| 2025 | ICDM | InSQuaD: In-Context Learning for Efficient Retrieval via Submodular Mutual Information to Enforce Quality and Diversity. | Souradeep Nanda, Anay Majee, Rishabh K. Iyer |
| 2024 | ECCV | SMILe: Leveraging Submodular Mutual Information For Robust Few-Shot Object Detection. | Anay Majee, Ryan Sharp, Rishabh K. Iyer |
| 2024 | ICML | SCoRe: Submodular Combinatorial Representation Learning. | Anay Majee, Suraj Kothawade, Krishnateja Killamsetty, Rishabh K. Iyer |
| 2024 | WACV | Beyond Active Learning: Leveraging the Full Potential of Human Interaction via Auto-Labeling, Human Correction, and Human Verification. | Nathan Beck, Krishnateja Killamsetty, Suraj Kothawade, Rishabh K. Iyer |
| 2024 | WACV | Gradient Coreset for Federated Learning. | Durga Sivasubramanian, Lokesh Nagalapatti, Rishabh K. Iyer, Ganesh Ramakrishnan |
| 2023 | ACL | DITTO: Data-efficient and Fair Targeted Subset Selection for ASR Accent Adaptation. | Suraj Kothawade, Anmol Reddy Mekala, D. Chandra Sekhara Hetha Havya, Mayank Kothyari, Rishabh K. Iyer, Ganesh Ramakrishnan, Preethi Jyothi |
| 2023 | EMNLP | INGENIOUS: Using Informative Data Subsets for Efficient Pre-Training of Language Models. | H. S. V. N. S. Kowndinya Renduchintala, Krishnateja Killamsetty, Sumit Bhatia, Milan Aggarwal, Ganesh Ramakrishnan, Rishabh K. Iyer, Balaji Krishnamurthy |
| 2023 | ICML | Discrete Continuous Optimization Framework for Simultaneous Clustering and Training in Mixture Models. | Parth Vipul Sangani, Arjun Shashank Kashettiwar, Pritish Chakraborty, Bhuvan Reddy Gangula, Durga Sivasubramanian, Ganesh Ramakrishnan, Rishabh K. Iyer, Abir De |
| 2022 | AAAI | A Nested Bi-level Optimization Framework for Robust Few Shot Learning. | KrishnaTeja Killamsetty, Changbin Li, Chen Zhao, Feng Chen, Rishabh K. Iyer |
| 2022 | AAAI | PRISM: A Rich Class of Parameterized Submodular Information Measures for Guided Data Subset Selection. | Suraj Kothawade, Vishal Kaushal, Ganesh Ramakrishnan, Jeff A. Bilmes, Rishabh K. Iyer |
| 2022 | ACL | Learning to Robustly Aggregate Labeling Functions for Semi-supervised Data Programming. | Ayush Maheshwari, KrishnaTeja Killamsetty, Ganesh Ramakrishnan, Rishabh K. Iyer, Marina Danilevsky, Lucian Popa |
| 2022 | CVPR | GCR: Gradient Coreset based Replay Buffer Selection for Continual Learning. | Rishabh Tiwari, KrishnaTeja Killamsetty, Rishabh K. Iyer, Pradeep Shenoy |
| 2022 | ECCV | Talisman: Targeted Active Learning for Object Detection with Rare Classes and Slices Using Submodular Mutual Information. | Suraj Kothawade, Saikat Ghosh, Sumit Shekhar, Yu Xiang, Rishabh K. Iyer |
| 2022 | EMNLP | SPEAR : Semi-supervised Data Programming in Python. | Guttu Sai Abhishek, Harshad Ingole, Parth Laturia, Vineeth Dorna, Ayush Maheshwari, Ganesh Ramakrishnan, Rishabh K. Iyer |
| 2022 | EMNLP | Partitioned Gradient Matching-based Data Subset Selection for Compute-Efficient Robust ASR Training. | Ashish R. Mittal, Durga Sivasubramanian, Rishabh K. Iyer, Preethi Jyothi, Ganesh Ramakrishnan |
| 2022 | ICDM | How Out-of-Distribution Data Hurts Semi-Supervised Learning. | Xujiang Zhao, KrishnaTeja Killamsetty, Rishabh K. Iyer, Feng Chen |
| 2022 | ICML | PLATINUM: Semi-Supervised Model Agnostic Meta-Learning using Submodular Mutual Information. | Changbin Li, Suraj Kothawade, Feng Chen, Rishabh K. Iyer |
| 2022 | MICCAI | CLINICAL: Targeted Active Learning for Imbalanced Medical Image Classification. | Suraj Kothawade, Atharv Savarkar, Venkat Iyer, Ganesh Ramakrishnan, Rishabh K. Iyer |
| 2022 | MICCAI | DIAGNOSE: Avoiding Out-of-Distribution Data Using Submodular Information Measures. | Suraj Kothawade, Akshit Shrivastava, Venkat Iyer, Ganesh Ramakrishnan, Rishabh K. Iyer |
| 2021 | AAAI | GLISTER: Generalization based Data Subset Selection for Efficient and Robust Learning. | KrishnaTeja Killamsetty, Durga Sivasubramanian, Ganesh Ramakrishnan, Rishabh K. Iyer |
| 2021 | ACL | Semi-Supervised Data Programming with Subset Selection. | Ayush Maheshwari, Oishik Chatterjee, KrishnaTeja Killamsetty, Ganesh Ramakrishnan, Rishabh K. Iyer |
| 2021 | ACL | Rule Augmented Unsupervised Constituency Parsing. | Atul Sahay, Anshul Nasery, Ayush Maheshwari, Ganesh Ramakrishnan, Rishabh K. Iyer |
