Date:30 January 2019, Wednesday
Location:S16-06-118, Seminar Room
Time:03:00pm - 04:00pm
High-Dimensional General Linear Hypothesis Tests via Spectral ShrinkageIn statistics, one of the fundamental inferential problems is to test a general linear hypothesis of regression coefficients under…
Date:23 January 2019, Wednesday
Location:S16-06-118, Seminar Room
Time:03:00pm - 04:00pm
Sorted Concave Penalized RegressionThe Lasso is biased. Concave penalized lease squares estimation (PLSE) takes advantage of signal strength to reduce this bias,…
Date:23 January 2019, Wednesday
Location:S16-06-118, Seminar Room
Time:03:00pm - 04:00pm
Sorted Concave Penalized RegressionThe Lasso is biased. Concave penalized lease squares estimation (PLSE) takes advantage of signal strength to reduce this bias, leading to…
Date:10 December 2018, Monday
Location:S16-06-118, Seminar Room
Time:03:00pm - 04:00pm
Near-Optimality of Bai and Saranadasa’s Test in Moderately Large DimensionsIn a highly influential paper, Bai and Saranadasa (1996) proposed a test for determining equality of means of two normal…
Date:26 November 2018, Monday
Location:S16-06-118, Statistics Seminar Room
Time:02:00pm - 03:00pm
High-Dimensional Time Series Modeling and Forecasting With Application To High-Frequency Financial and Energy DataPHD ORAL PRESENTATION Modern big data contain rich information that can be used to improve the understanding and predictability…
Date:16 November 2018, Friday
Location:S16-05-96, Computer Lab 4
Time:03:00pm - 04:00pm
Geometric MCMC for Bayesian Inverse ProblemsBayesian Inverse Problems often involve sampling posterior distributions on infinite-dimensional function spaces. Traditional Markov chain Monte Carlo (MCMC) algorithms…
Date:15 November 2018, Thursday
Location:S16-06-118, Seminar Room
Time:03:00pm - 04:00pm
Approximate Importance Sampling and Its Implications for Mapping Disease-GenesFor co-segregation studies involving a large number of small affected families and commercially available SNP arrays, it is difficult…
Date:14 November 2018, Wednesday
Location:S16-06-118, Seminar Room
Time:03:00pm - 04:00pm
Frequentist Expectation PropagationExpectation propagation is a technique from computer science for overcoming tractability obstacles in inference for Bayesian graphical models. We…
Date:17 October 2018, Wednesday
Location:S16-06-118, Seminar Room
Time:03:00pm - 04:00pm
From Causal Inference to Gene RegulationA recent break-through in genomics makes it possible to perform perturbation experiments at a very large scale. The availability…
Date:10 October 2018, Wednesday
Location:S16-06-118, Seminar Room
Time:03:00pm - 04:00pm
Phase Transitions for High Dimensional Clustering and Related ProblemsClustering, or unsupervised learning, is a major problem in statistics with many applications. In the Big Data era, it…