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STATSCALE PREVIOUS SEMINARS

Talks 2023 

10th March - Marvin Borsch (University of Cologne)

Title: Consistent Estimation of Multiple Breakpoints in Dependence Measures

24th February 2023 - Haotian Xu (Pennsylvania State University)

Title: Online network change point detection with missing values

10th February 2023 - Zifeng Zhao (University of Notre Dame)

Title: High-Dimensional Dynamic Pricing under Non-Stationarity: Learning and Earning with Change-Point Detection

27th January 2023 - Shubhadeep Chakraborty (University of Washington / Bristol Myers Squibb)

Title: High-dimensional change-point detection using generalized homogeneity metrics

Talks 2022

 

2nd December 2022 - Euan McGonigle (University of Bristol)

Title: Nonparametric Change Point Detection for Multivariate Time Series

18th November 2022 - Xianyang Zhang (Texas A&M University)

Title: Sequential Gradient Descent and Quasi-Newton's Method for Change-Point Analysis

 

4th November 2022 - Chao Gao (University of Chicago)

Title: Detection and Recovery of Sparse Signal Under Correlation

 

21st October 2022 - Alessia Caponera (École Polytechnique Fédérale de Lausanne)

Title: Statistical inference for time-varying functional autoregressive processes on the sphere

10th June 2022 - Renate Meyer (University of Auckland)

Title: Bayesian Spectral Analysis with Applications to Gravitational Wave Astronomy

27th May 2022 - Ichiro Takeuchi (Nagoya University)

Title: More powerful and general conditional selective inference by parametric programming and its application to change-point detection and image segmentation.

13th May 2022 - Philipp Klein (Otto von Guericke University Magdeburg)

Title: Anomaly detection based on MOSUM statistics in large image data

22nd April 2022- Daren Wang (Notre Dame)

Optimal High-dimensional Change Point Testing in Regression Settings

18th March 2022 - Lan Luo (University of Iowa)

Real-Time Regression Analysis with Streaming Health Datasets

 

4th March 2022 - Bouchra Nasri (University of Montreal)

Change-Point Problems For Multivariate Time Series Using Pseudo-Observations

25th February 2022 - Yajun Mei (Georgia Tech)

Bandit multi-stream sequential change-point detection

 

 

4th February 2022 - Karl Hallgren (Imperial College London)

Bayesian changepoint models motivated by cyber security applications

21st January 2022 - Jacob Bien (University of Southern California)

Mixture of Multivariate Regressions Modeling for Oceanographic Flow Cytometry Data

Talks 2021

3 December 2021 - Housen Li (University of Göttingen)

Distributional limits of graph cuts on discretized samples

 

19 November 2021 - Guo Yu (University of California, Santa Barbara)

Reluctant interaction modeling in generalized linear models

5 November 2021- Francesco Sanna Passino (Imperial College London)

Mutually exciting point process graphs for modelling dynamic networks

22 October 2021- Ichiro Takeuchi (Nagoya Institute of Technology)

More powerful and general conditional selective inference by parametric programming and its application to multi-dimensional change-point detection

2 July 2021 - Kevin Lin (University of Pennsylvania)

Time-varying stochastic block models, with application to understanding the dynamics of gene co-expression

18 June 2021 - Runmin Wang (Southern Methodist University)

Dating the Break in High Dimensional Data


 

4 June 2021 -  Abolfazl Safikhani (University of Florida)

Multiple Change Point Detection in Reduced Rank High Dimensional Vector Autoregressive Models


 

21th May 2021 - Hao Ni (University College London)

Sig-Wasserstein Generative models to generate realistic synthetic time series

7th May 2021 - Lynna Chu (Iowa State University)

Sequential Change-point Detection for High-Dimensional and non-Euclidean Data


 

26th March 2021 - Hao Chen (UC Davis)

A universal event detection framework for neuropixels data

 


 

12th March 2021 - Sumanta Basu (Cornell University)

Learning Financial Networks with Graphical Models of Time Series Data

26th February 2021 - Eric Kolaczyk (Boston University)

How hard is it to work with a network `average'?

12th February 2021 - Matteo Barigozzi (Università di Bologna)
Quasi Maximum Likelihood Estimation and Inference of Large Approximate Dynamic Factor Models via the EM algorithm

29th January 2021 - Holger Dette (Ruhr-Universitaet Bochum)

Testing Relevant Hypotheses in Functional Time Series via Self-Normalization

Talks 2020

4th December 2020 - Priyanga Dilini Talagala (University of Moratuwa)

Anomaly Detection in Streaming Time Series Data

 

 

20th November 2020 - Florian Pein (University of Cambridge)

About the loss function for cross-validation in change-point regression

 

 

6th November 2020 - Alex Aue (UC Davis)

Random matrix theory aids statistical inference in high dimensions

 

 

23rd October 2020 - Yoav Zemel (University of Cambridge)

Probabilistic approximations to optimal transport

 

 

9th October 2020 - Solt Kovacs (ETH Zurich)

Optimistic search strategy: change point detection for large-scale data via adaptive logarithmic queries

 

 

17th July 2020 - Tobias Kley (University of Bristol)

A new approach for open-end sequential change point monitoring

 

 

3rd July, 2020 - Claudia Kirch (Otto-von-Guericke University)

Functional change point detection for fMRI data 

 

 

19th June, 2020 - Martin Tveten (Dept. of Mathematics, University of Oslo)

Scalable changepoint and anomaly detection in cross-correlated data

 

 

5th June, 2020 - Yudong Chen (University of Cambridge)

High-dimensional, multiscale online changepoint detection

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