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Faculty of Mathematics

 

Seminars taking place at the Isaac Newton Institute as advertised through www.talks.cam.ac.uk, are listed below.

Separate pages listing these seminars are available from the institute website.

Monday 25 June 2018

Iain Johnstone (Stanford University)
tba STSW04 - Future challenges in statistical scalability

Iain Johnstone (Stanford University)
Eigenstructure in high dimensional random effects models STSW04 - Future challenges in statistical scalability

Spyros Skoulakis (KPMG)
Managing Model Risk in Banking UNQ - Uncertainty quantification for complex systems: theory and methodologies

Philippe Rigollet (Massachusetts Institute of Technology)
tba STSW04 - Future challenges in statistical scalability

Philippe Rigollet (Massachusetts Institute of Technology)
Uncoupled isotonic regression via minimum Wasserstein deconvolution STSW04 - Future challenges in statistical scalability

Matthew Stephens (University of Chicago)
On applications of Empirical Bayes approaches to the Normal Means problem STSW04 - Future challenges in statistical scalability

Matthew Stephens (University of Chicago)
On applications of Empirical Bayes approaches to the Normal Means problem STSW04 - Future challenges in statistical scalability

Jana Jankova (University of Cambridge)
tba STSW04 - Future challenges in statistical scalability

Jana Jankova (University of Cambridge)
Asymptotic Inference for Eigenstructure of Large Covariance Matrices STSW04 - Future challenges in statistical scalability

Flori Bunea (Cornell University)
tba STSW04 - Future challenges in statistical scalability

Flori Bunea (Cornell University)
A fast algorithm with minimax optimal guarantees for topic models with an unknown number of topics STSW04 - Future challenges in statistical scalability

Tuesday 26 June 2018

Guy Bresler (Massachusetts Institute of Technology)
Reducibility and Computational Lower Bounds for Problems with Planted Sparse Structure STSW04 - Future challenges in statistical scalability

Chao Gao (University of Chicago)
Reduced Isotonic Regression STSW04 - Future challenges in statistical scalability

Ryan Tibshirani (Carnegie Mellon University)
Dykstra’s Algorithm, ADMM, and Coordinate Descent: Connections, Insights, and Extensions STSW04 - Future challenges in statistical scalability

Peter Bickel (University of California, Berkeley)
Two network scale challenges:Constructing and fitting hierarchical block models and fitting large block models using the mean field method STSW04 - Future challenges in statistical scalability

Marten Herman Wegkamp (Cornell University)
Adaptive estimation of the rank of the regression coefficient matrix STSW04 - Future challenges in statistical scalability

Maryam Fazel (University of Washington)
Competitive Online Algorithms for Budgeted Allocation with Application to Online Experiment Design STSW04 - Future challenges in statistical scalability

Alex d'Aspremont (CNRS - Ecole Normale Superieure Paris)
An Approximate Shapley-Folkman Theorem. STSW04 - Future challenges in statistical scalability

Wednesday 27 June 2018

Urvashi Oswal (University of Wisconsin-Madison)
Selection and Clustering of Correlated variables using OWL/GrOWL regularizers STSW04 - Future challenges in statistical scalability

Elizaveta Levina (University of Michigan)
Matrix completion in network analysis STSW04 - Future challenges in statistical scalability

Garvesh Raskutti (University of Wisconsin-Madison)
Estimating sparse additive auto-regressive network models STSW04 - Future challenges in statistical scalability

Peter Bartlett (University of California, Berkeley)
Representation, optimization and generalization properties of deep neural networks STSW04 - Future challenges in statistical scalability

Thursday 28 June 2018

Tong Zhang (Rutgers, The State University of New Jersey)
Candidates vs. Noises Estimation for Large Multi-Class Classification Problem STSW04 - Future challenges in statistical scalability

Aurore Delaigle (University of Melbourne)
Estimating a covariance function from fragments of functional data STSW04 - Future challenges in statistical scalability