| 2021 | ALT | Submodular combinatorial information measures with applications in machine learning. | Rishabh K. Iyer, Ninad Khargoankar, Jeff A. Bilmes, Himanshu Asanani |
| 2021 | COMAD | A Clustering based Selection Framework for Cost Aware and Test-time Feature Elicitation. | Srijita Das, Rishabh K. Iyer, Sriraam Natarajan |
| 2021 | ICML | GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training. | KrishnaTeja Killamsetty, Durga Sivasubramanian, Ganesh Ramakrishnan, Abir De, Rishabh K. Iyer |
| 2021 | ICML | Training Data Subset Selection for Regression with Controlled Generalization Error. | Durga Sivasubramanian, Rishabh K. Iyer, Ganesh Ramakrishnan, Abir De |
| 2021 | ISIT | Independence Properties of Generalized Submodular Information Measures. | Himanshu Asnani, Jeff A. Bilmes, Rishabh K. Iyer |
| 2021 | SDM | A Practical Online Framework for Extracting Running Video Summaries under a Fixed Memory Budget. | Chandrashekhar Lavania, Kai Wei, Rishabh K. Iyer, Jeff A. Bilmes |
| 2020 | ECAI | Robust Submodular Minimization with Applications to Cooperative Modeling. | Rishabh K. Iyer |
| 2020 | ECCV | Watch Hours in Minutes: Summarizing Videos with User Intent. | Saiteja Nalla, Mohit Agrawal, Vishal Kaushal, Ganesh Ramakrishnan, Rishabh K. Iyer |
| 2020 | ISIT | Concave Aspects of Submodular Functions. | Rishabh K. Iyer, Jeff A. Bilmes |
| 2020 | KDD | Cost Aware Feature Elicitation. | Srijita Das, Rishabh K. Iyer, Sriraam Natarajan |
| 2019 | AISTATS | Near Optimal Algorithms for Hard Submodular Programs with Discounted Cooperative Costs. | Rishabh K. Iyer, Jeffrey A. Bilmes |
| 2019 | AISTATS | A Memoization Framework for Scaling Submodular Optimization to Large Scale Problems. | Rishabh K. Iyer, Jeffrey A. Bilmes |
| 2019 | WACV | Demystifying Multi-Faceted Video Summarization: Tradeoff Between Diversity, Representation, Coverage and Importance. | Vishal Kaushal, Rishabh K. Iyer, Khoshrav Doctor, Anurag Sahoo, Pratik Dubal, Suraj Kothawade, Rohan Mahadev, Kunal Dargan, Ganesh Ramakrishnan |
| 2019 | WACV | Learning From Less Data: A Unified Data Subset Selection and Active Learning Framework for Computer Vision. | Vishal Kaushal, Rishabh K. Iyer, Suraj Kothawade, Rohan Mahadev, Khoshrav Doctor, Ganesh Ramakrishnan |
| 2019 | WACV | A Framework Towards Domain Specific Video Summarization. | Vishal Kaushal, Sandeep Subramanian, Suraj Kothawade, Rishabh K. Iyer, Ganesh Ramakrishnan |
| 2016 | ICML | Algorithms for Optimizing the Ratio of Submodular Functions. | Wenruo Bai, Rishabh K. Iyer, Kai Wei, Jeff A. Bilmes |
| 2015 | ACL | Summarization of Multi-Document Topic Hierarchies using Submodular Mixtures. | Ramakrishna Bairi, Rishabh K. Iyer, Ganesh Ramakrishnan, Jeff A. Bilmes |
| 2015 | AISTATS | Submodular Point Processes with Applications to Machine learning. | Rishabh K. Iyer, Jeff A. Bilmes |
| 2015 | AISTATS | On Approximate Non-submodular Minimization via Tree-Structured Supermodularity. | Yoshinobu Kawahara, Rishabh K. Iyer, Jeff A. Bilmes |
| 2015 | ICML | Submodularity in Data Subset Selection and Active Learning. | Kai Wei, Rishabh K. Iyer, Jeff A. Bilmes |
| 2015 | Interspeech | SVitchboard II and fiSVer i: high-quality limited-complexity corpora of conversational English speech. | Yuzong Liu, Rishabh K. Iyer, Katrin Kirchhoff, Jeff A. Bilmes |
| 2014 | ICML | Fast Multi-stage Submodular Maximization. | Kai Wei, Rishabh K. Iyer, Jeff A. Bilmes |
| 2014 | UAI | Monotone Closure of Relaxed Constraints in Submodular Optimization: Connections Between Minimization and Maximization. | Rishabh K. Iyer, Stefanie Jegelka, Jeff A. Bilmes |
| 2013 | ICML | Fast Semidifferential-based Submodular Function Optimization. | Rishabh K. Iyer, Stefanie Jegelka, Jeff A. Bilmes |
| 2013 | UAI | The Lovasz-Bregman Divergence and connections to rank aggregation, clustering, and web ranking. | Rishabh K. Iyer, Jeff A. Bilmes |
| 2012 | UAI | Algorithms for Approximate Minimization of the Difference Between Submodular Functions, with Applications. | Rishabh K. Iyer, Jeff A. Bilmes |
| 2011 | BMVC | Object Mining for Large Video data. | Ronak Shah, Rishabh K. Iyer, Subhasis Chaudhuri |