| Artwork personalization at Netflix A Chandrashekar, F Amat, J Basilico, T Jebara Netflix technology blog 7, 2017 | 102* | 2017 |
| Artwork personalization at Netflix F Amat, A Chandrashekar, T Jebara, J Basilico Proceedings of the 12th ACM conference on recommender systems, 487-488, 2018 | 74 | 2018 |
| Image clustering C Zitnick, R Sagula, A Chandrashekar US Patent 8,625,907, 2014 | 43 | 2014 |
| Learning representations of hierarchical slates in collaborative filtering E Elahi, A Chandrashekar Proceedings of the 14th ACM Conference on Recommender Systems, 703-707, 2020 | 13 | 2020 |
| Derivation of a novel efficient supervised learning algorithm from cortical-subcortical loops A Chandrashekar, R Granger Frontiers in computational neuroscience 5, 50, 2012 | 12 | 2012 |
| Accelerating brain circuit simulations of object recognition with cell processors A Felch, JM Nageswaran, A Chandrashekar, J Furlong, N Dutt, R Granger, ... Innovative architecture for future generation high-performance processors …, 2007 | 11 | 2007 |
| Control variates for slate off-policy evaluation N Vlassis, A Chandrashekar, F Amat, N Kallus Advances in Neural Information Processing Systems 34, 3667-3679, 2021 | 10 | 2021 |
| On the bias-variance characteristics of lime and shap in high sparsity movie recommendation explanation tasks CV Roberts, E Elahi, A Chandrashekar arXiv preprint arXiv:2206.04784, 2022 | 9 | 2022 |
| Novel Brain-Derived Algorithms Scale Linearly with Number of Processing Elements. J Furlong, A Felch, JM Nageswaran, ND Dutt, A Nicolau, AV Veidenbaum, ... PARCO, 767-776, 2007 | 9 | 2007 |
| Learning what is where from unlabeled images: joint localization and clustering of foreground objects A Chandrashekar, L Torresani, R Granger Machine learning 94, 261-279, 2014 | 6 | 2014 |
| On Negative Sampling for Audio-Visual Contrastive Learning from Movies MMKSA LingyiLiu, N Kamath, A Chandrashekar | 5* | |
| Off-Policy Evaluation of Slate Policies under Bayes Risk N Vlassis, FA Gil, A Chandrashekar arXiv preprint arXiv:2101.02553, 2021 | 4 | 2021 |
| Watching too much television is good: Self-supervised audio-visual representation learning from movies and tv shows MM Kalayeh, N Kamath, L Liu, A Chandrashekar arXiv preprint arXiv:2106.08513, 2021 | 3 | 2021 |
| Bias-variance decomposition for ranking P Shivaswamy, A Chandrashekar Proceedings of the 14th ACM International Conference on Web Search and Data …, 2021 | 3 | 2021 |
| Towards understanding the gaps of offline and online evaluation metrics: Impact of series vs. movie recommendations B Edizel, T Sweetser, A Chandrashekar, K Ahmadi, P Das Proceedings of the 18th ACM Conference on Recommender Systems, 844-846, 2024 | 2 | 2024 |
| Accelerating brain circuit simulations of object recognition with a Sony PlayStation 3 JM Nageswaran, A Felch, A Chandrashekar, J Furlong, N Dutt, A Nicolau, ... Int. Workshop on Innovative Architecture for Future Generation …, 2007 | 1 | 2007 |
| CLIME: Completeness-Constrained LIME C Roberts, E Elahi, A Chandrashekar Companion Proceedings of the ACM Web Conference 2023, 950-958, 2023 | | 2023 |
| Combining biological and statistical learning principles for minimally supervised object recognition A Chandrashekar Dartmouth College, 2013 | | 2013 |
| Accelerating Brain Circuit Simulation for the Real World AC Felch, A Chandrashekar, J Moorkanikara Nageswaran, J Furlong, ... | | |
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