6 citations · 13 across the 11 of their papers we have counts for
13 papers
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…
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…
Partial Domain Adaptation Using Selective Representation Learning For Class-Weight Computation
Sandipan Choudhuri, Riti Paul, Arunabha Sen +2
The generalization power of deep-learning models is dependent on rich-labelled data. This supervision using large-scaled annotated information is restrictive in most real-world sce…
Leveraging Seen and Unseen Semantic Relationships for Generative Zero-Shot Learning
Maunil R Vyas, Hemanth Venkateswara, Sethuraman Panchanathan
Zero-shot learning (ZSL) addresses the unseen class recognition problem by leveraging semantic information to transfer knowledge from seen classes to unseen classes. Generative mod…
Foveated Haptic Gaze
Bijan Fakhri, Troy McDaniel, Heni Ben Amor +3
As digital worlds become ubiquitous via video games, simulations, virtual and augmented reality, people with disabilities who cannot access those worlds are becoming increasingly d…