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2020 – today
- 2024
[i6]Jason Moore, Alexander Genkin, Magnus Tournoy, Joshua Pughe-Sanford, Robert R. de Ruyter van Steveninck, Dmitri B. Chklovskii:
The Neuron as a Direct Data-Driven Controller. CoRR abs/2401.01489 (2024)- 2022
- [c11]Alexander Genkin, David Lipshutz, Siavash Golkar, Tiberiu Tesileanu, Dmitri B. Chklovskii:
Biological Learning of Irreducible Representations of Commuting Transformations. NeurIPS 2022 - 2021
- [c10]Johannes Friedrich, Siavash Golkar, Shiva Farashahi, Alexander Genkin, Anirvan M. Sengupta, Dmitri B. Chklovskii:
Neural optimal feedback control with local learning rules. NeurIPS 2021: 16358-16370 - [i5]Johannes Friedrich, Siavash Golkar, Shiva Farashahi, Alexander Genkin, Anirvan M. Sengupta, Dmitri B. Chklovskii:
Neural optimal feedback control with local learning rules. CoRR abs/2111.06920 (2021)
2010 – 2019
- 2019
- [c9]Alexander Genkin, Anirvan M. Sengupta, Dmitri B. Chklovskii:
A Neural Network for Semi-supervised Learning on Manifolds. ICANN (1) 2019: 375-386 - [i4]Alexander Genkin, Anirvan M. Sengupta, Dmitri B. Chklovskii:
A Neural Network for Semi-Supervised Learning on Manifolds. CoRR abs/1908.08145 (2019) - 2018
- [c8]Anirvan M. Sengupta, Cengiz Pehlevan, Mariano Tepper, Alexander Genkin, Dmitri B. Chklovskii:
Manifold-tiling Localized Receptive Fields are Optimal in Similarity-preserving Neural Networks. NeurIPS 2018: 7080-7090 - 2017
- [c7]Cengiz Pehlevan
, Alexander Genkin, Dmitri B. Chklovskii:
A clustering neural network model of insect olfaction. ACSSC 2017: 593-600 - 2016
- [i3]Ilya Trofimov, Alexander Genkin:
Distributed Coordinate Descent for Generalized Linear Models with Regularization. CoRR abs/1611.02101 (2016) - 2015
- [c6]Ilya Trofimov, Alexander Genkin:
Distributed Coordinate Descent for L1-regularized Logistic Regression. AIST 2015: 243-254 - 2014
- [i2]Ilya Trofimov, Alexander Genkin:
Distributed Coordinate Descent for L1-regularized Logistic Regression. CoRR abs/1411.6520 (2014) - 2013
- [c5]Tao Hu, Zaid J. Towfic, Cengiz Pehlevan, Alex V. Genkin, Dmitri B. Chklovskii:
A neuron as a signal processing device. ACSSC 2013: 362-366 - 2012
- [j3]Tao Hu, Alexander Genkin, Dmitri B. Chklovskii:
A Network of Spiking Neurons for Computing Sparse Representations in an Energy-Efficient Way. Neural Comput. 24(11): 2852-2872 (2012) - [i1]Tao Hu, Alexander Genkin, Dmitri B. Chklovskii:
A network of spiking neurons for computing sparse representations in an energy efficient way. CoRR abs/1210.1530 (2012) - 2010
- [c4]Ashok Veeraraghavan, Alex V. Genkin, Shiv Naga Prasad Vitaladevuni, Lou Scheffer, Shan Xu, Harald F. Hess, Richard Fetter, Marco Cantoni, Graham Knott, Dmitri B. Chklovskii:
Increasing depth resolution of electron microscopy of neural circuits using sparse tomographic reconstruction. CVPR 2010: 1767-1774
2000 – 2009
- 2007
- [j2]Alexander Genkin, David D. Lewis, David Madigan:
Large-Scale Bayesian Logistic Regression for Text Categorization. Technometrics 49(3): 291-304 (2007) - 2006
- [c3]Aynur A. Dayanik, David D. Lewis, David Madigan, Vladimir Menkov, Alexander Genkin:
Constructing informative prior distributions from domain knowledge in text classification. SIGIR 2006: 493-500 - 2005
- [c2]Aynur A. Dayanik, Alexander Genkin, Paul B. Kantor, David D. Lewis, David Madigan:
DIMACS at the TREC 2005 Genomics Track. TREC 2005 - 2004
- [c1]Aynur A. Dayanik, Dmitriy Fradkin, Alexander Genkin, Paul B. Kantor, David Madigan, David D. Lewis, Vladimir Menkov:
DIMACS at the TREC 2004 Genomics Track. TREC 2004 - 2002
- [j1]Alexander Genkin, Casimir A. Kulikowski, Ilya B. Muchnik:
Set covering submodular maximization: An optimal algorithm for data mining in bioinformatics and medical informatics. J. Intell. Fuzzy Syst. 12(1): 5-17 (2002)
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