27 citations · 40 across the 13 of their papers we have counts for
4 papers · 1 filter
Sampling Constraint Satisfaction Solutions in the Local Lemma Regime
Weiming Feng, Kun He, Yitong Yin
We give a Markov chain based algorithm for sampling almost uniform solutions of constraint satisfaction problems (CSPs). Assuming a canonical setting for the Lovász local lemma, wh…
Probability Learning based Tabu Search for the Budgeted Maximum Coverage Problem
Liwen Li, Zequn Wei, Jin-Kao Hao +1
Knapsack problems are classic models that can formulate a wide range of applications. In this work, we deal with the Budgeted Maximum Coverage Problem (BMCP), which is a generalize…
Stochastic Item Descent Method for Large Scale Equal Circle Packing Problem
Kun He, Min Zhang, Jianrong Zhou +2
Stochastic gradient descent (SGD) is a powerful method for large-scale optimization problems in the area of machine learning, especially for a finite-sum formulation with numerous…
Adaptive Large Neighborhood Search for Circle Bin Packing Problem
Kun He, Kevin Tole, Fei Ni +2
We address a new variant of packing problem called the circle bin packing problem (CBPP), which is to find a dense packing of circle items to multiple square bins so as to minimize…