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Explicit discriminative representation for improved classification of manifold features.

A. Wiliem, R. Vemulapalli, and B. Lovell. Pattern Recognit. Lett., (2016)

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Explicit discriminative representation for improved classification of manifold features.A. Wiliem, R. Vemulapalli, and B. Lovell. Pattern Recognit. Lett., (2016)Balancing Constraints and Submodularity in Data Subset Selection.S. Ramalingam, D. Glasner, K. Patel, R. Vemulapalli, S. Jayasumana, and S. Kumar. CoRR, (2021)Towards Federated Learning Under Resource Constraints via Layer-wise Training and Depth Dropout.P. Guo, W. Morningstar, R. Vemulapalli, K. Singhal, V. Patel, and P. Mansfield. CoRR, (2023)Weight subcloning: direct initialization of transformers using larger pretrained ones.M. Samragh, M. Farajtabar, S. Mehta, R. Vemulapalli, F. Faghri, D. Naik, O. Tuzel, and M. Rastegari. CoRR, (2023)Federated Training of Dual Encoding Models on Small Non-IID Client Datasets.R. Vemulapalli, W. Morningstar, P. Mansfield, H. Eichner, K. Singhal, A. Afkanpour, and B. Green. CoRR, (2022)Boosting Image-based Mutual Gaze Detection using Pseudo 3D Gaze.B. Doosti, C. Chen, R. Vemulapalli, X. Jia, Y. Zhu, and B. Green. AAAI, page 1273-1281. AAAI Press, (2021)Rolling Rotations for Recognizing Human Actions from 3D Skeletal Data.R. Vemulapalli, and R. Chellappa. CVPR, page 4471-4479. IEEE Computer Society, (2016)Unsupervised Cross-Modal Synthesis of Subject-Specific Scans.R. Vemulapalli, H. Nguyen, and S. Zhou. ICCV, page 630-638. IEEE Computer Society, (2015)TiC-CLIP: Continual Training of CLIP Models.S. Garg, M. Farajtabar, H. Pouransari, R. Vemulapalli, S. Mehta, O. Tuzel, V. Shankar, and F. Faghri. CoRR, (2023)CLIP meets Model Zoo Experts: Pseudo-Supervision for Visual Enhancement.M. Salehi, M. Farajtabar, M. Horton, F. Faghri, H. Pouransari, R. Vemulapalli, O. Tuzel, A. Farhadi, M. Rastegari, and S. Mehta. CoRR, (2023)

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Explicit discriminative representation for improved classification of manifold features.

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Disambiguation of "Vemulapalli, Raviteja"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Explicit discriminative representation for improved classification of manifold features.

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Explicit discriminative representation for improved classification of manifold features.