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Equivariance Allows Handling Multiple Nuisance Variables When Analyzing Pooled Neuroimaging Datasets


Mar 29, 2022
Vishnu Suresh Lokhande, Rudrasis Chakraborty, Sathya N. Ravi, Vikas Singh

* Accepted at 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 

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Graph Reparameterizations for Enabling 1000+ Monte Carlo Iterations in Bayesian Deep Neural Networks


Feb 19, 2022
Jurijs Nazarovs, Ronak R. Mehta, Vishnu Suresh Lokhande, Vikas Singh


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Towards Group Robustness in the presence of Partial Group Labels


Jan 10, 2022
Vishnu Suresh Lokhande, Kihyuk Sohn, Jinsung Yoon, Madeleine Udell, Chen-Yu Lee, Tomas Pfister


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Learning Invariant Representations using Inverse Contrastive Loss


Feb 16, 2021
Aditya Kumar Akash, Vishnu Suresh Lokhande, Sathya N. Ravi, Vikas Singh

* Accepted to AAAI-21 

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FairALM: Augmented Lagrangian Method for Training Fair Models with Little Regret


Apr 03, 2020
Vishnu Suresh Lokhande, Aditya Kumar Akash, Sathya N. Ravi, Vikas Singh


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Active Learning with Importance Sampling


Oct 10, 2019
Muni Sreenivas Pydi, Vishnu Suresh Lokhande

* NeurIPS 2019 Workshop on Machine Learning with Guarantees, Vancouver, Canada 

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Generating Accurate Pseudo-labels via Hermite Polynomials for SSL Confidently


Sep 12, 2019
Vishnu Suresh Lokhande, Sathya Ravi, Songwong Tasneeyapant, Abhay Venkatesh, Vikas Singh


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Accelerating Column Generation via Flexible Dual Optimal Inequalities with Application to Entity Resolution


Sep 12, 2019
Vishnu Suresh Lokhande, Shaofei Wang, Maneesh Singh, Julian Yarkony


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