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ORCIDVishnu Suresh Lokhande
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Conference and Workshop Papers
- 2024
[c9]Sotirios Panagiotis Chytas, Vishnu Suresh Lokhande, Vikas Singh:
Pooling Image Datasets with Multiple Covariate Shift and Imbalance. ICLR 2024- 2023
- [c8]Ronak Mehta, Jeffery Kline, Vishnu Suresh Lokhande, Glenn Fung, Vikas Singh:
Efficient Discrete Multi Marginal Optimal Transport Regularization. ICLR 2023 - 2022
- [c7]Vishnu Suresh Lokhande, Rudrasis Chakraborty, Sathya N. Ravi, Vikas Singh:
Equivariance Allows Handling Multiple Nuisance Variables When Analyzing Pooled Neuroimaging Datasets. CVPR 2022: 10422-10431 - 2021
- [c6]Aditya Kumar Akash, Vishnu Suresh Lokhande, Sathya N. Ravi, Vikas Singh:
Learning Invariant Representations using Inverse Contrastive Loss. AAAI 2021: 6582-6591 - [c5]Jurijs Nazarovs, Ronak R. Mehta, Vishnu Suresh Lokhande, Vikas Singh:
Graph reparameterizations for enabling 1000+ Monte Carlo iterations in Bayesian deep neural networks. UAI 2021: 118-128 - 2020
- [c4]Vishnu Suresh Lokhande, Shaofei Wang, Maneesh Singh, Julian Yarkony:
Accelerating Column Generation via Flexible Dual Optimal Inequalities with Application to Entity Resolution. AAAI 2020: 1593-1602 - [c3]Vishnu Suresh Lokhande, Songwong Tasneeyapant, Abhay Venkatesh, Sathya N. Ravi, Vikas Singh:
Generating Accurate Pseudo-Labels in Semi-Supervised Learning and Avoiding Overconfident Predictions via Hermite Polynomial Activations. CVPR 2020: 11432-11440 - [c2]Vishnu Suresh Lokhande
, Aditya Kumar Akash, Sathya N. Ravi, Vikas Singh:
FairALM: Augmented Lagrangian Method for Training Fair Models with Little Regret. ECCV (12) 2020: 365-381 - 2019
- [c1]Sathya N. Ravi, Tuan Dinh, Vishnu Suresh Lokhande, Vikas Singh:
Explicitly Imposing Constraints in Deep Networks via Conditional Gradients Gives Improved Generalization and Faster Convergence. AAAI 2019: 4772-4779
Informal and Other Publications
- 2024
- [i11]Mingzhen Huang, Jialing Cai, Shan Jia, Vishnu Suresh Lokhande, Siwei Lyu:
MultiEdits: Simultaneous Multi-Aspect Editing with Text-to-Image Diffusion Models. CoRR abs/2406.00985 (2024) - [i10]Jingchen Sun, Rohan Sharma, Vishnu Suresh Lokhande, Changyou Chen:
Craft: Cross-modal Aligned Features Improve Robustness of Prompt Tuning. CoRR abs/2407.15894 (2024) - 2022
- [i9]Vishnu Suresh Lokhande, Kihyuk Sohn, Jinsung Yoon, Madeleine Udell, Chen-Yu Lee, Tomas Pfister:
Towards Group Robustness in the presence of Partial Group Labels. CoRR abs/2201.03668 (2022) - [i8]Jurijs Nazarovs, Ronak R. Mehta, Vishnu Suresh Lokhande, Vikas Singh:
Graph Reparameterizations for Enabling 1000+ Monte Carlo Iterations in Bayesian Deep Neural Networks. CoRR abs/2202.09478 (2022) - [i7]Vishnu Suresh Lokhande, Rudrasis Chakraborty, Sathya N. Ravi, Vikas Singh:
Equivariance Allows Handling Multiple Nuisance Variables When Analyzing Pooled Neuroimaging Datasets. CoRR abs/2203.15234 (2022) - 2021
- [i6]Aditya Kumar Akash, Vishnu Suresh Lokhande, Sathya N. Ravi, Vikas Singh:
Learning Invariant Representations using Inverse Contrastive Loss. CoRR abs/2102.08343 (2021) - 2020
- [i5]Vishnu Suresh Lokhande, Aditya Kumar Akash, Sathya N. Ravi, Vikas Singh:
FairALM: Augmented Lagrangian Method for Training Fair Models with Little Regret. CoRR abs/2004.01355 (2020) - 2019
- [i4]Vishnu Suresh Lokhande, Shaofei Wang, Maneesh Singh, Julian Yarkony:
Accelerating Column Generation via Flexible Dual Optimal Inequalities with Application to Entity Resolution. CoRR abs/1909.05460 (2019) - [i3]Vishnu Suresh Lokhande, Sathya N. Ravi, Songwong Tasneeyapant, Abhay Venkatesh, Vikas Singh:
Generating Accurate Pseudo-labels via Hermite Polynomials for SSL Confidently. CoRR abs/1909.05479 (2019) - [i2]Muni Sreenivas Pydi, Vishnu Suresh Lokhande:
Active Learning with Importance Sampling. CoRR abs/1910.04371 (2019) - [i1]Shaofei Wang, Vishnu Suresh Lokhande, Maneesh Singh, Konrad P. Körding, Julian Yarkony:
End-to-end Training of CNN-CRF via Differentiable Dual-Decomposition. CoRR abs/1912.02937 (2019)
Coauthor Index
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