Now We’re Talking: Better Deliberation Groups through Submodular Optimization

“Talking It Out”: Deliberation With Others versus Deliberation Within

Sensor Array Design Through Submodular Optimization

We consider the problem of far-field sensing by means of a sensor array. Traditional array geometry design techniques are agnostic to prior information about the far-field scene. However, in many applications such priors are available and may be utilized to design more efficient array topologies. We formulate the problem of array geometry design with scene prior as one of finding a sampling con...

Submodular Optimization with Submodular Cover and Submodular Knapsack Constraints

We investigate two new optimization problems — minimizing a submodular function subject to a submodular lower bound constraint (submodular cover) and maximizing a submodular function subject to a submodular upper bound constraint (submodular knapsack). We are motivated by a number of real-world applications in machine learning including sensor placement and data subset selection, which require ...

Efficient Algorithms for Non-convex Isotonic Regression through Submodular Optimization

We consider the minimization of submodular functions subject to ordering constraints. We show that this optimization problem can be cast as a convex optimization problem on a space of uni-dimensional measures, with ordering constraints corresponding to first-order stochastic dominance. We propose new discretization schemes that lead to simple and efficient algorithms based on zero-th, first, or...

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