Rishabh K. Iyer

ORCID

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 99

Top Venues

Publications

Nathan Beck, Krishnateja Killamsetty, Suraj Kothawade, Rishabh K. Iyer
Beyond Active Learning: Leveraging the Full Potential of Human Interaction via Auto-Labeling, Human Correction, and Human Verification. WACV (2024)
Durga Sivasubramanian, Lokesh Nagalapatti, Rishabh K. Iyer, Ganesh Ramakrishnan
Gradient Coreset for Federated Learning. CoRR (2024)
Nathan Beck, Truong Pham, Rishabh K. Iyer
Theoretical Analysis of Submodular Information Measures for Targeted Data Subset Selection. CoRR (2024)
Anay Majee, Ryan Sharp, Rishabh K. Iyer
SMILe: Leveraging Submodular Mutual Information For Robust Few-Shot Object Detection. CoRR (2024)
Nathan Beck, Adithya Iyer, Rishabh K. Iyer
STENCIL: Submodular Mutual Information Based Weak Supervision for Cold-Start Active Learning. CoRR (2024)
Durga Sivasubramanian, Lokesh Nagalapatti, Rishabh K. Iyer, Ganesh Ramakrishnan
Gradient Coreset for Federated Learning. WACV (2024)
Nathan Beck, Krishnateja Killamsetty, Suraj Kothawade, Rishabh K. Iyer
Beyond Active Learning: Leveraging the Full Potential of Human Interaction via Auto-Labeling, Human Correction, and Human Verification. CoRR (2023)
H. S. V. N. S. Kowndinya Renduchintala, Krishnateja Killamsetty, Sumit Bhatia, Milan Aggarwal, Ganesh Ramakrishnan, Rishabh K. Iyer, Balaji Krishnamurthy
INGENIOUS: Using Informative Data Subsets for Efficient Pre-Training of Large Language Models. CoRR (2023)
Eeshaan Jain, Tushar Nandy, Gaurav Aggarwal, Ashish Tendulkar, Rishabh K. Iyer, Abir De
Efficient Data Subset Selection to Generalize Training Across Models: Transductive and Inductive Networks. NeurIPS (2023)
Anay Majee, Suraj Kothawade, Krishnateja Killamsetty, Rishabh K. Iyer
SCoRe: Submodular Combinatorial Representation Learning for Real-World Class-Imbalanced Settings. CoRR (2023)
Parth Vipul Sangani, Arjun Shashank Kashettiwar, Pritish Chakraborty, Bhuvan Reddy Gangula, Durga Sivasubramanian, Ganesh Ramakrishnan, Rishabh K. Iyer, Abir De
Discrete Continuous Optimization Framework for Simultaneous Clustering and Training in Mixture Models. ICML (2023)
H. S. V. N. S. Kowndinya Renduchintala, Krishnateja Killamsetty, Sumit Bhatia, Milan Aggarwal, Ganesh Ramakrishnan, Rishabh K. Iyer, Balaji Krishnamurthy
INGENIOUS: Using Informative Data Subsets for Efficient Pre-Training of Language Models. EMNLP (Findings) (2023)
KirshnaTeja Killamsetty, Alexandre V. Evfimievski, Tejaswini Pedapati, Kiran Kate, Lucian Popa, Rishabh K. Iyer
MILO: Model-Agnostic Subset Selection Framework for Efficient Model Training and Tuning. CoRR (2023)
Suraj Kothawade, Anmol Reddy Mekala, D. Chandra Sekhara Hetha Havya, Mayank Kothyari, Rishabh K. Iyer, Ganesh Ramakrishnan, Preethi Jyothi
DITTO: Data-efficient and Fair Targeted Subset Selection for ASR Accent Adaptation. ACL (1) (2023)
Nathan Beck, Suraj Kothawade, Pradeep Shenoy, Rishabh K. Iyer
STREAMLINE: Streaming Active Learning for Realistic Multi-Distributional Settings. CoRR (2023)
Changbin Li, Suraj Kothawade, Feng Chen, Rishabh K. Iyer
PLATINUM: Semi-Supervised Model Agnostic Meta-Learning using Submodular Mutual Information. CoRR (2022)
Guttu Sai Abhishek, Harshad Ingole, Parth Laturia, Vineeth Dorna, Ayush Maheshwari, Ganesh Ramakrishnan, Rishabh K. Iyer
SPEAR : Semi-supervised Data Programming in Python. EMNLP (Demos) (2022)
Suraj Kothawade, Atharv Savarkar, Venkat Iyer, Ganesh Ramakrishnan, Rishabh K. Iyer
CLINICAL: Targeted Active Learning for Imbalanced Medical Image Classification. MILLanD@MICCAI (2022)
KrishnaTeja Killamsetty, Changbin Li, Chen Zhao, Feng Chen, Rishabh K. Iyer
A Nested Bi-level Optimization Framework for Robust Few Shot Learning. AAAI (2022)
Suraj Kothawade, Shivang Chopra, Saikat Ghosh, Rishabh K. Iyer
Active Data Discovery: Mining Unknown Data using Submodular Information Measures. CoRR (2022)
Ashish R. Mittal, Durga Sivasubramanian, Rishabh K. Iyer, Preethi Jyothi, Ganesh Ramakrishnan
Partitioned Gradient Matching-based Data Subset Selection for Compute-Efficient Robust ASR Training. CoRR (2022)
Suraj Kothawade, Saikat Ghosh, Sumit Shekhar, Yu Xiang, Rishabh K. Iyer
Talisman: Targeted Active Learning for Object Detection with Rare Classes and Slices Using Submodular Mutual Information. ECCV (38) (2022)
Rishabh Tiwari, KrishnaTeja Killamsetty, Rishabh K. Iyer, Pradeep Shenoy
GCR: Gradient Coreset based Replay Buffer Selection for Continual Learning. CVPR (2022)
Rishabh K. Iyer, Ninad Khargonkar, Jeff A. Bilmes, Himanshu Asnani
Generalized Submodular Information Measures: Theoretical Properties, Examples, Optimization Algorithms, and Applications. IEEE Trans. Inf. Theory 68 (2) (2022)
Suraj Kothawade, Pavan Kumar Reddy, Ganesh Ramakrishnan, Rishabh K. Iyer
BASIL: Balanced Active Semi-supervised Learning for Class Imbalanced Datasets. CoRR (2022)
Athresh Karanam, KrishnaTeja Killamsetty, Harsha Kokel, Rishabh K. Iyer
ORIENT: Submodular Mutual Information Measures for Data Subset Selection under Distribution Shift. NeurIPS (2022)
Suraj Kothawade, Akshit Shrivastava, Venkat Iyer, Ganesh Ramakrishnan, Rishabh K. Iyer
DIAGNOSE: Avoiding Out-of-Distribution Data Using Submodular Information Measures. MILLanD@MICCAI (2022)
Ashish R. Mittal, Durga Sivasubramanian, Rishabh K. Iyer, Preethi Jyothi, Ganesh Ramakrishnan
Partitioned Gradient Matching-based Data Subset Selection for Compute-Efficient Robust ASR Training. EMNLP (Findings) (2022)
KrishnaTeja Killamsetty, Guttu Sai Abhishek, Aakriti, Alexandre V. Evfimievski, Lucian Popa, Ganesh Ramakrishnan, Rishabh K. Iyer
AUTOMATA: Gradient Based Data Subset Selection for Compute-Efficient Hyper-parameter Tuning. CoRR (2022)
Vishal Kaushal, Ganesh Ramakrishnan, Rishabh K. Iyer
Submodlib: A Submodular Optimization Library. CoRR (2022)
Ayush Maheshwari, KrishnaTeja Killamsetty, Ganesh Ramakrishnan, Rishabh K. Iyer, Marina Danilevsky, Lucian Popa
Learning to Robustly Aggregate Labeling Functions for Semi-supervised Data Programming. ACL (Findings) (2022)
Suraj Kothawade, Atharv Savarkar, Venkat Iyer, Lakshman Tamil, Ganesh Ramakrishnan, Rishabh K. Iyer
CLINICAL: Targeted Active Learning for Imbalanced Medical Image Classification. CoRR (2022)
KrishnaTeja Killamsetty, Guttu Sai Abhishek, Aakriti, Ganesh Ramakrishnan, Alexandre V. Evfimievski, Lucian Popa, Rishabh K. Iyer
AUTOMATA: Gradient Based Data Subset Selection for Compute-Efficient Hyper-parameter Tuning. NeurIPS (2022)
Suraj Kothawade, Vishal Kaushal, Ganesh Ramakrishnan, Jeff A. Bilmes, Rishabh K. Iyer
PRISM: A Rich Class of Parameterized Submodular Information Measures for Guided Data Subset Selection. AAAI (2022)
Xujiang Zhao, KrishnaTeja Killamsetty, Rishabh K. Iyer, Feng Chen
How Out-of-Distribution Data Hurts Semi-Supervised Learning. ICDM (2022)
Suraj Kothawade, Akshit Srivastava, Venkat Iyer, Ganesh Ramakrishnan, Rishabh K. Iyer
DIAGNOSE: Avoiding Out-of-distribution Data using Submodular Information Measures. CoRR (2022)
Changbin Li, Suraj Kothawade, Feng Chen, Rishabh K. Iyer
PLATINUM: Semi-Supervised Model Agnostic Meta-Learning using Submodular Mutual Information. ICML (2022)
Vishal Kaushal, Suraj Kothawade, Anshul Tomar, Rishabh K. Iyer, Ganesh Ramakrishnan
How Good is a Video Summary? A New Benchmarking Dataset and Evaluation Framework Towards Realistic Video Summarization. CoRR (2021)
Vishal Kaushal, Suraj Kothawade, Ganesh Ramakrishnan, Jeff A. Bilmes, Rishabh K. Iyer
PRISM: A Unified Framework of Parameterized Submodular Information Measures for Targeted Data Subset Selection and Summarization. CoRR (2021)
KrishnaTeja Killamsetty, Xujiang Zhao, Feng Chen, Rishabh K. Iyer
RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised Learning. CoRR (2021)
Durga Sivasubramanian, Rishabh K. Iyer, Ganesh Ramakrishnan, Abir De
Training Data Subset Selection for Regression with Controlled Generalization Error. CoRR (2021)
Mayank Kothyari, Anmol Reddy Mekala, Rishabh K. Iyer, Ganesh Ramakrishnan, Preethi Jyothi
Personalizing ASR with limited data using targeted subset selection. CoRR (2021)
Rishabh Tiwari, KrishnaTeja Killamsetty, Rishabh K. Iyer, Pradeep Shenoy
GCR: Gradient Coreset Based Replay Buffer Selection For Continual Learning. CoRR (2021)
Suraj Kothawade, Saikat Ghosh, Sumit Shekhar, Yu Xiang, Rishabh K. Iyer
TALISMAN: Targeted Active Learning for Object Detection with Rare Classes and Slices using Submodular Mutual Information. CoRR (2021)
KrishnaTeja Killamsetty, Durga Sivasubramanian, Baharan Mirzasoleiman, Ganesh Ramakrishnan, Abir De, Rishabh K. Iyer
GRAD-MATCH: A Gradient Matching Based Data Subset Selection for Efficient Learning. CoRR (2021)
Atul Sahay, Anshul Nasery, Ayush Maheshwari, Ganesh Ramakrishnan, Rishabh K. Iyer
Rule Augmented Unsupervised Constituency Parsing. ACL/IJCNLP (Findings) (2021)
Atul Sahay, Anshul Nasery, Ayush Maheshwari, Ganesh Ramakrishnan, Rishabh K. Iyer
Rule Augmented Unsupervised Constituency Parsing. CoRR (2021)
Ayush Maheshwari, Oishik Chatterjee, KrishnaTeja Killamsetty, Ganesh Ramakrishnan, Rishabh K. Iyer
Semi-Supervised Data Programming with Subset Selection. ACL/IJCNLP (Findings) (2021)
Guttu Sai Abhishek, Harshad Ingole, Parth Laturia, Vineeth Dorna, Ayush Maheshwari, Ganesh Ramakrishnan, Rishabh K. Iyer
SPEAR : Semi-supervised Data Programming in Python. CoRR (2021)
Himanshu Asnani, Jeff A. Bilmes, Rishabh K. Iyer
Independence Properties of Generalized Submodular Information Measures. CoRR (2021)
Chandrashekhar Lavania, Kai Wei, Rishabh K. Iyer, Jeff A. Bilmes
A Practical Online Framework for Extracting Running Video Summaries under a Fixed Memory Budget. SDM (2021)
Rishabh K. Iyer, Ninad Khargoankar, Jeff A. Bilmes, Himanshu Asanani
Submodular combinatorial information measures with applications in machine learning. ALT (2021)
Nathan Beck, Durga Sivasubramanian, Apurva Dani, Ganesh Ramakrishnan, Rishabh K. Iyer
Effective Evaluation of Deep Active Learning on Image Classification Tasks. CoRR (2021)
Ping Zhang, Rishabh K. Iyer, Ashish Tendulkar, Gaurav Aggarwal, Abir De
Learning to Select Exogenous Events for Marked Temporal Point Process. NeurIPS (2021)
Himanshu Asnani, Jeff A. Bilmes, Rishabh K. Iyer
Independence Properties of Generalized Submodular Information Measures. ISIT (2021)
Suraj Kothawade, Vishal Kaushal, Ganesh Ramakrishnan, Jeff A. Bilmes, Rishabh K. Iyer
Submodular Mutual Information for Targeted Data Subset Selection. CoRR (2021)
Durga Sivasubramanian, Rishabh K. Iyer, Ganesh Ramakrishnan, Abir De
Training Data Subset Selection for Regression with Controlled Generalization Error. ICML (2021)
Srijita Das, Rishabh K. Iyer, Sriraam Natarajan
A Clustering based Selection Framework for Cost Aware and Test-time Feature Elicitation. COMAD/CODS (2021)
KrishnaTeja Killamsetty, Durga Sivasubramanian, Ganesh Ramakrishnan, Abir De, Rishabh K. Iyer
GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training. ICML (2021)
KrishnaTeja Killamsetty, Durga Sivasubramanian, Ganesh Ramakrishnan, Rishabh K. Iyer
GLISTER: Generalization based Data Subset Selection for Efficient and Robust Learning. AAAI (2021)
KrishnaTeja Killamsetty, Xujiang Zhao, Feng Chen, Rishabh K. Iyer
RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised Learning. NeurIPS (2021)
Suraj Kothawade, Nathan Beck, KrishnaTeja Killamsetty, Rishabh K. Iyer
SIMILAR: Submodular Information Measures Based Active Learning In Realistic Scenarios. NeurIPS (2021)
Ayush Maheshwari, KrishnaTeja Killamsetty, Ganesh Ramakrishnan, Rishabh K. Iyer, Marina Danilevsky, Lucian Popa
Learning to Robustly Aggregate Labeling Functions for Semi-supervised Data Programming. CoRR (2021)
Suraj Kothawade, Nathan Beck, KrishnaTeja Killamsetty, Rishabh K. Iyer
SIMILAR: Submodular Information Measures Based Active Learning In Realistic Scenarios. CoRR (2021)
Rishabh K. Iyer
Robust Submodular Minimization with Applications to Cooperative Modeling. ECAI (2020)
KrishnaTeja Killamsetty, Durga Sivasubramanian, Ganesh Ramakrishnan, Rishabh K. Iyer
GLISTER: Generalization based Data Subset Selection for Efficient and Robust Learning. CoRR (2020)
Rishabh K. Iyer
Robust Submodular Minimization with Applications to Cooperative Modeling. CoRR (2020)
Srijita Das, Rishabh K. Iyer, Sriraam Natarajan
Cost Aware Feature Elicitation. KiML@KDD (2020)
Rishabh K. Iyer, Jeff A. Bilmes
Concave Aspects of Submodular Functions. CoRR (2020)
Vishal Kaushal, Suraj Kothawade, Rishabh K. Iyer, Ganesh Ramakrishnan
Realistic Video Summarization through VISIOCITY: A New Benchmark and Evaluation Framework. CoRR (2020)
KrishnaTeja Killamsetty, Changbin Li, Chen Zhao, Rishabh K. Iyer, Feng Chen
A Reweighted Meta Learning Framework for Robust Few Shot Learning. CoRR (2020)
Saiteja Nalla, Mohit Agrawal, Vishal Kaushal, Ganesh Ramakrishnan, Rishabh K. Iyer
Watch Hours in Minutes: Summarizing Videos with User Intent. ECCV Workshops (5) (2020)
Rishabh K. Iyer, Jeff A. Bilmes
Concave Aspects of Submodular Functions. ISIT (2020)
Vishal Kaushal, Suraj Kothawade, Ganesh Ramakrishnan, Jeff A. Bilmes, Himanshu Asnani, Rishabh K. Iyer
A Unified Framework for Generic, Query-Focused, Privacy Preserving and Update Summarization using Submodular Information Measures. CoRR (2020)
Vishal Kaushal, Suraj Kothawade, Rishabh K. Iyer, Ganesh Ramakrishnan
Realistic Video Summarization through VISIOCITY: A New Benchmark and Evaluation Framework. AI4TV@MM (2020)
Rishabh K. Iyer, Ninad Khargoankar, Jeff A. Bilmes, Himanshu Asanani
Submodular Combinatorial Information Measures with Applications in Machine Learning. CoRR (2020)
Suraj Kothawade, Jiten Girdhar, Chandrashekhar Lavania, Rishabh K. Iyer
Deep Submodular Networks for Extractive Data Summarization. CoRR (2020)
Ayush Maheshwari, Oishik Chatterjee, KrishnaTeja Killamsetty, Rishabh K. Iyer, Ganesh Ramakrishnan
Data Programming using Semi-Supervision and Subset Selection. CoRR (2020)
Xujiang Zhao, KrishnaTeja Killamsetty, Rishabh K. Iyer, Feng Chen
Robust Semi-Supervised Learning with Out of Distribution Data. CoRR (2020)
Rishabh K. Iyer, Jeffrey A. Bilmes
A Memoization Framework for Scaling Submodular Optimization to Large Scale Problems. AISTATS (2019)
Rishabh K. Iyer, Jeff A. Bilmes
Near Optimal Algorithms for Hard Submodular Programs with Discounted Cooperative Costs. CoRR (2019)
Vishal Kaushal, Rishabh K. Iyer, Suraj Kothawade, Rohan Mahadev, Khoshrav Doctor, Ganesh Ramakrishnan
Learning From Less Data: A Unified Data Subset Selection and Active Learning Framework for Computer Vision. CoRR (2019)
Vishal Kaushal, Rishabh K. Iyer, Khoshrav Doctor, Anurag Sahoo, Pratik Dubal, Suraj Kothawade, Rohan Mahadev, Kunal Dargan, Ganesh Ramakrishnan
Demystifying Multi-Faceted Video Summarization: Tradeoff Between Diversity, Representation, Coverage and Importance. CoRR (2019)
Rishabh K. Iyer, Jeffrey A. Bilmes
Near Optimal Algorithms for Hard Submodular Programs with Discounted Cooperative Costs. AISTATS (2019)
Rishabh K. Iyer
A Unified Framework of Robust Submodular Optimization. CoRR (2019)
Vishal Kaushal, Rishabh K. Iyer, Khoshrav Doctor, Anurag Sahoo, Pratik Dubal, Suraj Kothawade, Rohan Mahadev, Kunal Dargan, Ganesh Ramakrishnan
Demystifying Multi-Faceted Video Summarization: Tradeoff Between Diversity, Representation, Coverage and Importance. WACV (2019)
Vishal Kaushal, Sandeep Subramanian, Suraj Kothawade, Rishabh K. Iyer, Ganesh Ramakrishnan
A Framework Towards Domain Specific Video Summarization. WACV (2019)
Rishabh K. Iyer, Jeff A. Bilmes
A Memoization Framework for Scaling Submodular Optimization to Large Scale Problems. CoRR (2019)
Vishal Kaushal, Rishabh K. Iyer, Suraj Kothawade, Rohan Mahadev, Khoshrav Doctor, Ganesh Ramakrishnan
Learning From Less Data: A Unified Data Subset Selection and Active Learning Framework for Computer Vision. WACV (2019)
Rishabh K. Iyer, Nimit Acharya, Tanuja Bompada, Denis Charles, Eren Manavoglu
A Unified Batch Online Learning Framework for Click Prediction. CoRR (2018)
Vishal Kaushal, Rishabh K. Iyer, Suraj Kothawade, Sandeep Subramanian, Ganesh Ramakrishnan
A Framework towards Domain Specific Video Summarization. CoRR (2018)
Rishabh K. Iyer, Pratik Dubal, Kunal Dargan, Suraj Kothawade, Rohan Mahadev, Vishal Kaushal
Vis-DSS: An Open-Source toolkit for Visual Data Selection and Summarization. CoRR (2018)
John Moore, Joel Pfeiffer, Kai Wei, Rishabh K. Iyer, Denis Charles, Ran Gilad-Bachrach, Levi Boyles, Eren Manavoglu
Modeling and Simultaneously Removing Bias via Adversarial Neural Networks. CoRR (2018)
Pratik Dubal, Rohan Mahadev, Suraj Kothawade, Kunal Dargan, Rishabh K. Iyer
Deployment of Customized Deep Learning based Video Analytics On Surveillance Cameras. CoRR (2018)
Rishabh K. Iyer, John T. Halloran, Kai Wei
Jensen: An Easily-Extensible C++ Toolkit for Production-Level Machine Learning and Convex Optimization. CoRR (2018)
Vishal Kaushal, Anurag Sahoo, Khoshrav Doctor, Narasimha Raju Uppalapati, Suyash Shetty, Pankaj Singh, Rishabh K. Iyer, Ganesh Ramakrishnan
Learning From Less Data: Diversified Subset Selection and Active Learning in Image Classification Tasks. CoRR (2018)
Yuzong Liu, Rishabh K. Iyer, Katrin Kirchhoff, Jeff A. Bilmes
SVitchboard-II and FiSVer-I: Crafting high quality and low complexity conversational english speech corpora using submodular function optimization. Comput. Speech Lang. 42 (2017)
Anurag Sahoo, Vishal Kaushal, Khoshrav Doctor, Suyash Shetty, Rishabh K. Iyer, Ganesh Ramakrishnan
A Unified Multi-Faceted Video Summarization System. CoRR (2017)
Wenruo Bai, Rishabh K. Iyer, Kai Wei, Jeff A. Bilmes
Algorithms for Optimizing the Ratio of Submodular Functions. ICML (2016)
Ramakrishna Bairi, Rishabh K. Iyer, Ganesh Ramakrishnan, Jeff A. Bilmes
Summarization of Multi-Document Topic Hierarchies using Submodular Mixtures. ACL (1) (2015)

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Publication Activity (10 Years)

Top Topics

Top Venues

Rishabh K. Iyer