標(biāo)題：Nearest-Neighbor Sampling Based Conditional Independence Testing
報(bào)告時(shí)間：2024年5月9日(星期四) 10：00-11：00
報(bào)告地點(diǎn)：線(xiàn)上騰訊會(huì)議（會(huì)議ID：481-989-032）
主講人：諶自奇
主辦單位：數(shù)學(xué)與統(tǒng)計(jì)學(xué)院
報(bào)告內(nèi)容簡(jiǎn)介：
The conditional randomization test (CRT) was recently proposed to test whether two random variables X and Y are conditionally independent given random variables Z. The CRT assumes that the conditional distribution of X given Z is known under the null hypothesis and then it is compared to the distribution of the observed samples of the original data. The aim of this paper is to develop a novel alternative of CRT by using nearest-neighbor sampling without assuming the exact form of the distribution of X given Z. Specifically, we utilize the computationally efficient 1-nearest-neighbor to approximate the conditional distribution that encodes the null hypothesis. Then, theoretically, we show that the distribution of the generated samples is very close to the true conditional distribution in terms of total variation distance. Furthermore, we take the classifier-based conditional mutual information estimator as our test statistic. The test statistic as an empirical fundamental information theoretic quantity is able to well capture the conditional-dependence feature. We show that our proposed test is computationally very fast, while controlling type I and II errors quite well. Finally, we demonstrate the efficiency of our proposed test in both synthetic and real data analyses.
主講人簡(jiǎn)介：
諶自奇，華東師范大學(xué)統(tǒng)計(jì)學(xué)院研究員，博士生導(dǎo)師。博士畢業(yè)于東北師范大學(xué), 曾于2016-2019年在美國(guó)安德森癌癥研究中心生物統(tǒng)計(jì)系從事博士后研究工作。專(zhuān)注復(fù)雜數(shù)據(jù)領(lǐng)域的統(tǒng)計(jì)學(xué)及其交叉科學(xué)研究，研究興趣包含高維矩陣、條件獨(dú)立性檢驗(yàn)、因果結(jié)果學(xué)習(xí)、機(jī)器學(xué)習(xí)、生物統(tǒng)計(jì)學(xué)中的統(tǒng)計(jì)方法等。在JASA、Biometrics、NeurIPS等國(guó)際權(quán)威統(tǒng)計(jì)或者計(jì)算機(jī)期刊（會(huì)議）上發(fā)表論文20多篇。主持國(guó)家自然科學(xué)基金面上項(xiàng)目2項(xiàng)、國(guó)家自然科學(xué)基金重點(diǎn)項(xiàng)目（子課題）1項(xiàng)，國(guó)家自然科學(xué)基金青年項(xiàng)目1項(xiàng)等，作為骨干力量參與國(guó)家重點(diǎn)研發(fā)計(jì)劃和上海市“科技創(chuàng)新行動(dòng)計(jì)劃”基礎(chǔ)研究領(lǐng)域應(yīng)用數(shù)學(xué)重點(diǎn)項(xiàng)目。
