Hemanth Venkateswara | DeepAI

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∙ 12/03/2022

Domain-Invariant Feature Alignment Using Variational Inference For Partial Domain Adaptation

The standard closed-set domain adaptation approaches seek to mitigate di...

0 Sandipan Choudhuri, et al. ∙

∙ 10/27/2022

PatchRot: A Self-Supervised Technique for Training Vision Transformers

Vision transformers require a huge amount of labeled data to outperform ...

0 Sachin Chhabra, et al. ∙

∙ 07/17/2022

Coupling Adversarial Learning with Selective Voting Strategy for Distribution Alignment in Partial Domain Adaptation

In contrast to a standard closed-set domain adaptation task, partial dom...

0 Sandipan Choudhuri, et al. ∙

∙ 01/26/2022

Sparsity Regularization For Cold-Start Recommendation

Recently, Generative Adversarial Networks (GANs) have been applied to th...

0 Aksheshkumar Ajaykumar Shah, et al. ∙

∙ 01/06/2021

Partial Domain Adaptation Using Selective Representation Learning For Class-Weight Computation

The generalization power of deep-learning models is dependent on rich-la...

0 Sandipan Choudhuri, et al. ∙

∙ 07/19/2020

Leveraging Seen and Unseen Semantic Relationships for Generative Zero-Shot Learning

Zero-shot learning (ZSL) addresses the unseen class recognition problem ...

0 Maunil R Vyas, et al. ∙

∙ 01/07/2020

Foveated Haptic Gaze

As digital worlds become ubiquitous via video games, simulations, virtua...

0 Bijan Fakhri, et al. ∙

∙ 07/01/2019

Representation, Exploration and Recommendation of Music Playlists

Playlists have become a significant part of our listening experience bec...

0 Piyush Papreja, et al. ∙

∙ 06/23/2017

Efficient Approximate Solutions to Mutual Information Based Global Feature Selection

Mutual Information (MI) is often used for feature selection when develop...

0 Hemanth Venkateswara, et al. ∙

∙ 06/23/2017

Multiresolution Match Kernels for Gesture Video Classification

The emergence of depth imaging technologies like the Microsoft Kinect ha...

0 Hemanth Venkateswara, et al. ∙

∙ 06/23/2017

Model Selection with Nonlinear Embedding for Unsupervised Domain Adaptation

Domain adaptation deals with adapting classifiers trained on data from a...

0 Hemanth Venkateswara, et al. ∙

∙ 06/22/2017

Coupled Support Vector Machines for Supervised Domain Adaptation

Popular domain adaptation (DA) techniques learn a classifier for the tar...

0 Hemanth Venkateswara, et al. ∙

∙ 06/22/2017

Nonlinear Embedding Transform for Unsupervised Domain Adaptation

The problem of domain adaptation (DA) deals with adapting classifier mod...

0 Hemanth Venkateswara, et al. ∙

∙ 06/22/2017

Deep Hashing Network for Unsupervised Domain Adaptation

In recent years, deep neural networks have emerged as a dominant machine...

0 Hemanth Venkateswara, et al. ∙

∙ 05/02/2017

A Strategy for an Uncompromising Incremental Learner

Multi-class supervised learning systems require the knowledge of the ent...

0 Ragav Venkatesan, et al. ∙