Eva L. Dyer
TitleCited byYear
Greedy feature selection for subspace clustering
EL Dyer, AC Sankaranarayanan, RG Baraniuk
Journal of Machine Learning Research 14 (1), 2487-2517, 2013
Rapid FPGA characterzation using clock synthesis and signal sparsity
M Majzoobi, E Dyer, A Elnably, F Koushanfar
IEEE International Test Conference (ITC), Austin, TX, 2010
Quantifying mesoscale neuroanatomy using x-ray microtomography
EL Dyer, WG Roncal, JA Prasad, HL Fernandes, D Gürsoy, V De Andrade, ...
Eneuro 4 (5), 2017
Low-dose x-ray tomography through a deep convolutional neural network
X Yang, V De Andrade, W Scullin, EL Dyer, N Kasthuri, F De Carlo, ...
Scientific reports 8 (1), 1-13, 2018
Self-expressive decompositions for matrix approximation and clustering
EL Dyer, TA Goldstein, R Patel, KP Kording, RG Baraniuk
arXiv preprint arXiv:1505.00824, 2015
Deterministic Column Sampling for Low-Rank Matrix Approximation: Nyström vs. Incomplete Cholesky Decomposition
R Patel, T Goldstein, E Dyer, A Mirhoseini, R Baraniuk
Proceedings of the 2016 SIAM International Conference on Data Mining, 594-602, 2016
Latent factors and dynamics in motor cortex and their application to brain–machine interfaces
C Pandarinath, KC Ames, AA Russo, A Farshchian, LE Miller, EL Dyer, ...
Journal of Neuroscience 38 (44), 9390-9401, 2018
RankMap: A Framework for Distributed Learning From Dense Data Sets
A Mirhoseini, EL Dyer, EM Songhori, R Baraniuk, F Koushanfar
IEEE transactions on neural networks and learning systems 29 (7), 2717-2730, 2017
A robust and efficient method to recover neural events from noisy and corrupted data
EL Dyer, C Studer, JT Robinson, RG Baraniuk
2013 6th International IEEE/EMBS Conference on Neural Engineering (NER), 593-596, 2013
Validation system of MR image overlay and other needle insertion techniques
JD Westwood
Medicine Meets Virtual Reality 15: In Vivo, in Vitro, in Silico: Designing …, 2007
Recovering spikes from noisy neuronal calcium signals via structured sparse approximation
EL Dyer, MF Duarte, DH Johnson, RG Baraniuk
International Conference on Latent Variable Analysis and Signal Separation …, 2010
A cryptography-based approach for movement decoding
EL Dyer, MG Azar, MG Perich, HL Fernandes, S Naufel, LE Miller, ...
Nature biomedical engineering 1 (12), 967-976, 2017
Approximating cellular densities from high-resolution neuroanatomical imaging data
TJ LaGrow, MG Moore, JA Prasad, MA Davenport, EL Dyer
2018 40th Annual International Conference of the IEEE Engineering in …, 2018
Subspace clustering with dense representations
EL Dyer, C Studer, RG Baraniuk
2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013
Generative models and abstractions for large-scale neuroanatomy datasets
D Rolnick, EL Dyer
Current opinion in neurobiology 55, 112-120, 2019
An automated pipeline for the collection, transfer, and processing of large-scale tomography data
M Du, R Vescovi, R Chard, N Kasthuri, C Jacobsen, E Dyer, D Gürsoy
Optics and the Brain, BF4C. 2, 2018
Endogenous sparse recovery
EL Dyer
Hybrid modeling of non-stationary process variations
E Dyer, M Majzoobi, F Koushanfar
Proceedings of the 48th Design Automation Conference, 194-199, 2011
Large-scale neuroanatomy using LASSO: loop-based automated serial sectioning operation
TJ Lee, A Kumar, AH Balwani, D Brittain, S Kinn, CA Tovey, EL Dyer, ...
PloS one 13 (10), 2018
Convex relaxation regression: Black-box optimization of smooth functions by learning their convex envelopes
MG Azar, E Dyer, K Kording
arXiv preprint arXiv:1602.02191, 2016
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Articles 1–20