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Principal components analysis (PCA) is a well-known technique for approximating a data set represented by a matrix by a low rank matrix. Here, we extend the idea of PCA to handle arbitrary data sets…
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In this talk, we study two different diffusion models on the random graphs. In the first part, we
consider first passage percolation. We analyze the impact of the edge weights on distances
in…
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Continuous optimization is a key component of modern data analysis. Recently, the demands
of extremely large-scale applications have shifted the focus from high cost, high accuracy
methods to low…
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Variational analysis has come of age. Long an elegant theoretical toolkit for variational mathematics and nonsmooth optimization, it now increasingly underpins the study of algorithms, and a rich…
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Monday, May 5
3 p.m. – Presentation – 253 Rhodes Hall
Suvrit Sra
Inexactness, geometry, and optimization: recurrent themes in modern data analysis
The current data-age is…
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Friday, May 2
2:20 p.m. – Presentation – 253 Rhodes Hall
Philippe Rigollet
The statistical price to pay for computational efficiency in sparse PCA
Computational limitations of…
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Tuesday, February 4, 2014 at 4:15pm
Upson Hall, B17
ORIE Colloquium: John Duchi (UC Berkeley) - Machine Learning: a Discipline of Resource Tradeoffs
Joint colloquium with Computer Science.
How…
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Tuesday, May 6, 2014 at 4:15 PM [.ics]
253 Rhodes Hall
Alexander (Sasha) Rakhlin
Assistant Professor, Department of Statistics
Secondary appointment: Department of Computer & Information…
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Tuesday, September 30, 2014
The last few years have seen an increasing interest in utilizing optimization for large-scale data analysis. However, optimization problems arising from these…
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Proponents of robust optimization typically make three claims concerning the value of the robust approach. The first is that robust optimization models lead to solutions whose expected cost is close…
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Many operational problems in data-rich environments can be characterized by three primitives: data on uncertain quantities of interest such as simultaneous demands, concurrent auxiliary data such as…
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We consider customer service chat systems where customers can receive real time service from agents using an instant messaging application over the Internet. A unique feature of these systems is that…
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In many practical situations one has to make decisions sequentially based on data available at the time of the decision and facing uncertainty of the future. This leads to optimization problems which…
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Multidisciplinary Design refers to design projects in which multiple teams, typically with
different disciplines or expertise, design different subsystems of an overall system.
Usually,…
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