We study a new connection between a technical measure called -conductance that arises in the study of Markov chains for sampling convex bod-.
Mar 25, 2023 · We derive a sequence of optimization problems including a low-rank semi-definite program from which we can derive a lower bound on the optimal \ ...
We study a new connection between a technical measure called 𝜇-conductance that arises in the study of Markov chains for sampling convex bod-.
Jul 23, 2023 · We derive a sequence of optimization problems including a low-rank semidefinite program from which we can derive a lower bound on the optimal µ- ...
We derive a sequence of optimization problems including a low-rank semi-definite program from which we can derive a lower bound on the optimal $\mu$-conductance ...
Table 2.1: upper bounds on the minimum rank of a solution of (SDP) space has ... generating lower bounds actually produces tight lower bounds in many.
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x-axis is the ranks ranging from 1 to 2x the theoretical rank upper-bound (. √. 2n). Experiments suggests that a very low rank (≤ 5) is sufficeint to ...
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One celebrated method for solving these problems is to formulate and solve a semidefinite program (SDP). It is often known that the exact solution to the SDP ...
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Mar 1, 2023 · Yufan Huang, C. Seshadhri. Theoretical bounds on the network community profile from low-rank semi-definite programming. International Conference ...
Semidefinite programming is a relatively new field of optimization which is of growing interest for several reasons. Many practical problems in operations ...