Erik M Lindgren
Erik M Lindgren
Graduate Student at University of Texas at Austin
Verified email at utexas.edu - Homepage
Title
Cited by
Cited by
Year
Leveraging sparsity for efficient submodular data summarization
E Lindgren, S Wu, AG Dimakis
Advances in Neural Information Processing Systems, 3414-3422, 2016
20*2016
A rule-based design specification language for synthetic biology
E Oberortner, S Bhatia, E Lindgren, D Densmore
ACM Journal on Emerging Technologies in Computing Systems (JETC) 11 (3), 1-19, 2014
132014
Experimental design for cost-aware learning of causal graphs
E Lindgren, M Kocaoglu, AG Dimakis, S Vishwanath
Advances in Neural Information Processing Systems, 5279-5289, 2018
42018
Conditional sampling from invertible generative models with applications to inverse problems
EM Lindgren, J Whang, AG Dimakis
arXiv preprint arXiv:2002.11743, 2020
12020
Exact MAP inference by avoiding fractional vertices
EM Lindgren, AG Dimakis, A Klivans
arXiv preprint arXiv:1703.02689, 2017
1*2017
Combinatorial optimization for graphical structures in machine learning
EM Lindgren
2019
Accelerating Large-Scale Inference with Anisotropic Vector Quantization
R Guo, P Sun, E Lindgren, Q Geng, D Simcha, F Chern, S Kumar
Rescaled JL Embedding
S Wu, E Lindgren
On Robust Learning of Ising Models
EM Lindgren, V Shah, Y Shen, AG Dimakis, A Klivans
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Articles 1–9