Berk U.

Cambridge, MA

berkustun.com

Age: 27

I am a Ph.D. student in the Electrical Engineering and Computer Science Department at MIT. I am interested in developing new methods for data-driven decision-making and using them to solve problems in areas such as climate change, crime prediction, healthcare and revenue management.

2h
asked Simplifying a Taylor polynomial that involves Stirling numbers of the second kind
3h
asked Bounding the difference in the value of a strongly convex function at its integer minimum and other integer points
20h
awarded Scholar
20h
accepted Using a Polynomial Time Algorithm for Upper Bound Recognition to Show Polynomial Time for Evaluation?
20h
accepted How to exclude all points adjacent to a given point from the feasible region of IP
20h
accepted Resource Request for a "Most Similar Vector Problem" on an Integer Lattice?
20h
accepted Efficient (sublinear) approximation algorithms for matrix-vector multiplication?
21h
asked Simplifying a Taylor polynomial that involves Stirling numbers of the second kind
Aug
10
awarded Constituent
Aug
10
awarded Caucus
Aug
6
awarded Popular Question
Aug
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awarded Autobiographer
Aug
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comment "Most Similar Vector Problem" on an Integer Lattice?
@AlexR This is really interesting. Would you mind writing it up as an answer so we can discuss it fully?
Aug
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revised "Most Similar Vector Problem" on an Integer Lattice?
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Aug
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comment "Most Similar Vector Problem" on an Integer Lattice?
By original article, are you refering to the one that @Joseph O'Rourke linked?
Aug
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revised "Most Similar Vector Problem" on an Integer Lattice?
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Aug
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comment How to exclude all points adjacent to a given point from the feasible region of IP
@D.W. Actually, you could also remove $y$ from the feasible region. I will reword. When I first wrote the question, I thought that it wasn't a good idea since $y$ might be the optimal solution so the IP would return a different result. That said, we could solve the IP without $\mathcal{A}(y)$ and $y$. In this case, we would know that the solution we obtain is optimal iff it attains an objective that is less than or equal to $c^Ty$.
Aug
1
comment How to exclude all points adjacent to a given point from the feasible region of IP
@D.W. Thanks for the follow up questions! In terms of motivation, I have a procedure that I can use that will return a "locally optimal" solution $y$. The purpose of removing the adjacent points in $\mathcal{A}(y)$ is to reduce the size of the feasible region and improve the lower bound to the objective value that will be produced by a continuous relaxation. I understand that it may require new variables / constraints, but I was looking for a way to do it using as few variables / constraints as possible.
Aug
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revised "Most Similar Vector Problem" on an Integer Lattice?
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Aug
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revised "Most Similar Vector Problem" on an Integer Lattice?
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