| The loss surfaces of multilayer networks A Choromanska, M Henaff, M Mathieu, GB Arous, Y LeCun Artificial intelligence and statistics, 192-204, 2015 | 1059 | 2015 |
| Deep learning with elastic averaging SGD S Zhang, A Choromanska, Y LeCun arXiv preprint arXiv:1412.6651, 2014 | 470 | 2014 |
| Entropy-sgd: Biasing gradient descent into wide valleys P Chaudhari, A Choromanska, S Soatto, Y LeCun, C Baldassi, C Borgs, ... Journal of Statistical Mechanics: Theory and Experiment 2019 (12), 124018, 2019 | 380 | 2019 |
| Explaining how a deep neural network trained with end-to-end learning steers a car M Bojarski, P Yeres, A Choromanska, K Choromanski, B Firner, L Jackel, ... arXiv preprint arXiv:1704.07911, 2017 | 277 | 2017 |
| Open problem: The landscape of the loss surfaces of multilayer networks A Choromanska, Y LeCun, GB Arous Conference on Learning Theory, 1756-1760, 2015 | 99 | 2015 |
| Logarithmic time online multiclass prediction A Choromanska, J Langford arXiv preprint arXiv:1406.1822, 2014 | 73 | 2014 |
| Visualbackprop: visualizing cnns for autonomous driving M Bojarski, A Choromanska, K Choromanski, B Firner, L Jackel, U Muller, ... arXiv preprint arXiv:1611.05418 2, 2016 | 54 | 2016 |
| Fast spectral clustering via the nyström method A Choromanska, T Jebara, H Kim, M Mohan, C Monteleoni International Conference on Algorithmic Learning Theory, 367-381, 2013 | 46 | 2013 |
| Online clustering with experts A Choromanska, C Monteleoni Artificial Intelligence and Statistics, 227-235, 2012 | 43 | 2012 |
| Automatic reconstruction of neural morphologies with multi-scale tracking A Choromanska, SF Chang, R Yuste Frontiers in neural circuits 6, 25, 2012 | 37 | 2012 |
| Sensor modality fusion with CNNs for UGV autonomous driving in indoor environments N Patel, A Choromanska, P Krishnamurthy, F Khorrami 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2017 | 36 | 2017 |
| Extreme multi class classification A Choromanska, A Agarwal, J Langford NIPS Workshop: eXtreme Classification, submitted 1, 2.1, 2013 | 36 | 2013 |
| Visualbackprop: efficient visualization of cnns M Bojarski, A Choromanska, K Choromanski, B Firner, L Jackel, U Muller, ... arXiv preprint arXiv:1611.05418, 2016 | 33 | 2016 |
| Binary embeddings with structured hashed projections A Choromanska, K Choromanski, M Bojarski, T Jebara, S Kumar, ... International Conference on Machine Learning, 344-353, 2016 | 33 | 2016 |
| Structured adaptive and random spinners for fast machine learning computations M Bojarski, A Choromanska, K Choromanski, F Fagan, C Gouy-Pailler, ... Artificial Intelligence and Statistics, 1020-1029, 2017 | 30 | 2017 |
| Visualbackprop: Efficient visualization of cnns for autonomous driving M Bojarski, A Choromanska, K Choromanski, B Firner, LJ Ackel, U Muller, ... 2018 IEEE International Conference on Robotics and Automation (ICRA), 4701-4708, 2018 | 27 | 2018 |
| Simultaneous learning of trees and representations for extreme classification and density estimation Y Jernite, A Choromanska, D Sontag International Conference on Machine Learning, 1665-1674, 2017 | 26 | 2017 |
| Differentially-and non-differentially-private random decision trees M Bojarski, A Choromanska, K Choromanski, Y LeCun arXiv preprint arXiv:1410.6973, 2014 | 24 | 2014 |
| Beyond backprop: Online alternating minimization with auxiliary variables A Choromanska, B Cowen, S Kumaravel, R Luss, M Rigotti, I Rish, ... International Conference on Machine Learning, 1193-1202, 2019 | 21 | 2019 |
| Towards automated melanoma detection with deep learning: Data purification and augmentation D Bisla, A Choromanska, RS Berman, JA Stein, D Polsky Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 18 | 2019 |
