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A. Deshmukh

11 papers hereh-index 9658 citations29 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author5
  • middle author5
  • last author1

Across the 11 of 11 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • stat.ML4
  • cs.LG2
  • cs.AR1
same name
  • A. Deshmukh — 2 papers
  • A. Deshmukh — 1 paper, h 3
  • A. Deshmukh — 1 paper, h 2
  • A. Deshmukh — 1 paper
  • A. Deshmukh — 1 paper, h 6

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20172021
most citedMulti-Task Learning for Contextual Bandits

29 citations · 57 across the 7 of their papers we have counts for

collaborators
Showing stat.MLShow all

4 papers · 1 filter

stat.ML2020★ 2 cited

Data Transformation Insights in Self-supervision with Clustering Tasks

Abhimanu Kumar, Aniket Anand Deshmukh, Urun Dogan +2

Self-supervision is key to extending use of deep learning for label scarce domains. For most of self-supervised approaches data transformations play an important role. However, up…

stat.ML2019★ 19 cited

A Generalization Error Bound for Multi-class Domain Generalization

Aniket Anand Deshmukh, Yunwen Lei, Srinagesh Sharma +3

Domain generalization is the problem of assigning labels to an unlabeled data set, given several similar data sets for which labels have been provided. Despite considerable interes…

stat.ML2018

Simple Regret Minimization for Contextual Bandits

Aniket Anand Deshmukh, Srinagesh Sharma, James W. Cutler +2

There are two variants of the classical multi-armed bandit (MAB) problem that have received considerable attention from machine learning researchers in recent years: contextual ban…

stat.ML2017★ 29 cited

Multi-Task Learning for Contextual Bandits

Aniket Anand Deshmukh, Urun Dogan, Clayton Scott

Contextual bandits are a form of multi-armed bandit in which the agent has access to predictive side information (known as the context) for each arm at each time step, and have bee…

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