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ORCIDJayaram Raghuram
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2020 – today
- 2024
[c9]Muhammad Osama Shahid, Daniel Jay Koch, Jayaram Raghuram, Bhuvana Krishnaswamy, Krishna Chintalapudi, Suman Banerjee:
Cloud-LoRa: Enabling Cloud Radio Access LoRa Networks Using Reinforcement Learning Based Bandwidth-Adaptive Compression. NSDI 2024- [i7]Jayaram Raghuram, George Kesidis, David J. Miller:
On Trojans in Refined Language Models. CoRR abs/2406.07778 (2024) - 2023
- [c8]Jayaram Raghuram, Yijing Zeng
, Dolores García, Rafael Ruiz, Somesh Jha, Joerg Widmer, Suman Banerjee:
Few-Shot Domain Adaptation For End-to-End Communication. ICLR 2023 - [c7]Zhenmei Shi, Jiefeng Chen, Kunyang Li, Jayaram Raghuram, Xi Wu, Yingyu Liang, Somesh Jha:
The Trade-off between Universality and Label Efficiency of Representations from Contrastive Learning. ICLR 2023 - [c6]Jiefeng Chen, Jayaram Raghuram, Jihye Choi, Xi Wu, Yingyu Liang, Somesh Jha:
Stratified Adversarial Robustness with Rejection. ICML 2023: 4867-4894 - [c5]Jihye Choi, Jayaram Raghuram, Ryan Feng, Jiefeng Chen, Somesh Jha, Atul Prakash:
Concept-based Explanations for Out-of-Distribution Detectors. ICML 2023: 5817-5837 - [i6]Zhenmei Shi, Jiefeng Chen, Kunyang Li, Jayaram Raghuram, Xi Wu, Yingyu Liang, Somesh Jha:
The Trade-off between Universality and Label Efficiency of Representations from Contrastive Learning. CoRR abs/2303.00106 (2023) - [i5]Jiefeng Chen, Jayaram Raghuram, Jihye Choi, Xi Wu, Yingyu Liang, Somesh Jha:
Stratified Adversarial Robustness with Rejection. CoRR abs/2305.01139 (2023) - 2022
- [i4]Jihye Choi, Jayaram Raghuram, Ryan Feng, Jiefeng Chen, Somesh Jha, Atul Prakash:
Concept-based Explanations for Out-Of-Distribution Detectors. CoRR abs/2203.02586 (2022) - 2021
- [c4]Jayaram Raghuram, Varun Chandrasekaran, Somesh Jha, Suman Banerjee:
A General Framework For Detecting Anomalous Inputs to DNN Classifiers. ICML 2021: 8764-8775 - [i3]Jayaram Raghuram, Yijing Zeng, Dolores García Martí, Somesh Jha, Suman Banerjee, Joerg Widmer, Rafael Ruiz Ortiz:
Domain Adaptation for Autoencoder-Based End-to-End Communication Over Wireless Channels. CoRR abs/2108.00874 (2021) - 2020
- [i2]Jayaram Raghuram, Varun Chandrasekaran, Somesh Jha, Suman Banerjee:
Detecting Anomalous Inputs to DNN Classifiers By Joint Statistical Testing at the Layers. CoRR abs/2007.15147 (2020)
2010 – 2019
- 2015
- [j3]Yuquan Shan, Jayaram Raghuram, George Kesidis, David J. Miller, Anna Scaglione, Jeff Rowe, Karl N. Levitt:
Generation bidding game with potentially false attestation of flexible demand. EURASIP J. Adv. Signal Process. 2015: 29 (2015) - 2014
- [j2]Jayaram Raghuram, David J. Miller, George Kesidis:
Instance-Level Constraint-Based Semisupervised Learning With Imposed Space-Partitioning. IEEE Trans. Neural Networks Learn. Syst. 25(8): 1520-1537 (2014) - [c3]Jayaram Raghuram, George Kesidis, Christopher Griffin, Karl N. Levitt, David J. Miller, Jeff Rowe, Anna Scaglione:
A Bidding Game for Generators in the Presence of Flexible Demand. Feedback Computing 2014 - [i1]Yuquan Shan, Jayaram Raghuram, George Kesidis, Christopher Griffin, Karl N. Levitt, David J. Miller, Jeff Rowe, Anna Scaglione:
Generation bidding game with flexible demand. CoRR abs/1408.6689 (2014) - 2012
- [j1]David J. Miller, Jayaram Raghuram, George Kesidis, Christopher M. Collins:
Improved Generative Semisupervised Learning Based on Finely Grained Component-Conditional Class Labeling. Neural Comput. 24(7): 1926-1966 (2012) - [c2]Jayaram Raghuram, David J. Miller, George Kesidis:
Semisupervised domain adaptation for mixture model based classifiers. CISS 2012: 1-6 - 2011
- [c1]Z. Berkay Celik, Jayaram Raghuram, George Kesidis, David J. Miller:
Salting Public Traces with Attack Traffic to Test Flow Classifiers. CSET 2011
Coauthor Index
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