Jeet Mohapatra

Publication Activity (10 Years)

Years Active: 2017-2022
Publications (10 Years): 11

Top Topics

Exact And Approximate

Image Smoothing

Privacy Preserving Association Rule Mining

Nonparametric Regression

Top Venues

Publications

Ching-Yun Ko, Jeet Mohapatra, Sijia Liu, Pin-Yu Chen, Luca Daniel, Lily Weng
Revisiting Contrastive Learning through the Lens of Neighborhood Component Analysis: an Integrated Framework. ICML (2022)
Ching-Yun Ko, Pin-Yu Chen, Jeet Mohapatra, Payel Das, Luca Daniel
SynBench: Task-Agnostic Benchmarking of Pretrained Representations using Synthetic Data. CoRR (2022)
Jeet Mohapatra, Ching-Yun Ko, Lily Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
Hidden Cost of Randomized Smoothing. AISTATS (2021)
Ching-Yun Ko, Jeet Mohapatra, Sijia Liu, Pin-Yu Chen, Luca Daniel, Lily Weng
Revisiting Contrastive Learning through the Lens of Neighborhood Component Analysis: an Integrated Framework. CoRR (2021)
Jeet Mohapatra, Ching-Yun Ko, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
Higher-Order Certification for Randomized Smoothing. CoRR (2020)
Jeet Mohapatra, Ching-Yun Ko, Tsui-Wei Weng, Sijia Liu, Pin-Yu Chen, Luca Daniel
Rethinking Randomized Smoothing for Adversarial Robustness. CoRR (2020)
Jeet Mohapatra, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
Towards Verifying Robustness of Neural Networks Against A Family of Semantic Perturbations. CVPR (2020)
Jeet Mohapatra, Ching-Yun Ko, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
Higher-Order Certification For Randomized Smoothing. NeurIPS (2020)
Jeet Mohapatra, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
Towards Verifying Robustness of Neural Networks Against Semantic Perturbations. CoRR (2019)
Bernhard Haeupler, Jeet Mohapatra, Hsin-Hao Su
Optimal Gossip Algorithms for Exact and Approximate Quantile Computations. PODC (2018)
Bernhard Haeupler, Jeet Mohapatra, Hsin-Hao Su
Optimal Gossip Algorithms for Exact and Approximate Quantile Computations. CoRR (2017)