Jayaram Raghuram

According to our database, Jayaram Raghuram authored at least 15 papers between 2011 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Cloud-LoRa: Enabling Cloud Radio Access LoRa Networks Using Reinforcement Learning Based Bandwidth-Adaptive Compression.

Muhammad Osama Shahid, Daniel Jay Koch, Jayaram Raghuram, Bhuvana Krishnaswamy, Krishna Chintalapudi, Suman Banerjee

Proceedings of the 21st USENIX Symposium on Networked Systems Design and Implementation, 2024

2023

Concept-based Explanations for Out-of-Distribution Detectors.

Jihye Choi, Jayaram Raghuram, Ryan Feng, Jiefeng Chen, Somesh Jha, Atul Prakash

Proceedings of the International Conference on Machine Learning, 2023

Stratified Adversarial Robustness with Rejection.

Jiefeng Chen, Jayaram Raghuram, Jihye Choi, Xi Wu, Yingyu Liang, Somesh Jha

Proceedings of the International Conference on Machine Learning, 2023

The Trade-off between Universality and Label Efficiency of Representations from Contrastive Learning.

Zhenmei Shi, Jiefeng Chen, Kunyang Li, Jayaram Raghuram, Xi Wu, Yingyu Liang, Somesh Jha

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Few-Shot Domain Adaptation For End-to-End Communication.

Jayaram Raghuram, Yijing Zeng, Dolores García, Rafael Ruiz, Somesh Jha, Joerg Widmer, Suman Banerjee

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2021

Domain Adaptation for Autoencoder-Based End-to-End Communication Over Wireless Channels.

Jayaram Raghuram, Yijing Zeng, Dolores García Martí, Somesh Jha, Suman Banerjee, Joerg Widmer, Rafael Ruiz Ortiz

CoRR, 2021

A General Framework For Detecting Anomalous Inputs to DNN Classifiers.

Jayaram Raghuram, Varun Chandrasekaran, Somesh Jha, Suman Banerjee

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Detecting Anomalous Inputs to DNN Classifiers By Joint Statistical Testing at the Layers.

Jayaram Raghuram, Varun Chandrasekaran, Somesh Jha, Suman Banerjee

CoRR, 2020

2015

Generation bidding game with potentially false attestation of flexible demand.

Yuquan Shan, Jayaram Raghuram, George Kesidis, David J. Miller, Anna Scaglione, Jeff Rowe, Karl N. Levitt

EURASIP J. Adv. Signal Process., 2015

2014

Instance-Level Constraint-Based Semisupervised Learning With Imposed Space-Partitioning.

Jayaram Raghuram, David J. Miller, George Kesidis

IEEE Trans. Neural Networks Learn. Syst., 2014

Generation bidding game with flexible demand.

Yuquan Shan, Jayaram Raghuram, George Kesidis, Christopher Griffin, Karl N. Levitt, David J. Miller, Jeff Rowe, Anna Scaglione

CoRR, 2014

A Bidding Game for Generators in the Presence of Flexible Demand.

Jayaram Raghuram, George Kesidis, Christopher Griffin, Karl N. Levitt, David J. Miller, Jeff Rowe, Anna Scaglione

Proceedings of the 9th International Workshop on Feedback Computing, 2014

2012

Improved Generative Semisupervised Learning Based on Finely Grained Component-Conditional Class Labeling.

David J. Miller, Jayaram Raghuram, George Kesidis, Christopher M. Collins

Neural Comput., 2012

Semisupervised domain adaptation for mixture model based classifiers.

Jayaram Raghuram, David J. Miller, George Kesidis

Proceedings of the 46th Annual Conference on Information Sciences and Systems, 2012

2011

Salting Public Traces with Attack Traffic to Test Flow Classifiers.

Z. Berkay Celik, Jayaram Raghuram, George Kesidis, David J. Miller

Proceedings of the 4th Workshop on Cyber Security Experimentation and Test, 2011