| Mapping the global design space of nanophotonic components using machine learning pattern recognition D Melati, Y Grinberg, MK Dezfouli, S Janz, P Cheben, JH Schmid, ... Nature communications 10 (1), 1-9, 2019 | 39 | 2019 |
| Compressed least-squares regression on sparse spaces MM Fard, Y Grinberg, J Pineau, D Precup Proceedings of the AAAI Conference on Artificial Intelligence 26 (1), 2012 | 30 | 2012 |
| Bellman error based feature generation using random projections on sparse spaces MM Fard, Y Grinberg, A Farahmand, J Pineau, D Precup arXiv preprint arXiv:1207.5554, 2012 | 17 | 2012 |
| Mixed observability predictive state representations S Ong, Y Grinberg, J Pineau Proceedings of the AAAI Conference on Artificial Intelligence 27 (1), 2013 | 10 | 2013 |
| Goal-directed online learning of predictive models SCW Ong, Y Grinberg, J Pineau European Workshop on Reinforcement Learning, 18-29, 2011 | 6 | 2011 |
| Remote energy auditing: Energy efficiency through smart thermostat data and control GR Newsham, Y Grinberg, A Pardasani, K Bar ECEEE Proceedings, 2017 | 4 | 2017 |
| Perfectly vertical surface grating couplers using subwavelength engineering for increased feature sizes MK Dezfouli, Y Grinberg, D Melati, P Cheben, JH Schmid, ... Optics Letters 45 (13), 3701-3704, 2020 | 3 | 2020 |
| Eurogames16: evaluating change detection in online conversation C Goutte, Y Wang, F Liao, Z Zanussi, S Larkin, Y Grinberg Proceedings of the Eleventh International Conference on Language Resources …, 2018 | 3 | 2018 |
| State Sequence Analysis in Hidden Markov Models. Y Grinberg, TJ Perkins UAI, 336-344, 2015 | 3 | 2015 |
| Design of multi-parameter photonic devices using machine learning pattern recognition D Melati, Y Grinberg, MK Dezfouli, JH Schmid, P Cheben, S Janz, ... Integrated Photonics Platforms: Fundamental Research, Manufacturing and …, 2020 | 2 | 2020 |
| On-chip Fourier-transform spectrometers and machine learning: a new route to smart photonic sensors A Herrero-Bermello, J Li, M Khazaei, Y Grinberg, AV Velasco, M Vachon, ... Optics letters 44 (23), 5840-5843, 2019 | 2 | 2019 |
| Optimizing energy production using policy search and predictive state representations Y Grinberg, D Precup, M Gendreau Advances in Neural Information Processing Systems, 2969-2977, 2014 | 2 | 2014 |
| Random projections preserve linearity in sparse spaces MM Fard, Y Grinberg, J Pineau, D Precup School of Computer Science, Mcgill University, Tech. Rep, 2012 | 2 | 2012 |
| Machine learning design of subwavelengh integrated photonic devices D Melati, MK Dezfouli, Y Grinberg, S Janz, JH Schmid, P Cheben, DX Xu 2019 International Conference on Numerical Simulation of Optoelectronic …, 2019 | 1 | 2019 |
| Performance robustness analysis in machine-assisted design of photonic devices D Melati, Y Grinberg, A Waqas, P Manfredi, MK Dezfouli, P Cheben, ... Smart Photonic and Optoelectronic Integrated Circuits XXI 10922, 1092203, 2019 | 1 | 2019 |
| Reaping the benefits of machine learning pattern recognition in nanophotonic component design Y Grinberg, D Melati, MK Dezfouli, S Janz, JH Schmid, P Cheben, ... Integrated Optics: Devices, Materials, and Technologies XXIII 10921, 109210B, 2019 | 1 | 2019 |
| Learning Predictive State Representations from Non-Uniform Sampling Y Grinberg, H Aboutalebi, M Lyman-Abramovitch, B Balle, D Precup Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 1 | 2018 |
| Fully polynomial-time computation of maximum likelihood trajectories in Markov chains Y Grinberg, TJ Perkins Information Processing Letters 118, 53-57, 2017 | 1 | 2017 |
| On average reward policy evaluation in infinite-state partially observable systems Y Grinberg, D Precup Artificial Intelligence and Statistics, 449-457, 2012 | 1 | 2012 |
| LSTD on sparse spaces Y Grinberg, MM Fard, J Pineau NIPS Workshop on New Frontiers in Model Order Selection, 2011 | 1 | 2011 |
Pavel ChebenNational Research Council CanadaVerified email at nrc.ca
