Harnessing the Power of Latent Structure Models and Modern Big Data learning
Videos from IASM Workshop
Jianqing Fan, Princeton University
Monday Dec 11, 2023 09:00 - 09:40
Ranking inferences based on the top choice of multiway comparisons
Xihong Lin, Harvard University
Monday Dec 11, 2023 09:40 - 10:20
Ensemble testing of global null hypotheses with applications to whole genome sequencing studies
Ji Zhu, University of Michigan
Monday Dec 11, 2023 11:00 - 11:30
A latent space model for hypergraphs with diversity and heterogeneous popularity
Yumou Qiu, Peking University
Monday Dec 11, 2023 11:30 - 12:00
Optimal signal detection in covariance and precision matrices
Geoff McLachlan, University of Queen’sland
Monday Dec 11, 2023 14:00 - 14:30
An apparent paradox in semi-supervised learning
Adel Javanmard, University of Southern California
Monday Dec 11, 2023 14:30 - 15:00
Adversarial robustness for latent models: Revisiting the robust-standard accuracies tradeoff
Lixing Zhu, Beijing Normal University/Hong Kong Baptist University
Monday Dec 11, 2023 15:30 - 16:00
Change point detection for tensors with heterogeneous slices
Weixin Yao, University of California, Riverside
Monday Dec 11, 2023 16:00 - 16:30
Semiparametric mixture of regression with unspecified error distributions
Jiaying Gu, University of Toronto
Monday Dec 11, 2023 16:30 - 17:00
Identification of dynamic panel logit models with fixed effects
Jiashun Jin, Carnegie Mellon University
Tuesday Dec 12, 2023 09:00 - 09:30
Learning and Rranking Research Topics in Statistics
Paromita Dubey, University of Southern California
Tuesday Dec 12, 2023 09:30 - 10:00
Two sample inference for random objects using depth profiles
Tracy Ke, Harvard University
Tuesday Dec 12, 2023 10:00 - 10:30
Text analysis and testing of high-dimensional multinomials
Nikolaos Ignatiadis, University of Chicago
Tuesday Dec 12, 2023 11:00 - 11:30
Empirical partially Bayes multiple testing and compound χ² decisions
Zhigang Yao, National University of Singapore
Tuesday Dec 12, 2023 11:30 - 12:00
Manifold fitting with CycleGAN
Yan Shuo Tan, National University of Singapore
Tuesday Dec 12, 2023 13:30 - 14:00
The computational curse of big data for Bayesian additive regression trees: A hitting time analysis
Wanjie Wang, National University of Singapore
Tuesday Dec 12, 2023 14:00 - 14:30
Network-guided covariate selection and downstream applications
Xin Tong, University of Southern California
Tuesday Dec 12, 2023 14:30 - 15:00
Neyman-Pearson and equal opportunity: when efficiency meets fairness in classification
Richard Samworth, University of Cambridge
Tuesday Dec 12, 2023 15:30 - 16:00
Isotonic subgroup selection
Po-Ling Loh, University of Cambridge
Tuesday Dec 12, 2023 16:00 - 16:30
Differentially private penalized M-estimation via noisy optimization
Axel Munk, Institute of Mathematical Stochastics, Goettingen
Tuesday Dec 12, 2023 16:30 - 17:00
Transport dependency: Optimal transport-based dependency measures
Florentina Bunea, Cornell
Wednesday Dec 13, 2023 09:00 - 09:30
Inference for the Wasserstein distance between mixing measures in topic models
Weijie Su, Wharton School, University of Pennsylvnania
Wednesday Dec 13, 2023 09:30 - 10:00
Gaussian differential privacy and how to enhance census data privacy for free
Nhat Ho, The University of Texas, Austin
Wednesday Dec 13, 2023 10:00 - 10:30
Demystifying softmax gating Gaussian mixture of experts
Xuening Zhu, Fudan University
Wednesday Dec 13, 2023 10:50 - 11:20
Network autoregression for incomplete matrix-valued time series
Wenguang Sun, Zhejiang University
Wednesday Dec 13, 2023 11:20 - 11:50
Large-scale inference on heteroscedastic units
Ping Ma, University of Georgia Athens
Wednesday Dec 13, 2023 11:50 - 12:30
Subsampling in large networks
Marten Wegkamp, Cornell University
Thursday Dec 14, 2023 09:00 - 09:30
Discriminant analysis in high-dimensional Gaussian mixtures
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Thursday Dec 14, 2023 09:30 - 10:00
Homogeneity pursuit in ranking inferences based on pairwise comparison data
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Thursday Dec 14, 2023 10:00 - 10:30
Optimal nonparametric inference with two-scale distributional nearest neighbors
Wei Lin, Peking University
Thursday Dec 14, 2023 11:00 - 11:30
Nonasymptotic theory for two-layer neural networks: Beyond the bias-variance trade-off
Lan Gao, The University of Tennessee Knoxville
Thursday Dec 14, 2023 11:30 - 12:00
Robust knockoff inference with coupling
Qiong Zhang, Renmin University of China
Thursday Dec 14, 2023 13:30 - 14:00
Distributed learning of finite mixture models
Jinchi Lv, University of Southern California
Thursday Dec 14, 2023 14:00 - 14:30
SOFARI: High-dimensional manifold-based inference
Puying Zhao, Yunnan University
Thursday Dec 14, 2023 15:00 - 15:30
Augmented two-step estimating equations with nuisance functionals and complex survey data
Jyoti U. Devkota, Kathmandu University
Thursday Dec 14, 2023 15:30 - 16:00
Identification of latent structures in qualitative variables – Examples from renewable energy users of Nepal
Yukun Liu, Each China Normal University
Thursday Dec 14, 2023 16:30 - 17:00
Navigating challenges in classification and outlier detection: a remedy based on semi-parametric density ratio models
Abbas Khalili, McGill University
Friday Dec 15, 2023 09:00 - 09:30
Estimation and Sparsity in overfitted mixture-of-experts (MOE) models
Yun Wei, Duke University
Friday Dec 15, 2023 09:30 - 10:00
Parameter Estimations in Finite Mixture Models
Pengfei Li, University of Waterloo
Friday Dec 15, 2023 10:00 - 10:30
Maximum binomial likelihood for multivariate mixture data
Special Notice:
The videos for IASM workshop 23w5009 are available here: http://videos.birs.ca/2023/23w5009/.
