11 citations · 21 across the 5 of their papers we have counts for
5 papers
Drowning in Documents: Consequences of Scaling Reranker Inference
Mathew Jacob, Erik Lindgren, Matei Zaharia +3
Rerankers, typically cross-encoders, are computationally intensive but are frequently used because they are widely assumed to outperform cheaper initial IR systems. We challenge th…
Composing Normalizing Flows for Inverse Problems
Jay Whang, Erik M. Lindgren, Alexandros G. Dimakis
Given an inverse problem with a normalizing flow prior, we wish to estimate the distribution of the underlying signal conditioned on the observations. We approach this problem as a…
Experimental Design for Cost-Aware Learning of Causal Graphs
Erik M. Lindgren, Murat Kocaoglu, Alexandros G. Dimakis +1
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…
Leveraging Sparsity for Efficient Submodular Data Summarization
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. One difficulty of…
Exact MAP Inference by Avoiding Fractional Vertices
Erik M. Lindgren, Alexandros G. Dimakis, Adam Klivans
Given a graphical model, one essential problem is MAP inference, that is, finding the most likely configuration of states according to the model. Although this problem is NP-hard,…