| The loss surfaces of multilayer networks A Choromanska, M Henaff, M Mathieu, GB Arous, Y LeCun Artificial intelligence and statistics, 192-204, 2015 | 1668 | 2015 |
| Entropy SGD: biasing gradient descent into wide valleys P Chaudhari, A Choromanska, S Soatto, Y LeCun, C Baldassi, C Borgs, ... International Conference on Learning Representations, 1-19, 2017 | 839 | 2017 |
| Deep learning with elastic averaging SGD S Zhang, AE Choromanska, Y LeCun Advances in neural information processing systems 28, 2015 | 745 | 2015 |
| 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 | 557 | 2017 |
| End to end learning for self-driving cars. arXiv 2016 M Bojarski, D Del Testa, D Dworakowski, B Firner, B Flepp, P Goyal, ... arXiv preprint arXiv:1604.07316 103, 2016 | 184 | 2016 |
| 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 | 146 | 2019 |
| Open problem: The landscape of the loss surfaces of multilayer networks A Choromanska, Y LeCun, GB Arous Conference on Learning Theory, 1756-1760, 2015 | 145 | 2015 |
| 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 | 109 | 2018 |
| Visualbackprop: visualizing cnns for autonomous driving M Bojarski, A Choromanska, K Choromanski, B Firner, L Jackel, U Muller, ... arXiv preprint arXiv:1611.05418 2, 1.2, 2016 | 102 | 2016 |
| Logarithmic time online multiclass prediction AE Choromanska, J Langford Advances in neural information processing systems 28, 2015 | 90 | 2015 |
| 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 | 77 | 2017 |
| Fast spectral clustering via the nyström method A Choromanska, T Jebara, H Kim, M Mohan, C Monteleoni Algorithmic Learning Theory: 24th International Conference, ALT 2013 …, 2013 | 76 | 2013 |
| 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 | 72 | 2019 |
| Visualbackprop: efficient visualization of cnns M Bojarski, A Choromanska, K Choromanski, B Firner, L Jackel, U Muller, ... arXiv preprint arXiv:1611.05418, 2016 | 65 | 2016 |
| Online clustering with experts A Choromanska, C Monteleoni Artificial Intelligence and Statistics, 227-235, 2012 | 62 | 2012 |
| Automatic reconstruction of neural morphologies with multi-scale tracking A Choromanska, SF Chang, R Yuste Frontiers in neural circuits 6, 25, 2012 | 47 | 2012 |
| Learning to score behaviors for guided policy optimization A Pacchiano, J Parker-Holder, Y Tang, K Choromanski, A Choromanska, ... International Conference on Machine Learning, 7445-7454, 2020 | 44 | 2020 |
| 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 | 43 | 2017 |
| Binary embeddings with structured hashed projections A Choromanska, K Choromanski, M Bojarski, T Jebara, S Kumar, ... International Conference on Machine Learning, 344-353, 2016 | 42 | 2016 |
| 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 | 40 | 2017 |