145 citations · 269 across the 15 of their papers we have counts for
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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…
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…
Domain Generalization by Marginal Transfer Learning
Gilles Blanchard, Aniket Anand Deshmukh, Urun Dogan +2
In the problem of domain generalization (DG), there are labeled training data sets from several related prediction problems, and the goal is to make accurate predictions on future…
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…
Distributed Optimization of Multi-Class SVMs
Maximilian Alber, Julian Zimmert, Urun Dogan +1
Training of one-vs.-rest SVMs can be parallelized over the number of classes in a straight forward way. Given enough computational resources, one-vs.-rest SVMs can thus be trained…
Coordinate Descent with Online Adaptation of Coordinate Frequencies
Tobias Glasmachers, Ürün Dogan
Coordinate descent (CD) algorithms have become the method of choice for solving a number of optimization problems in machine learning. They are particularly popular for training li…