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Robust Handwriting Recognition with Limited and Noisy Data.

H. Pham, A. Setlur, S. Dingliwal, T. Lin, B. Póczos, K. Huang, Z. Li, J. Lim, C. McCormack, and T. Vu. ICFHR, page 301-306. IEEE, (2020)

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ReStGAN: A step towards visually guided shopper experience via text-to-image synthesis.S. Surya, A. Setlur, A. Biswas, and S. Negi. WACV, page 1189-1197. IEEE, (2020)Towards Using Heterogeneous Relation Graphs for End-to-End TTS.A. Setlur, A. Madaan, T. Parekh, Y. Yang, and A. Black. ASRU, page 1162-1169. IEEE, (2021)Robust Handwriting Recognition with Limited and Noisy Data.H. Pham, A. Setlur, S. Dingliwal, T. Lin, B. Póczos, K. Huang, Z. Li, J. Lim, C. McCormack, and T. Vu. ICFHR, page 301-306. IEEE, (2020)Contextual Reliability: When Different Features Matter in Different Contexts.G. Ghosal, A. Setlur, D. Brown, A. Dragan, and A. Raghunathan. ICML, volume 202 of Proceedings of Machine Learning Research, page 11300-11320. PMLR, (2023)Explaining the Efficacy of Counterfactually Augmented Data.D. Kaushik, A. Setlur, E. Hovy, and Z. Lipton. ICLR, OpenReview.net, (2021)Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts.A. Setlur, D. Dennis, B. Eysenbach, A. Raghunathan, C. Finn, V. Smith, and S. Levine. ICLR, OpenReview.net, (2023)RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-Fold.A. Setlur, S. Garg, X. Geng, N. Garg, V. Smith, and A. Kumar. CoRR, (2024)Deep Neural Networks Tend To Extrapolate Predictably.K. Kang, A. Setlur, C. Tomlin, and S. Levine. ICLR, OpenReview.net, (2024)Is Support Set Diversity Necessary for Meta-Learning?A. Setlur, O. Li, and V. Smith. CoRR, (2020)Project and Probe: Sample-Efficient Domain Adaptation by Interpolating Orthogonal Features.A. Chen, Y. Lee, A. Setlur, S. Levine, and C. Finn. CoRR, (2023)

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Disambiguation of "Setlur, Amrith"

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Robust Handwriting Recognition with Limited and Noisy Data.

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Disambiguation of "Setlur, Amrith"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Robust Handwriting Recognition with Limited and Noisy Data.

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Robust Handwriting Recognition with Limited and Noisy Data.