| The loss surfaces of multilayer networks A Choromanska, M Henaff, M Mathieu, GB Arous, Y LeCun Artificial intelligence and statistics, 192-204, 2015 | 1866 | 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 | 983 | 2017 |
| Deep learning with elastic averaging SGD S Zhang, AE Choromanska, Y LeCun Advances in neural information processing systems 28, 2015 | 811 | 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 | 627 | 2017 |
| 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 | 184 | 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 | 158 | 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 | 122 | 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 | 117 | 2016 |
| Logarithmic time online multiclass prediction AE Choromanska, J Langford Advances in neural information processing systems 28, 2015 | 91 | 2015 |
| 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 | 83 | 2019 |
| 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 | 82 | 2013 |
| 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 | 79 | 2017 |
| Online clustering with experts A Choromanska, C Monteleoni Artificial Intelligence and Statistics, 227-235, 2012 | 68 | 2012 |
| Visualbackprop: efficient visualization of cnns M Bojarski, A Choromanska, K Choromanski, B Firner, L Jackel, U Muller, ... arXiv preprint arXiv:1611.05418, 2016 | 66 | 2016 |
| 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 | 51 | 2020 |
| Automatic reconstruction of neural morphologies with multi-scale tracking A Choromanska, SF Chang, R Yuste Frontiers in neural circuits 6, 25, 2012 | 51 | 2012 |
| Low-pass filtering sgd for recovering flat optima in the deep learning optimization landscape D Bisla, J Wang, A Choromanska International Conference on Artificial Intelligence and Statistics, 8299-8339, 2022 | 48 | 2022 |
| 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 | 43 | 2017 |
| 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 |
