| Analysis of thompson sampling for the multi-armed bandit problem S Agrawal, N Goyal Conference on learning theory, 39.1-39.26, 2012 | 1621 | 2012 |
| Thompson sampling for contextual bandits with linear payoffs S Agrawal, N Goyal International conference on machine learning, 127-135, 2013 | 1254 | 2013 |
| Near-optimal regret bounds for thompson sampling S Agrawal, N Goyal Journal of the ACM (JACM) 64 (5), 1-24, 2017 | 699 | 2017 |
| Are NLP models really able to solve simple math word problems? A Patel, S Bhattamishra, N Goyal arXiv preprint arXiv:2103.07191, 2021 | 600 | 2021 |
| On the ability and limitations of transformers to recognize formal languages S Bhattamishra, K Ahuja, N Goyal arXiv preprint arXiv:2009.11264, 2020 | 147 | 2020 |
| Fourier PCA and robust tensor decomposition N Goyal, S Vempala, Y Xiao Proceedings of the forty-sixth annual ACM symposium on Theory of computing …, 2014 | 134* | 2014 |
| The more, the merrier: the blessing of dimensionality for learning large Gaussian mixtures J Anderson, M Belkin, N Goyal, L Rademacher, J Voss Conference on Learning Theory, 1135-1164, 2014 | 111 | 2014 |
| Deterministic algorithms for the Lovász local lemma K Chandrasekaran, N Goyal, B Haeupler SIAM Journal on Computing 42 (6), 2132-2155, 2013 | 89 | 2013 |
| Lower bounds for the noisy broadcast problem N Goyal, G Kindler, M Saks SIAM Journal on Computing 37 (6), 1806-1841, 2008 | 71 | 2008 |
| On the computational power of transformers and its implications in sequence modeling S Bhattamishra, A Patel, N Goyal arXiv preprint arXiv:2006.09286, 2020 | 68 | 2020 |
| Expanders via random spanning trees N Goyal, L Rademacher, S Vempala Proceedings of the twentieth annual ACM-SIAM symposium on Discrete …, 2009 | 65 | 2009 |
| The VPN conjecture is true N Goyal, N Olver, FB Shepherd Journal of the ACM (JACM) 60 (3), 1-17, 2013 | 60 | 2013 |
| A theory of emergent in-context learning as implicit structure induction M Hahn, N Goyal arXiv preprint arXiv:2303.07971, 2023 | 58 | 2023 |
| Non-Gaussianity of stochastic gradient noise A Panigrahi, R Somani, N Goyal, P Netrapalli arXiv preprint arXiv:1910.09626, 2019 | 49 | 2019 |
| Disorder inequality: a combinatorial approach to nearest neighbor search N Goyal, Y Lifshits, H Schütze Proceedings of the 2008 international conference on web search and data …, 2008 | 47 | 2008 |
| Monitor-guided decoding of code LMs with static analysis of repository context LA Agrawal, A Kanade, N Goyal, S Lahiri, S Rajamani Advances in Neural Information Processing Systems 36, 2024 | 41* | 2024 |
| Learning convex bodies is hard N Goyal, L Rademacher arXiv preprint arXiv:0904.1227, 2009 | 35* | 2009 |
| Effect of activation functions on the training of overparametrized neural nets A Panigrahi, A Shetty, N Goyal arXiv preprint arXiv:1908.05660, 2019 | 32 | 2019 |
| In-context learning through the bayesian prism M Panwar, K Ahuja, N Goyal arXiv preprint arXiv:2306.04891, 2023 | 30 | 2023 |
| Revisiting the compositional generalization abilities of neural sequence models A Patel, S Bhattamishra, P Blunsom, N Goyal arXiv preprint arXiv:2203.07402, 2022 | 30 | 2022 |
