Aniket Anand Deshmukh

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University of Michigan ∙ Microsoft

Consensus Clustering with Unsupervised Representation Learning

Recent advances in deep clustering and unsupervised representation learn...
10/03/2020 ∙ by Jayanth Reddy Regatti, et al. ∙ 0 ∙ share

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Zero Shot Domain Generalization

Standard supervised learning setting assumes that training data and test...
08/17/2020 ∙ by Udit Maniyar, et al. ∙ 0 ∙ share

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Self-Supervised Contextual Bandits in Computer Vision

Contextual bandits are a common problem faced by machine learning practi...
03/18/2020 ∙ by Aniket Anand Deshmukh, et al. ∙ 0 ∙ share

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Data Transformation Insights in Self-supervision with Clustering Tasks

Self-supervision is key to extending use of deep learning for label scar...
02/18/2020 ∙ by Abhimanu Kumar, et al. ∙ 0 ∙ share

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Head and Tail Localization of C. elegans

C. elegans is commonly used in neuroscience for behaviour analysis becau...
01/12/2020 ∙ by Mansi Ranjit Mane, et al. ∙ 6 ∙ share

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Label-similarity Curriculum Learning

Curriculum learning can improve neural network training by guiding the o...
11/15/2019 ∙ by Urun Dogan, et al. ∙ 0 ∙ share

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PAC Reinforcement Learning without Real-World Feedback

This work studies reinforcement learning in the Sim-to-Real setting, in ...
09/23/2019 ∙ by Yuren Zhong, et al. ∙ 0 ∙ share

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A Generalization Error Bound for Multi-class Domain Generalization

Domain generalization is the problem of assigning labels to an unlabeled...
05/24/2019 ∙ by Aniket Anand Deshmukh, et al. ∙ 0 ∙ share

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Simple Regret Minimization for Contextual Bandits

There are two variants of the classical multi-armed bandit (MAB) problem...
10/17/2018 ∙ by Aniket Anand Deshmukh, et al. ∙ 0 ∙ share

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Domain2Vec: Deep Domain Generalization

We address the problem of domain generalization where a decision functio...
07/09/2018 ∙ by Aniket Anand Deshmukh, et al. ∙ 0 ∙ share

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Domain Generalization by Marginal Transfer Learning

Domain generalization is the problem of assigning class labels to an unl...
11/21/2017 ∙ by Gilles Blanchard, et al. ∙ 0 ∙ share

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Multi-Task Learning for Contextual Bandits

Contextual bandits are a form of multi-armed bandit in which the agent h...
05/24/2017 ∙ by Aniket Anand Deshmukh, et al. ∙ 0 ∙ share

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Aniket Anand Deshmukh

Featured Co-authors

Vineeth N Balasubramanian

Clayton Scott

Gilles Blanchard

Christian Igel

Urun Dogan

Yunwen Lei

Abhimanu Kumar

Denis Charles

Eren Manavoglu

Mansi Ranjit Mane

Srinagesh Sharma

Consensus Clustering with Unsupervised Representation Learning

Zero Shot Domain Generalization

Self-Supervised Contextual Bandits in Computer Vision

Data Transformation Insights in Self-supervision with Clustering Tasks

Head and Tail Localization of C. elegans

Label-similarity Curriculum Learning

PAC Reinforcement Learning without Real-World Feedback

A Generalization Error Bound for Multi-class Domain Generalization

Simple Regret Minimization for Contextual Bandits

Domain2Vec: Deep Domain Generalization

Domain Generalization by Marginal Transfer Learning

Multi-Task Learning for Contextual Bandits