Vishnu Suresh Lokhande

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 20

Top Topics

Active Learning

Importance Sampling

Unlabeled Instances

Top Venues

Publications

Jingchen Sun, Rohan Sharma, Vishnu Suresh Lokhande, Changyou Chen
Craft: Cross-modal Aligned Features Improve Robustness of Prompt Tuning. CoRR (2024)
Sotirios Panagiotis Chytas, Vishnu Suresh Lokhande, Vikas Singh
Pooling Image Datasets with Multiple Covariate Shift and Imbalance. ICLR (2024)
Mingzhen Huang, Jialing Cai, Shan Jia, Vishnu Suresh Lokhande, Siwei Lyu
MultiEdits: Simultaneous Multi-Aspect Editing with Text-to-Image Diffusion Models. CoRR (2024)
Ronak Mehta, Jeffery Kline, Vishnu Suresh Lokhande, Glenn Fung, Vikas Singh
Efficient Discrete Multi Marginal Optimal Transport Regularization. ICLR (2023)
Vishnu Suresh Lokhande, Rudrasis Chakraborty, Sathya N. Ravi, Vikas Singh
Equivariance Allows Handling Multiple Nuisance Variables When Analyzing Pooled Neuroimaging Datasets. CoRR (2022)
Jurijs Nazarovs, Ronak R. Mehta, Vishnu Suresh Lokhande, Vikas Singh
Graph Reparameterizations for Enabling 1000+ Monte Carlo Iterations in Bayesian Deep Neural Networks. CoRR (2022)
Vishnu Suresh Lokhande, Rudrasis Chakraborty, Sathya N. Ravi, Vikas Singh
Equivariance Allows Handling Multiple Nuisance Variables When Analyzing Pooled Neuroimaging Datasets. CVPR (2022)
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 (2022)
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)
Aditya Kumar Akash, Vishnu Suresh Lokhande, Sathya N. Ravi, Vikas Singh
Learning Invariant Representations using Inverse Contrastive Loss. AAAI (2021)
Aditya Kumar Akash, Vishnu Suresh Lokhande, Sathya N. Ravi, Vikas Singh
Learning Invariant Representations using Inverse Contrastive Loss. CoRR (2021)
Vishnu Suresh Lokhande, Shaofei Wang, Maneesh Singh, Julian Yarkony
Accelerating Column Generation via Flexible Dual Optimal Inequalities with Application to Entity Resolution. AAAI (2020)
Vishnu Suresh Lokhande, Aditya Kumar Akash, Sathya N. Ravi, Vikas Singh
FairALM: Augmented Lagrangian Method for Training Fair Models with Little Regret. CoRR (2020)
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)
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)
Muni Sreenivas Pydi, Vishnu Suresh Lokhande
Active Learning with Importance Sampling. CoRR (2019)
Shaofei Wang, Vishnu Suresh Lokhande, Maneesh Singh, Konrad P. Körding, Julian Yarkony
End-to-end Training of CNN-CRF via Differentiable Dual-Decomposition. CoRR (2019)
Vishnu Suresh Lokhande, Shaofei Wang, Maneesh Singh, Julian Yarkony
Accelerating Column Generation via Flexible Dual Optimal Inequalities with Application to Entity Resolution. CoRR (2019)
Vishnu Suresh Lokhande, Sathya N. Ravi, Songwong Tasneeyapant, Abhay Venkatesh, Vikas Singh
Generating Accurate Pseudo-labels via Hermite Polynomials for SSL Confidently. CoRR (2019)
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)