Search Results for author: Erik M. Lindgren

Found 4 papers, 0 papers with code

Composing Normalizing Flows for Inverse Problems

no code implementations26 Feb 2020 Jay Whang, Erik M. Lindgren, Alexandros G. Dimakis

We approach this problem as a task of conditional inference on the pre-trained unconditional flow model.

Compressive Sensing Variational Inference

Experimental Design for Cost-Aware Learning of Causal Graphs

no code implementations NeurIPS 2018 Erik M. Lindgren, Murat Kocaoglu, Alexandros G. Dimakis, Sriram Vishwanath

We consider the minimum cost intervention design problem: Given the essential graph of a causal graph and a cost to intervene on a variable, identify the set of interventions with minimum total cost that can learn any causal graph with the given essential graph.

Experimental Design

Exact MAP Inference by Avoiding Fractional Vertices

no code implementations ICML 2017 Erik M. Lindgren, Alexandros G. Dimakis, Adam Klivans

We require that the number of fractional vertices in the LP relaxation exceeding the optimal solution is bounded by a polynomial in the problem size.

Leveraging Sparsity for Efficient Submodular Data Summarization

no code implementations NeurIPS 2016 Erik M. Lindgren, Shanshan Wu, Alexandros G. Dimakis

The facility location problem is widely used for summarizing large datasets and has additional applications in sensor placement, image retrieval, and clustering.

Data Summarization Image Retrieval +1

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