Network-aware rate adaptation for video streaming. - Aravindan Raghuveer; Ewa Kusmierek; David Hung-Chang Du (ICME, 2004)

Techniques for efficient stream of layered video in heterogeneous client environments. - Aravindan Raghuveer; Nam Oh Kang; David H. C. Du (GLOBECOM, 2005)

Towards efficient search on unstructured data: an intelligent-storage approach. - Aravindan Raghuveer; Meera Jindal; Mohamed F. Mokbel; Biplob K. Debnath; David Hung-Chang Du (CIKM, 2007)

Enabling database-aware storage with OSD. - Aravindan Raghuveer; Steven W. Schlosser; Sami Iren (MSST, 2007)

A Network-Aware Approach for Video and Metadata Streaming. - Aravindan Raghuveer; Ewa Kusmierek; David Hung-Chang Du (IEEE Trans. Circuits Syst. Video Technol., 2007)

StatStream: providing statistical reliability guarantees in peer-to-peer live video streaming. - Aravindan Raghuveer; Yingfei Dong; David Hung-Chang Du (Int. J. Adv. Media Commun., 2010)

Automated Content Labeling using Context in Email. - Aravindan Raghuveer (COMAD, 2011)

WOOster: A Map-Reduce based Platform for Graph Mining. - Aravindan Raghuveer (COMAD, 2011)

Modeling Mobile User Actions for Purchase Recommendation using Deep Memory Networks. - Djordje Gligorijevic; Jelena Gligorijevic; Aravindan Raghuveer; Mihajlo Grbovic; Zoran Obradovic (SIGIR, 2018)

HintedBT: Augmenting Back-Translation with Quality and Transliteration Hints. - Sahana Ramnath; Melvin Johnson; Abhirut Gupta; Aravindan Raghuveer (EMNLP (1), 2021)

On Combining Bags to Better Learn from Label Proportions. - Rishi Saket; Aravindan Raghuveer; Balaraman Ravindran (AISTATS, 2022)

Domain-Agnostic Contrastive Representations for Learning from Label Proportions. - Jay Nandy; Rishi Saket; Prateek Jain; Jatin Chauhan; Balaraman Ravindran; Aravindan Raghuveer (CIKM, 2022)

T-STAR: Truthful Style Transfer using AMR Graph as Intermediate Representation. - Anubhav Jangra; Preksha Nema; Aravindan Raghuveer (EMNLP, 2022)

CoCoa: An Encoder-Decoder Model for Controllable Code-switched Generation. - Sneha Mondal; Ritika; Shreya Pathak; Preethi Jyothi; Aravindan Raghuveer (EMNLP, 2022)

Multi-Variate Time Series Forecasting on Variable Subsets. - Jatin Chauhan; Aravindan Raghuveer; Rishi Saket; Jay Nandy; Balaraman Ravindran (KDD, 2022)

Walking with PACE - Personalized and Automated Coaching Engine. - Madhurima Vardhan; Narayan Hegde; Srujana Merugu; Shantanu Prabhat; Deepak Nathani; Martin Seneviratne; Nur Muhammad; Pranay Reddy; Sriram Lakshminarasimhan; Rahul Singh; Karina Lorenzana; Eshan Motwani; et al. (UMAP, 2022)

Bi-Phone: Modeling Inter Language Phonetic Influences in Text. - Abhirut Gupta; Ananya B. Sai; Richard Sproat; Yuri Vasilevski; James S. Ren; Ambarish Jash; Sukhdeep S. Sodhi; Aravindan Raghuveer (ACL (1), 2023)

Non-Uniform Adversarial Perturbations for Discrete Tabular Datasets. - Jay Nandy; Jatin Chauhan; Rishi Saket; Aravindan Raghuveer (CIKM, 2023)

ReTAG: Reasoning Aware Table to Analytic Text Generation. - Deepanway Ghosal; Preksha Nema; Aravindan Raghuveer (EMNLP, 2023)

PAC Learning Linear Thresholds from Label Proportions. - Anand Brahmbhatt; Rishi Saket; Aravindan Raghuveer (NeurIPS, 2023)

STOAT: Structured Data to Analytical Text With Controls. - Deepanway Ghosal; Preksha Nema; Aravindan Raghuveer (CoRR, 2023)

BiPhone: Modeling Inter Language Phonetic Influences in Text. - Abhirut Gupta; Ananya B. Sai; Richard Sproat; Yuri Vasilevski; James S. Ren; Ambarish Jash; Sukhdeep S. Sodhi; Aravindan Raghuveer (CoRR, 2023)

Improving Fairness-Accuracy tradeoff with few Test Samples under Covariate Shift. - Shreyas Havaldar; Jatin Chauhan; Karthikeyan Shanmugam; Jay Nandy; Aravindan Raghuveer (CoRR, 2023)

Label Differential Privacy via Aggregation. - Anand Brahmbhatt; Rishi Saket; Shreyas Havaldar; Anshul Nasery; Aravindan Raghuveer (CoRR, 2023)

Fairness under Covariate Shift: Improving Fairness-Accuracy Tradeoff with Few Unlabeled Test Samples. - Shreyas Havaldar; Jatin Chauhan; Karthikeyan Shanmugam; Jay Nandy; Aravindan Raghuveer (AAAI, 2024)

DIMSIM: Distilled Multilingual Critics for Indic Text Simplification. - Sneha Mondal; Ritika; Ashish Agrawal; Preethi Jyothi; Aravindan Raghuveer (ACL (Findings), 2024)

LLP-Bench: A Large Scale Tabular Benchmark for Learning from Label Proportions. - Anand Brahmbhatt; Mohith Pokala; Rishi Saket; Aravindan Raghuveer (CIKM, 2024)

Learning from Label Proportions: Bootstrapping Supervised Learners via Belief Propagation. - Shreyas Havaldar; Navodita Sharma; Shubhi Sareen; Karthikeyan Shanmugam; Aravindan Raghuveer (ICLR, 2024)

Generalization and Learnability in Multiple Instance Regression. - Kushal Chauhan; Rishi Saket; Lorne Applebaum; Ashwinkumar Badanidiyuru; Chandan Giri; Aravindan Raghuveer (UAI, 2024)

Preserving Expert-Level Privacy in Offline Reinforcement Learning. - Navodita Sharma; Vishnu Vinod; Abhradeep Thakurta; Alekh Agarwal; Borja Balle; Christoph Dann; Aravindan Raghuveer (CoRR, 2024)

Aggregating Data for Optimal and Private Learning. - Sushant Agarwal; Yukti Makhija; Rishi Saket; Aravindan Raghuveer (CoRR, 2024)

FRACTAL: Fine-Grained Scoring from Aggregate Text Labels. - Yukti Makhija; Priyanka Agrawal; Rishi Saket; Aravindan Raghuveer (ACL (1), 2025)

Aggregating Data for Optimal Learning. - Sushant Agarwal; Yukti Makhija; Rishi Saket; Aravindan Raghuveer (UAI, 2025)

Learning from Label Proportions and Covariate-shifted Instances. - Sagalpreet Singh; Navodita Sharma; Shreyas Havaldar; Rishi Saket; Aravindan Raghuveer (UAI, 2025)

Robust Reward Modeling via Causal Rubrics. - Pragya Srivastava; Harman Singh; Rahul Madhavan; Gandharv Patil; Sravanti Addepalli; Arun Sai Suggala; Rengarajan Aravamudhan; Soumya Sharma; Anirban Laha; Aravindan Raghuveer; Karthikeyan Shanmugam; Doina Precup (CoRR, 2025)