…
- 2016

The following detection problem is studied, in which there are M sequences of samples out of which one outlier sequence needs to be detected. Each typical sequence contains n independent and identically distributed (i.i.d.) continuous observations from a known distribution π, and the outlier sequence contains n i.i.d. observations from an outlier… (More)

- Yuheng Bu, Shaofeng Zou, Venugopal V. Veeravalli
- ArXiv
- 2017

- Yuheng Bu, Shaofeng Zou, Venugopal V. Veeravalli
- 2017 IEEE International Symposium on Information…
- 2017

We study a universal outlying sequence detection problem, in which there are M sequences of samples out of which a small subset of outliers need to be detected. A sequence is considered as an outlier if the observations therein are generated by a distribution different from those generating the observations in the majority of the sequences. In the universal… (More)

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