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Seminars (STSW04)

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Event When Speaker Title Presentation Material
STSW04 25th June 2018
11:00 to 11:45
Iain Johnstone Eigenstructure in high dimensional random effects models
STSW04 25th June 2018
11:45 to 12:30
Philippe Rigollet Uncoupled isotonic regression via minimum Wasserstein deconvolution
STSW04 25th June 2018
14:00 to 14:45
Matthew Stephens On applications of Empirical Bayes approaches to the Normal Means problem
STSW04 25th June 2018
14:45 to 15:30
Jana Jankova Asymptotic Inference for Eigenstructure of Large Covariance Matrices
STSW04 25th June 2018
16:00 to 16:45
Flori Bunea A fast algorithm with minimax optimal guarantees for topic models with an unknown number of topics
STSW04 26th June 2018
09:00 to 09:45
Guy Bresler Reducibility and Computational Lower Bounds for Problems with Planted Sparse Structure
STSW04 26th June 2018
09:45 to 10:30
Chao Gao Reduced Isotonic Regression
STSW04 26th June 2018
11:00 to 11:45
Ryan Tibshirani Dykstra’s Algorithm, ADMM, and Coordinate Descent: Connections, Insights, and Extensions
STSW04 26th June 2018
11:45 to 12:30
Peter Bickel Two network scale challenges:Constructing and fitting hierarchical block models and fitting large block models using the mean field method
STSW04 26th June 2018
14:00 to 14:45
Marten Herman Wegkamp Adaptive estimation of the rank of the regression coefficient matrix
STSW04 26th June 2018
14:45 to 15:30
Maryam Fazel Competitive Online Algorithms for Budgeted Allocation with Application to Online Experiment Design
STSW04 26th June 2018
16:00 to 16:45
Alex d'Aspremont An Approximate Shapley-Folkman Theorem.
STSW04 27th June 2018
09:00 to 09:45
Urvashi Oswal Selection and Clustering of Correlated variables using OWL/GrOWL regularizers
STSW04 27th June 2018
09:45 to 10:30
Elizaveta Levina Matrix completion in network analysis
STSW04 27th June 2018
11:00 to 11:45
Garvesh Raskutti Estimating sparse additive auto-regressive network models
STSW04 27th June 2018
11:45 to 12:30
Peter Bartlett Representation, optimization and generalization properties of deep neural networks
STSW04 28th June 2018
09:00 to 09:45
Tong Zhang Candidates vs. Noises Estimation for Large Multi-Class Classification Problem
STSW04 28th June 2018
09:45 to 10:30
Aurore Delaigle Estimating a covariance function from fragments of functional data
STSW04 28th June 2018
11:00 to 11:45
Francis Bach Statistical Optimality of Stochastic Gradient Descent on Hard Learning Problems through Multiple Passes
STSW04 28th June 2018
11:45 to 12:30
Edward Ionides Monte Carlo adjusted profile likelihood, with applications to spatiotemporal and phylodynamic inference.
STSW04 28th June 2018
14:00 to 14:45
Jinchi Lv Asymptotics of Eigenvectors and Eigenvalues for Large Structured Random Matrices
STSW04 28th June 2018
14:45 to 15:30
Rui Castro Are there needles in a (moving) haystack? Adaptive sensing for detection and estimation of static and dynamically evolving signals
STSW04 28th June 2018
16:00 to 16:45
Pradeep Ravikumar Robust Estimation via Robust Gradient Estimation
STSW04 29th June 2018
09:00 to 09:45
Alexandre Tsybakov Does data interpolation contradict statistical optimality?
STSW04 29th June 2018
09:45 to 10:30
Vincent Vu Group invariance and computational sufficiency
STSW04 29th June 2018
11:00 to 11:45
Richard Samworth Data perturbation for data science
STSW04 29th June 2018
11:45 to 12:30
Domagoj Ćevid, Peter Bühlmann Deconfounding using Spectral Transformations
University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons