Object Mining for Large Video data. - Ronak Shah; Rishabh K. Iyer; Subhasis Chaudhuri (BMVC, 2011)

Estimation of the Embedding Capacity in Pixel-pair based Watermarking Schemes - Rishabh K. Iyer; Rushikesh Borse; Ronak Shah; Subhasis Chaudhuri (CoRR, 2011)

Submodular-Bregman and the Lovász-Bregman Divergences with Applications. - Rishabh K. Iyer; Jeff A. Bilmes (NIPS, 2012)

Algorithms for Approximate Minimization of the Difference Between Submodular Functions, with Applications. - Rishabh K. Iyer; Jeff A. Bilmes (UAI, 2012)

Fast Semidifferential-based Submodular Function Optimization. - Rishabh K. Iyer; Stefanie Jegelka; Jeff A. Bilmes (ICML (3), 2013)

Submodular Optimization with Submodular Cover and Submodular Knapsack Constraints. - Rishabh K. Iyer; Jeff A. Bilmes (NIPS, 2013)

Curvature and Optimal Algorithms for Learning and Minimizing Submodular Functions. - Rishabh K. Iyer; Stefanie Jegelka; Jeff A. Bilmes (NIPS, 2013)

The Lovasz-Bregman Divergence and connections to rank aggregation, clustering, and web ranking. - Rishabh K. Iyer; Jeff A. Bilmes (UAI, 2013)

Fast Multi-stage Submodular Maximization. - Kai Wei; Rishabh K. Iyer; Jeff A. Bilmes (ICML, 2014)

Learning Mixtures of Submodular Functions for Image Collection Summarization. - Sebastian Tschiatschek; Rishabh K. Iyer; Haochen Wei; Jeff A. Bilmes (NIPS, 2014)

Monotone Closure of Relaxed Constraints in Submodular Optimization: Connections Between Minimization and Maximization. - Rishabh K. Iyer; Stefanie Jegelka; Jeff A. Bilmes (UAI, 2014)

Summarization of Multi-Document Topic Hierarchies using Submodular Mixtures. - Ramakrishna Bairi; Rishabh K. Iyer; Ganesh Ramakrishnan; Jeff A. Bilmes (ACL (1), 2015)

Submodular Point Processes with Applications to Machine learning. - Rishabh K. Iyer; Jeff A. Bilmes (AISTATS, 2015)

On Approximate Non-submodular Minimization via Tree-Structured Supermodularity. - Yoshinobu Kawahara; Rishabh K. Iyer; Jeff A. Bilmes (AISTATS, 2015)

Submodularity in Data Subset Selection and Active Learning. - Kai Wei; Rishabh K. Iyer; Jeff A. Bilmes (ICML, 2015)

SVitchboard II and fiSVer i: high-quality limited-complexity corpora of conversational English speech. - Yuzong Liu; Rishabh K. Iyer; Katrin Kirchhoff; Jeff A. Bilmes (INTERSPEECH, 2015)

Submodular Hamming Metrics. - Jennifer Gillenwater; Rishabh K. Iyer; Bethany Lusch; Rahul Kidambi; Jeff A. Bilmes (NIPS, 2015)

Mixed Robust/Average Submodular Partitioning: Fast Algorithms, Guarantees, and Applications. - Kai Wei; Rishabh K. Iyer; Shengjie Wang; Wenruo Bai; Jeff A. Bilmes (NIPS, 2015)

Polyhedral aspects of Submodularity, Convexity and Concavity. - Rishabh K. Iyer; Jeff A. Bilmes (CoRR, 2015)

Mixed Robust/Average Submodular Partitioning: Fast Algorithms, Guarantees, and Applications to Parallel Machine Learning and Multi-Label Image Segmentation. - Kai Wei; Rishabh K. Iyer; Shengjie Wang; Wenruo Bai; Jeff A. Bilmes (CoRR, 2015)

Algorithms for Optimizing the Ratio of Submodular Functions. - Wenruo Bai; Rishabh K. Iyer; Kai Wei; Jeff A. Bilmes (ICML, 2016)

A Unified Multi-Faceted Video Summarization System. - Anurag Sahoo; Vishal Kaushal; Khoshrav Doctor; Suyash Shetty; Rishabh K. Iyer; Ganesh Ramakrishnan (CoRR, 2017)

SVitchboard-II and FiSVer-I: Crafting high quality and low complexity conversational english speech corpora using submodular function optimization. - Yuzong Liu; Rishabh K. Iyer; Katrin Kirchhoff; Jeff A. Bilmes (Comput. Speech Lang., 2017)

Modeling and Simultaneously Removing Bias via Adversarial Neural Networks. - John Moore; Joel Pfeiffer; Kai Wei; Rishabh K. Iyer; Denis Charles; Ran Gilad-Bachrach; Levi Boyles; Eren Manavoglu (CoRR, 2018)

Deployment of Customized Deep Learning based Video Analytics On Surveillance Cameras. - Pratik Dubal; Rohan Mahadev; Suraj Kothawade; Kunal Dargan; Rishabh K. Iyer (CoRR, 2018)

Learning From Less Data: Diversified Subset Selection and Active Learning in Image Classification Tasks. - Vishal Kaushal; Anurag Sahoo; Khoshrav Doctor; Narasimha Raju Uppalapati; Suyash Shetty; Pankaj Singh; Rishabh K. Iyer; Ganesh Ramakrishnan (CoRR, 2018)

Jensen: An Easily-Extensible C++ Toolkit for Production-Level Machine Learning and Convex Optimization. - Rishabh K. Iyer; John T. Halloran; Kai Wei (CoRR, 2018)

A Unified Batch Online Learning Framework for Click Prediction. - Rishabh K. Iyer; Nimit Acharya; Tanuja Bompada; Denis Charles; Eren Manavoglu (CoRR, 2018)

Vis-DSS: An Open-Source toolkit for Visual Data Selection and Summarization. - Rishabh K. Iyer; Pratik Dubal; Kunal Dargan; Suraj Kothawade; Rohan Mahadev; Vishal Kaushal (CoRR, 2018)

Near Optimal Algorithms for Hard Submodular Programs with Discounted Cooperative Costs. - Rishabh K. Iyer; Jeffrey A. Bilmes (AISTATS, 2019)

A Memoization Framework for Scaling Submodular Optimization to Large Scale Problems. - Rishabh K. Iyer; Jeffrey A. Bilmes (AISTATS, 2019)

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 (WACV, 2019)

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 (WACV, 2019)

A Framework Towards Domain Specific Video Summarization. - Vishal Kaushal; Sandeep Subramanian; Suraj Kothawade; Rishabh K. Iyer; Ganesh Ramakrishnan (WACV, 2019)

A Unified Framework of Robust Submodular Optimization. - Rishabh K. Iyer (CoRR, 2019)

Robust Submodular Minimization with Applications to Cooperative Modeling. - Rishabh K. Iyer (ECAI, 2020)

Watch Hours in Minutes: Summarizing Videos with User Intent. - Saiteja Nalla; Mohit Agrawal; Vishal Kaushal; Ganesh Ramakrishnan; Rishabh K. Iyer (ECCV Workshops (5), 2020)

Concave Aspects of Submodular Functions. - Rishabh K. Iyer; Jeff A. Bilmes (ISIT, 2020)

Cost Aware Feature Elicitation. - Srijita Das 001; Rishabh K. Iyer; Sriraam Natarajan (KiML@KDD, 2020)

Realistic Video Summarization through VISIOCITY: A New Benchmark and Evaluation Framework. - Vishal Kaushal; Suraj Kothawade; Rishabh K. Iyer; Ganesh Ramakrishnan (AI4TV@MM, 2020)

Data Programming using Semi-Supervision and Subset Selection. - Ayush Maheshwari; Oishik Chatterjee; KrishnaTeja Killamsetty; Rishabh K. Iyer; Ganesh Ramakrishnan (CoRR, 2020)

Robust Semi-Supervised Learning with Out of Distribution Data. - Xujiang Zhao; KrishnaTeja Killamsetty; Rishabh K. Iyer; Feng Chen 001 (CoRR, 2020)

A Unified Framework for Generic, Query-Focused, Privacy Preserving and Update Summarization using Submodular Information Measures. - Vishal Kaushal; Suraj Kothawade; Ganesh Ramakrishnan; Jeff A. Bilmes; Himanshu Asnani; Rishabh K. Iyer (CoRR, 2020)

Deep Submodular Networks for Extractive Data Summarization. - Suraj Kothawade; Jiten Girdhar; Chandrashekhar Lavania; Rishabh K. Iyer (CoRR, 2020)

A Reweighted Meta Learning Framework for Robust Few Shot Learning. - KrishnaTeja Killamsetty; Changbin Li; Chen Zhao 010; Rishabh K. Iyer; Feng Chen 001 (CoRR, 2020)

GLISTER: Generalization based Data Subset Selection for Efficient and Robust Learning. - KrishnaTeja Killamsetty; Durga Sivasubramanian; Ganesh Ramakrishnan; Rishabh K. Iyer (AAAI, 2021)

Semi-Supervised Data Programming with Subset Selection. - Ayush Maheshwari; Oishik Chatterjee; KrishnaTeja Killamsetty; Ganesh Ramakrishnan; Rishabh K. Iyer (ACL/IJCNLP (Findings), 2021)

Rule Augmented Unsupervised Constituency Parsing. - Atul Sahay; Anshul Nasery; Ayush Maheshwari; Ganesh Ramakrishnan; Rishabh K. Iyer (ACL/IJCNLP (Findings), 2021)

Submodular combinatorial information measures with applications in machine learning. - Rishabh K. Iyer; Ninad Khargoankar; Jeff A. Bilmes; Himanshu Asanani (ALT, 2021)

A Clustering based Selection Framework for Cost Aware and Test-time Feature Elicitation. - Srijita Das 001; Rishabh K. Iyer; Sriraam Natarajan (COMAD/CODS, 2021)

GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training. - KrishnaTeja Killamsetty; Durga Sivasubramanian; Ganesh Ramakrishnan; Abir De; Rishabh K. Iyer (ICML, 2021)

Training Data Subset Selection for Regression with Controlled Generalization Error. - Durga Sivasubramanian; Rishabh K. Iyer; Ganesh Ramakrishnan; Abir De (ICML, 2021)

Independence Properties of Generalized Submodular Information Measures. - Himanshu Asnani; Jeff A. Bilmes; Rishabh K. Iyer (ISIT, 2021)

RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised Learning. - KrishnaTeja Killamsetty; Xujiang Zhao; Feng Chen 001; Rishabh K. Iyer (NeurIPS, 2021)

SIMILAR: Submodular Information Measures Based Active Learning In Realistic Scenarios. - Suraj Kothawade; Nathan Beck; KrishnaTeja Killamsetty; Rishabh K. Iyer (NeurIPS, 2021)

Learning to Select Exogenous Events for Marked Temporal Point Process. - Ping Zhang; Rishabh K. Iyer; Ashish Tendulkar; Gaurav Aggarwal; Abir De (NeurIPS, 2021)

A Practical Online Framework for Extracting Running Video Summaries under a Fixed Memory Budget. - Chandrashekhar Lavania; Kai Wei; Rishabh K. Iyer; Jeff A. Bilmes (SDM, 2021)

How Good is a Video Summary? A New Benchmarking Dataset and Evaluation Framework Towards Realistic Video Summarization. - Vishal Kaushal; Suraj Kothawade; Anshul Tomar; Rishabh K. Iyer; Ganesh Ramakrishnan (CoRR, 2021)

GRAD-MATCH: A Gradient Matching Based Data Subset Selection for Efficient Learning. - KrishnaTeja Killamsetty; Durga Sivasubramanian; Baharan Mirzasoleiman; Ganesh Ramakrishnan; Abir De; Rishabh K. Iyer (CoRR, 2021)

PRISM: A Unified Framework of Parameterized Submodular Information Measures for Targeted Data Subset Selection and Summarization. - Vishal Kaushal; Suraj Kothawade; Ganesh Ramakrishnan; Jeff A. Bilmes; Rishabh K. Iyer (CoRR, 2021)

Submodular Mutual Information for Targeted Data Subset Selection. - Suraj Kothawade; Vishal Kaushal; Ganesh Ramakrishnan; Jeff A. Bilmes; Rishabh K. Iyer (CoRR, 2021)

Effective Evaluation of Deep Active Learning on Image Classification Tasks. - Nathan Beck; Durga Sivasubramanian; Apurva Dani; Ganesh Ramakrishnan; Rishabh K. Iyer (CoRR, 2021)

Personalizing ASR with limited data using targeted subset selection. - Mayank Kothyari; Anmol Reddy Mekala; Rishabh K. Iyer; Ganesh Ramakrishnan; Preethi Jyothi (CoRR, 2021)

A Nested Bi-level Optimization Framework for Robust Few Shot Learning. - KrishnaTeja Killamsetty; Changbin Li; Chen Zhao 010; Feng Chen 001; Rishabh K. Iyer (AAAI, 2022)

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 (AAAI, 2022)

Learning to Robustly Aggregate Labeling Functions for Semi-supervised Data Programming. - Ayush Maheshwari; KrishnaTeja Killamsetty; Ganesh Ramakrishnan; Rishabh K. Iyer; Marina Danilevsky; Lucian Popa 001 (ACL (Findings), 2022)

GCR: Gradient Coreset based Replay Buffer Selection for Continual Learning. - Rishabh Tiwari; KrishnaTeja Killamsetty; Rishabh K. Iyer; Pradeep Shenoy (CVPR, 2022)

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 (ECCV (38), 2022)

SPEAR : Semi-supervised Data Programming in Python. - Guttu Sai Abhishek; Harshad Ingole; Parth Laturia; Vineeth Dorna; Ayush Maheshwari; Ganesh Ramakrishnan; Rishabh K. Iyer (EMNLP (Demos), 2022)

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 (EMNLP (Findings), 2022)

How Out-of-Distribution Data Hurts Semi-Supervised Learning. - Xujiang Zhao; KrishnaTeja Killamsetty; Rishabh K. Iyer; Feng Chen 001 (ICDM, 2022)

PLATINUM: Semi-Supervised Model Agnostic Meta-Learning using Submodular Mutual Information. - Changbin Li; Suraj Kothawade; Feng Chen 001; Rishabh K. Iyer (ICML, 2022)

CLINICAL: Targeted Active Learning for Imbalanced Medical Image Classification. - Suraj Kothawade; Atharv Savarkar; Venkat Iyer; Ganesh Ramakrishnan; Rishabh K. Iyer (MILLanD@MICCAI, 2022)

DIAGNOSE: Avoiding Out-of-Distribution Data Using Submodular Information Measures. - Suraj Kothawade; Akshit Shrivastava; Venkat Iyer; Ganesh Ramakrishnan; Rishabh K. Iyer (MILLanD@MICCAI, 2022)

ORIENT: Submodular Mutual Information Measures for Data Subset Selection under Distribution Shift. - Athresh Karanam; KrishnaTeja Killamsetty; Harsha Kokel; Rishabh K. Iyer (NeurIPS, 2022)

AUTOMATA: Gradient Based Data Subset Selection for Compute-Efficient Hyper-parameter Tuning. - KrishnaTeja Killamsetty; Guttu Sai Abhishek; Aakriti; Ganesh Ramakrishnan; Alexandre V. Evfimievski; Lucian Popa 001; Rishabh K. Iyer (NeurIPS, 2022)

Submodlib: A Submodular Optimization Library. - Vishal Kaushal; Ganesh Ramakrishnan; Rishabh K. Iyer (CoRR, 2022)

BASIL: Balanced Active Semi-supervised Learning for Class Imbalanced Datasets. - Suraj Kothawade; Pavan Kumar Reddy; Ganesh Ramakrishnan; Rishabh K. Iyer (CoRR, 2022)

Active Data Discovery: Mining Unknown Data using Submodular Information Measures. - Suraj Kothawade; Shivang Chopra; Saikat Ghosh; Rishabh K. Iyer (CoRR, 2022)

CLINICAL: Targeted Active Learning for Imbalanced Medical Image Classification. - Suraj Kothawade; Atharv Savarkar; Venkat Iyer; Lakshman Tamil; Ganesh Ramakrishnan; Rishabh K. Iyer (CoRR, 2022)

Generalized Submodular Information Measures: Theoretical Properties, Examples, Optimization Algorithms, and Applications. - Rishabh K. Iyer; Ninad Khargonkar; Jeff A. Bilmes; Himanshu Asnani (IEEE Trans. Inf. Theory, 2022)

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 (ACL (1), 2023)

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 (EMNLP (Findings), 2023)

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 (ICML, 2023)

Efficient Data Subset Selection to Generalize Training Across Models: Transductive and Inductive Networks. - Eeshaan Jain; Tushar Nandy; Gaurav Aggarwal; Ashish Tendulkar; Rishabh K. Iyer; Abir De (NeurIPS, 2023)

MILO: Model-Agnostic Subset Selection Framework for Efficient Model Training and Tuning. - KrishnaTeja Killamsetty; Alexandre V. Evfimievski; Tejaswini Pedapati; Kiran Kate; Lucian Popa 001; Rishabh K. Iyer (CoRR, 2023)

INGENIOUS: Using Informative Data Subsets for Efficient Pre-Training of Large Language Models. - H. S. V. N. S. Kowndinya Renduchintala; Krishnateja Killamsetty; Sumit Bhatia; Milan Aggarwal; Ganesh Ramakrishnan; Rishabh K. Iyer; Balaji Krishnamurthy (CoRR, 2023)

STREAMLINE: Streaming Active Learning for Realistic Multi-Distributional Settings. - Nathan Beck; Suraj Kothawade; Pradeep Shenoy; Rishabh K. Iyer (CoRR, 2023)

SCoRe: Submodular Combinatorial Representation Learning for Real-World Class-Imbalanced Settings. - Anay Majee; Suraj Kothawade; Krishnateja Killamsetty; Rishabh K. Iyer (CoRR, 2023)

SMILe: Leveraging Submodular Mutual Information For Robust Few-Shot Object Detection. - Anay Majee; Ryan Sharp; Rishabh K. Iyer (ECCV (32), 2024)

SCoRe: Submodular Combinatorial Representation Learning. - Anay Majee; Suraj Kothawade; Krishnateja Killamsetty; Rishabh K. Iyer (ICML, 2024)

STONE: A Submodular Optimization Framework for Active 3D Object Detection. - Ruiyu Mao; Sarthak Kumar Maharana; Rishabh K. Iyer; Yunhui Guo (NeurIPS, 2024)

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 (WACV, 2024)

Gradient Coreset for Federated Learning. - Durga Sivasubramanian; Lokesh Nagalapatti; Rishabh K. Iyer; Ganesh Ramakrishnan (WACV, 2024)

Theoretical Analysis of Submodular Information Measures for Targeted Data Subset Selection. - Nathan Beck; Truong Pham; Rishabh K. Iyer (CoRR, 2024)

STENCIL: Submodular Mutual Information Based Weak Supervision for Cold-Start Active Learning. - Nathan Beck; Adithya Iyer; Rishabh K. Iyer (CoRR, 2024)