| Linear stochastic approximation: How far does constant step-size and iterate averaging go? C Lakshminarayanan, C Szepesvari International Conference on Artificial Intelligence and Statistics, 1347-1355, 2018 | 146 | 2018 |
| A linearly relaxed approximate linear program for Markov decision processes C Lakshminarayanan, S Bhatnagar, C Szepesvári IEEE Transactions on Automatic control 63 (4), 1185-1191, 2017 | 35 | 2017 |
| A stability criterion for two timescale stochastic approximation schemes C Lakshminarayanan, S Bhatnagar Automatica 79, 108-114, 2017 | 29 | 2017 |
| Linear stochastic approximation: Constant step-size and iterate averaging C Lakshminarayanan, C Szepesvári arXiv preprint arXiv:1709.04073, 2017 | 11 | 2017 |
| Neural path features and neural path kernel: Understanding the role of gates in deep learning C Lakshminarayanan, A Vikram Singh Advances in Neural Information Processing Systems 33, 5227-5237, 2020 | 10 | 2020 |
| Approximate dynamic programming with (min;+) linear function approximation for markov decision processes L Chandrashekar, S Bhatnagar 53rd IEEE Conference on Decision and Control, 1588-1593, 2014 | 7 | 2014 |
| A generalized reduced linear program for Markov decision processes C Lakshminarayanan, S Bhatnagar Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015 | 4 | 2015 |
| CurriculumTutor: An Adaptive Algorithm for Mastering a Curriculum KM Shabana, C Lakshminarayanan, JK Anil International Conference on Artificial Intelligence in Education, 319-331, 2022 | 2 | 2022 |
| Disentangling deep neural networks with rectified linear units using duality C Lakshminarayanan, AV Singh arXiv preprint arXiv:2110.03403, 2021 | 1 | 2021 |
| Half-Space Feature Learning in Neural Networks ML Yadav, HG Ramaswamy, C Lakshminarayanan arXiv preprint arXiv:2404.04312, 2024 | | 2024 |
| Half-Space Feature Learning in Neural Networks M Lorik Yadav, H Guruprasad Ramaswamy, C Lakshminarayanan arXiv e-prints, arXiv: 2404.04312, 2024 | | 2024 |
| Approximate Linear Programming and Decentralized Policy Improvement in Cooperative Multi-agent Markov Decision Processes L Mandal, C Lakshminarayanan, S Bhatnagar arXiv preprint arXiv:2311.11789, 2023 | | 2023 |
| Enhancing Decision Tree Learning with Deep Networks P Banerjee, ML Yadav, HG Ramaswamy, CS LAKSHMINARAYANAN | | 2023 |
| Unsupervised Concept Tagging of Mathematical Questions from Student Explanations KM Shabana, C Lakshminarayanan International Conference on Artificial Intelligence in Education, 627-638, 2023 | | 2023 |
| Deployment and Explanation of Deep Models for Endoscopy Video Classification KV Mahendar, CS LAKSHMINARAYANAN, A Rajkumar, ... Third Conference on Deployable AI, 2023 | | 2023 |
| Explicitising The Implicit Intrepretability of Deep Neural Networks Via Duality C Lakshminarayanan, AV Singh, A Rajkumar arXiv preprint arXiv:2203.16455, 2022 | | 2022 |
| Deep Learning Is Composite Kernel Learning CS LAKSHMINARAYANAN, AV Singh | | 2020 |
| Deep Gated Networks: A framework to understand training and generalisation in deep learning C Lakshminarayanan, AV Singh arXiv preprint arXiv:2002.03996, 2020 | | 2020 |
| Approximate Dynamic Programming and Reinforcement Learning-Algorithms, Analysis and an Application C Lakshminarayanan | | 2018 |
| A Markov Decision Process Framework for Predictable Job Completion Times on Crowdsourcing Platforms C Lakshminarayanan, A Dubey, S Bhatnagar, C Balamurugan Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 2 …, 2014 | | 2014 |
Shalabh BhatnagarProfessor in the Department of Computer Science and Automation, Indian Institute of ScienceVerified email at iisc.ac.in
