41 citations · 81 across the 21 of their papers we have counts for
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Domain-Invariant Feature Alignment Using Variational Inference For Partial Domain Adaptation
Sandipan Choudhuri, Suli Adeniye, Arunabha Sen +1
The standard closed-set domain adaptation approaches seek to mitigate distribution discrepancies between two domains under the constraint of both sharing identical label sets. Howe…
PatchRot: A Self-Supervised Technique for Training Vision Transformers
Sachin Chhabra, Prabal Bijoy Dutta, Hemanth Venkateswara +1
Vision transformers require a huge amount of labeled data to outperform convolutional neural networks. However, labeling a huge dataset is a very expensive process. Self-supervised…
Coupling Adversarial Learning with Selective Voting Strategy for Distribution Alignment in Partial Domain Adaptation
Sandipan Choudhuri, Hemanth Venkateswara, Arunabha Sen
In contrast to a standard closed-set domain adaptation task, partial domain adaptation setup caters to a realistic scenario by relaxing the identical label set assumption. The fact…
Sparsity Regularization For Cold-Start Recommendation
Aksheshkumar Ajaykumar Shah, Hemanth Venkateswara
Recently, Generative Adversarial Networks (GANs) have been applied to the problem of Cold-Start Recommendation, but the training performance of these models is hampered by the extr…