| Entropy-SGD: biasing gradient descent into wide valleys P Chaudhari, A Choromanska, S Soatto, Y LeCun, C Baldassi, C Borgs, ... Proc. of the International Conference of Learning and Representations (ICLR …, 2016 | 335 | 2016 |
| Stochastic gradient descent performs variational inference, converges to limit cycles for deep networks P Chaudhari, S Soatto Proc. of the International Conference of Learning and Representations (ICLR …, 2018 | 136 | 2018 |
| Deep relaxation: partial differential equations for optimizing deep neural networks P Chaudhari, A Oberman, S Osher, S Soatto, G Carlier Research in the Mathematical Sciences 5 (3), 30, 2018 | 93 | 2018 |
| Incremental sampling-based algorithm for minimum-violation motion planning LIR Castro, P Chaudhari, J Tůmová, S Karaman, E Frazzoli, D Rus 52nd IEEE Conference on Decision and Control, 3217-3224, 2013 | 66 | 2013 |
| A Baseline for Few-Shot Image Classification GS Dhillon, P Chaudhari, A Ravichandran, S Soatto Proc. of the International Conference of Learning and Representations (ICLR …, 2019 | 50 | 2019 |
| Sampling-based algorithms for continuous-time POMDPs P Chaudhari, S Karaman, D Hsu, E Frazzoli 2013 American Control Conference, 4604-4610, 2013 | 30 | 2013 |
| On the energy landscape of deep networks P Chaudhari, S Soatto arXiv:1511.06485, 2015 | 21* | 2015 |
| Game theoretic controller synthesis for multi-robot motion planning Part I: Trajectory based algorithms M Zhu, M Otte, P Chaudhari, E Frazzoli 2014 IEEE International Conference on Robotics and Automation (ICRA), 1646-1651, 2014 | 19 | 2014 |
| Parle: parallelizing stochastic gradient descent P Chaudhari, C Baldassi, R Zecchina, S Soatto, A Talwalkar, A Oberman Proc. of Conference on Systems and Machine Learning (SysML) 2018, arXiv …, 2017 | 18 | 2017 |
| Sampling-based algorithms for optimal motion planning using process algebra specifications V Varricchio, P Chaudhari, E Frazzoli 2014 IEEE International Conference on Robotics and Automation (ICRA), 5326-5332, 2014 | 16 | 2014 |
| Meta-Q-Learning R Fakoor, P Chaudhari, S Soatto, AJ Smola Proc. of the International Conference of Learning and Representations (ICLR …, 2019 | 14 | 2019 |
| Rethinking the Hyperparameters for Fine-tuning H Li, P Chaudhari, H Yang, M Lam, A Ravichandran, R Bhotika, S Soatto Proc. of the International Conference of Learning and Representations (ICLR …, 2020 | 9 | 2020 |
| Incremental minimum-violation control synthesis for robots interacting with external agents P Chaudhari, T Wongpiromsarny, E Frazzoli 2014 American Control Conference, 1761-1768, 2014 | 9 | 2014 |
| P3O: Policy-on Policy-off Policy Optimization R Fakoor, P Chaudhari, AJ Smola Proc. of the Conference on Uncertainty in Artificial Intelligence, arXiv …, 2019 | 7 | 2019 |
| Sampling-based algorithm for filtering using Markov chain approximations P Chaudhari, S Karaman, E Frazzoli 2012 IEEE 51st IEEE Conference on Decision and Control (CDC), 5972-5978, 2012 | 7 | 2012 |
| Directional adversarial training for cost sensitive deep learning classification applications M Terzi, GA Susto, P Chaudhari Engineering Applications of Artificial Intelligence 91, 103550, 2020 | 3 | 2020 |
| TraDE: Transformers for Density Estimation R Fakoor, P Chaudhari, J Mueller, AJ Smola arXiv preprint arXiv:2004.02441, 2020 | 3 | 2020 |
| A Free-Energy Principle for Representation Learning Y Gao, P Chaudhari Proc. of the International Conference of Machine Learning (ICML) 2020, arXiv …, 2020 | 2 | 2020 |
| Localization using Average Landmark Vector in the presence of clutter P Chaudhari 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC …, 2009 | 2 | 2009 |
| Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation R Fakoor, J Mueller, N Erickson, P Chaudhari, AJ Smola Proc. of the Conference on Neural Information Processing Systems (NeurIPS …, 2020 | 1 | 2020 |
Stefano SoattoProfessor of Computer Science, UCLAVerified email at ucla.edu
