Salting Public Traces with Attack Traffic to Test Flow Classifiers. - Z. Berkay Celik; Jayaram Raghuram; George Kesidis; David J. Miller 001 (CSET, 2011)

Semisupervised domain adaptation for mixture model based classifiers. - Jayaram Raghuram; David J. Miller 001; George Kesidis (CISS, 2012)

Improved Generative Semisupervised Learning Based on Finely Grained Component-Conditional Class Labeling. - David J. Miller 001; Jayaram Raghuram; George Kesidis; Christopher M. Collins 002 (Neural Comput., 2012)

A Bidding Game for Generators in the Presence of Flexible Demand. - Jayaram Raghuram; George Kesidis; Christopher Griffin 001; Karl N. Levitt; David J. Miller 001; Jeff Rowe; Anna Scaglione (Feedback Computing, 2014)

Generation bidding game with flexible demand. - Yuquan Shan; Jayaram Raghuram; George Kesidis; Christopher Griffin 001; Karl N. Levitt; David J. Miller 001; Jeff Rowe; Anna Scaglione (CoRR, 2014)

Instance-Level Constraint-Based Semisupervised Learning With Imposed Space-Partitioning. - Jayaram Raghuram; David J. Miller 001; George Kesidis (IEEE Trans. Neural Networks Learn. Syst., 2014)

Generation bidding game with potentially false attestation of flexible demand. - Yuquan Shan; Jayaram Raghuram; George Kesidis; David J. Miller 001; Anna Scaglione; Jeff Rowe; Karl N. Levitt (EURASIP J. Adv. Signal Process., 2015)

Detecting Anomalous Inputs to DNN Classifiers By Joint Statistical Testing at the Layers. - Jayaram Raghuram; Varun Chandrasekaran; Somesh Jha; Suman Banerjee 001 (CoRR, 2020)

A General Framework For Detecting Anomalous Inputs to DNN Classifiers. - Jayaram Raghuram; Varun Chandrasekaran; Somesh Jha; Suman Banerjee 001 (ICML, 2021)

Domain Adaptation for Autoencoder-Based End-to-End Communication Over Wireless Channels. - Jayaram Raghuram; Yijing Zeng; Dolores García Martí; Somesh Jha; Suman Banerjee 001; Joerg Widmer; Rafael Ruiz Ortiz 001 (CoRR, 2021)

Few-Shot Domain Adaptation For End-to-End Communication. - Jayaram Raghuram; Yijing Zeng; Dolores García 001; Rafael Ruiz 001; Somesh Jha; Joerg Widmer; Suman Banerjee 001 (ICLR, 2023)

The Trade-off between Universality and Label Efficiency of Representations from Contrastive Learning. - Zhenmei Shi; Jiefeng Chen 001; Kunyang Li 001; Jayaram Raghuram; Xi Wu 001; Yingyu Liang; Somesh Jha (ICLR, 2023)

Stratified Adversarial Robustness with Rejection. - Jiefeng Chen 001; Jayaram Raghuram; Jihye Choi; Xi Wu 001; Yingyu Liang; Somesh Jha (ICML, 2023)

Concept-based Explanations for Out-of-Distribution Detectors. - Jihye Choi; Jayaram Raghuram; Ryan Feng; Jiefeng Chen 001; Somesh Jha; Atul Prakash 001 (ICML, 2023)

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 001 (NSDI, 2024)

On Trojans in Refined Language Models. - Jayaram Raghuram; George Kesidis; David J. Miller 001 (CoRR, 2024)

PalmBench: A Comprehensive Benchmark of Compressed Large Language Models on Mobile Platforms. - Yilong Li; Jingyu Liu; Hao Zhang; M. Badri Narayanan; Utkarsh Sharma; Shuai Zhang; Pan Hu; Yijing Zeng; Jayaram Raghuram; Suman Banerjee 001 (CoRR, 2024)

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts. - Jihye Choi; Jayaram Raghuram; Yixuan Li 001; Somesh Jha (CoRR, 2024)

CONDA: Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts. - Jihye Choi; Jayaram Raghuram; Yixuan Li 001; Somesh Jha (ICLR, 2025)

Palmbench: a comprehensive Benchmark of Compressed Large Language Models on Mobile Platforms. - Yilong Li; Jingyu Liu; Hao Zhang; M. Badri Narayanan; Utkarsh Sharma; Shuai Zhang; Yijing Zeng; Jayaram Raghuram; Suman Banerjee 001 (ICLR, 2025)