Jayaram Raghuram

25 papers A* 8Misc 2Journal 13Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	CONDA: Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts. ICLR Jihye Choi, Jayaram Raghuram, Yixuan Li, Somesh Jha
2025	J	`jnl`	Inverting Trojans in LLMs. CoRR Zhengxing Li, Guangmingmei Yang, Jayaram Raghuram, David J. Miller, George Kesidis
2025	A*	`conf`	Medusa: Scalable Multi-View Biometric Sensing in the Wild with Distributed MIMO Radars. MobiCom Yilong Li, Ramanujan K. Sheshadri, Karthik Sundaresan, Eugene Chai, Yijing Zeng, Jayaram Raghuram, Suman Banerjee
2025	A*	`conf`	Palmbench: a comprehensive Benchmark of Compressed Large Language Models on Mobile Platforms. ICLR Yilong Li, Jingyu Liu, Hao Zhang, M. Badri Narayanan, Utkarsh Sharma, Shuai Zhang, Yijing Zeng, Jayaram Raghuram, Suman Banerjee
2024	J	`jnl`	Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts. CoRR Jihye Choi, Jayaram Raghuram, Yixuan Li, Somesh Jha
2024	Misc	`conf`	Cloud-LoRa: Enabling Cloud Radio Access LoRa Networks Using Reinforcement Learning Based Bandwidth-Adaptive Compression. NSDI Muhammad Osama Shahid, Daniel Jay Koch, Jayaram Raghuram, Bhuvana Krishnaswamy, Krishna Chintalapudi, Suman Banerjee
2024	J	`jnl`	On Trojans in Refined Language Models. CoRR Jayaram Raghuram, George Kesidis, David J. Miller
2024	J	`jnl`	PalmBench: A Comprehensive Benchmark of Compressed Large Language Models on Mobile Platforms. CoRR Yilong Li, Jingyu Liu, Hao Zhang, M. Badri Narayanan, Utkarsh Sharma, Shuai Zhang, Pan Hu, Yijing Zeng, Jayaram Raghuram, Suman Banerjee
2023	A*	`conf`	Concept-based Explanations for Out-of-Distribution Detectors. ICML Jihye Choi, Jayaram Raghuram, Ryan Feng, Jiefeng Chen, Somesh Jha, Atul Prakash
2023	A*	`conf`	Few-Shot Domain Adaptation For End-to-End Communication. ICLR Jayaram Raghuram, Yijing Zeng, Dolores García, Rafael Ruiz, Somesh Jha, Joerg Widmer, Suman Banerjee
2023	A*	`conf`	Stratified Adversarial Robustness with Rejection. ICML Jiefeng Chen, Jayaram Raghuram, Jihye Choi, Xi Wu, Yingyu Liang, Somesh Jha
2023	J	`jnl`	Stratified Adversarial Robustness with Rejection. CoRR Jiefeng Chen, Jayaram Raghuram, Jihye Choi, Xi Wu, Yingyu Liang, Somesh Jha
2023	A*	`conf`	The Trade-off between Universality and Label Efficiency of Representations from Contrastive Learning. ICLR Zhenmei Shi, Jiefeng Chen, Kunyang Li, Jayaram Raghuram, Xi Wu, Yingyu Liang, Somesh Jha
2023	J	`jnl`	The Trade-off between Universality and Label Efficiency of Representations from Contrastive Learning. CoRR Zhenmei Shi, Jiefeng Chen, Kunyang Li, Jayaram Raghuram, Xi Wu, Yingyu Liang, Somesh Jha
2022	J	`jnl`	Concept-based Explanations for Out-Of-Distribution Detectors. CoRR Jihye Choi, Jayaram Raghuram, Ryan Feng, Jiefeng Chen, Somesh Jha, Atul Prakash
2021	A*	`conf`	A General Framework For Detecting Anomalous Inputs to DNN Classifiers. ICML Jayaram Raghuram, Varun Chandrasekaran, Somesh Jha, Suman Banerjee
2021	J	`jnl`	Domain Adaptation for Autoencoder-Based End-to-End Communication Over Wireless Channels. CoRR Jayaram Raghuram, Yijing Zeng, Dolores García Martí, Somesh Jha, Suman Banerjee, Joerg Widmer, Rafael Ruiz Ortiz
2020	J	`jnl`	Detecting Anomalous Inputs to DNN Classifiers By Joint Statistical Testing at the Layers. CoRR Jayaram Raghuram, Varun Chandrasekaran, Somesh Jha, Suman Banerjee
2015	J	`jnl`	Generation bidding game with potentially false attestation of flexible demand. EURASIP J. Adv. Signal Process. Yuquan Shan, Jayaram Raghuram, George Kesidis, David J. Miller, Anna Scaglione, Jeff Rowe, Karl N. Levitt
2014	—	`conf`	A Bidding Game for Generators in the Presence of Flexible Demand. Feedback Computing Jayaram Raghuram, George Kesidis, Christopher Griffin, Karl N. Levitt, David J. Miller, Jeff Rowe, Anna Scaglione
2014	J	`jnl`	Generation bidding game with flexible demand. CoRR Yuquan Shan, Jayaram Raghuram, George Kesidis, Christopher Griffin, Karl N. Levitt, David J. Miller, Jeff Rowe, Anna Scaglione
2014	J	`jnl`	Instance-Level Constraint-Based Semisupervised Learning With Imposed Space-Partitioning. IEEE Trans. Neural Networks Learn. Syst. Jayaram Raghuram, David J. Miller, George Kesidis
2012	J	`jnl`	Improved Generative Semisupervised Learning Based on Finely Grained Component-Conditional Class Labeling. Neural Comput. David J. Miller, Jayaram Raghuram, George Kesidis, Christopher M. Collins
2012	Misc	`conf`	Semisupervised domain adaptation for mixture model based classifiers. CISS Jayaram Raghuram, David J. Miller, George Kesidis
2011	—	`conf`	Salting Public Traces with Attack Traffic to Test Flow Classifiers. CSET Z. Berkay Celik, Jayaram Raghuram, George Kesidis, David J. Miller