Rishabh K. Iyer

Orcid: 0000-0001-9851-463X

Affiliations:
  • University of Texas at Dallas, TX, USA


According to our database1, Rishabh K. Iyer authored at least 96 papers between 2011 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
STONE: A Submodular Optimization Framework for Active 3D Object Detection.
CoRR, 2024

SMILe: Leveraging Submodular Mutual Information For Robust Few-Shot Object Detection.
CoRR, 2024

STENCIL: Submodular Mutual Information Based Weak Supervision for Cold-Start Active Learning.
CoRR, 2024

Theoretical Analysis of Submodular Information Measures for Targeted Data Subset Selection.
CoRR, 2024

Gradient Coreset for Federated Learning.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Beyond Active Learning: Leveraging the Full Potential of Human Interaction via Auto-Labeling, Human Correction, and Human Verification.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

SCoRe: Submodular Combinatorial Representation Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
SCoRe: Submodular Combinatorial Representation Learning for Real-World Class-Imbalanced Settings.
CoRR, 2023

STREAMLINE: Streaming Active Learning for Realistic Multi-Distributional Settings.
CoRR, 2023

INGENIOUS: Using Informative Data Subsets for Efficient Pre-Training of Large Language Models.
CoRR, 2023

MILO: Model-Agnostic Subset Selection Framework for Efficient Model Training and Tuning.
CoRR, 2023

Efficient Data Subset Selection to Generalize Training Across Models: Transductive and Inductive Networks.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Discrete Continuous Optimization Framework for Simultaneous Clustering and Training in Mixture Models.
Proceedings of the International Conference on Machine Learning, 2023

INGENIOUS: Using Informative Data Subsets for Efficient Pre-Training of Language Models.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

DITTO: Data-efficient and Fair Targeted Subset Selection for ASR Accent Adaptation.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022
Generalized Submodular Information Measures: Theoretical Properties, Examples, Optimization Algorithms, and Applications.
IEEE Trans. Inf. Theory, 2022

CLINICAL: Targeted Active Learning for Imbalanced Medical Image Classification.
CoRR, 2022

Active Data Discovery: Mining Unknown Data using Submodular Information Measures.
CoRR, 2022

BASIL: Balanced Active Semi-supervised Learning for Class Imbalanced Datasets.
CoRR, 2022

Submodlib: A Submodular Optimization Library.
CoRR, 2022

AUTOMATA: Gradient Based Data Subset Selection for Compute-Efficient Hyper-parameter Tuning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

ORIENT: Submodular Mutual Information Measures for Data Subset Selection under Distribution Shift.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

DIAGNOSE: Avoiding Out-of-Distribution Data Using Submodular Information Measures.
Proceedings of the Medical Image Learning with Limited and Noisy Data, 2022

CLINICAL: Targeted Active Learning for Imbalanced Medical Image Classification.
Proceedings of the Medical Image Learning with Limited and Noisy Data, 2022

PLATINUM: Semi-Supervised Model Agnostic Meta-Learning using Submodular Mutual Information.
Proceedings of the International Conference on Machine Learning, 2022

How Out-of-Distribution Data Hurts Semi-Supervised Learning.
Proceedings of the IEEE International Conference on Data Mining, 2022

Partitioned Gradient Matching-based Data Subset Selection for Compute-Efficient Robust ASR Training.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

SPEAR : Semi-supervised Data Programming in Python.
Proceedings of the The 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Talisman: Targeted Active Learning for Object Detection with Rare Classes and Slices Using Submodular Mutual Information.
Proceedings of the Computer Vision - ECCV 2022, 2022

GCR: Gradient Coreset based Replay Buffer Selection for Continual Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Learning to Robustly Aggregate Labeling Functions for Semi-supervised Data Programming.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

PRISM: A Rich Class of Parameterized Submodular Information Measures for Guided Data Subset Selection.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

A Nested Bi-level Optimization Framework for Robust Few Shot Learning.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Personalizing ASR with limited data using targeted subset selection.
CoRR, 2021

Effective Evaluation of Deep Active Learning on Image Classification Tasks.
CoRR, 2021

Submodular Mutual Information for Targeted Data Subset Selection.
CoRR, 2021

PRISM: A Unified Framework of Parameterized Submodular Information Measures for Targeted Data Subset Selection and Summarization.
CoRR, 2021

GRAD-MATCH: A Gradient Matching Based Data Subset Selection for Efficient Learning.
CoRR, 2021

How Good is a Video Summary? A New Benchmarking Dataset and Evaluation Framework Towards Realistic Video Summarization.
CoRR, 2021

A Practical Online Framework for Extracting Running Video Summaries under a Fixed Memory Budget.
Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Learning to Select Exogenous Events for Marked Temporal Point Process.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

SIMILAR: Submodular Information Measures Based Active Learning In Realistic Scenarios.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Independence Properties of Generalized Submodular Information Measures.
Proceedings of the IEEE International Symposium on Information Theory, 2021

Training Data Subset Selection for Regression with Controlled Generalization Error.
Proceedings of the 38th International Conference on Machine Learning, 2021

GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training.
Proceedings of the 38th International Conference on Machine Learning, 2021

A Clustering based Selection Framework for Cost Aware and Test-time Feature Elicitation.
Proceedings of the CODS-COMAD 2021: 8th ACM IKDD CODS and 26th COMAD, 2021

Submodular combinatorial information measures with applications in machine learning.
Proceedings of the Algorithmic Learning Theory, 2021

Rule Augmented Unsupervised Constituency Parsing.
Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

Semi-Supervised Data Programming with Subset Selection.
Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

GLISTER: Generalization based Data Subset Selection for Efficient and Robust Learning.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
A Reweighted Meta Learning Framework for Robust Few Shot Learning.
CoRR, 2020

Deep Submodular Networks for Extractive Data Summarization.
CoRR, 2020

A Unified Framework for Generic, Query-Focused, Privacy Preserving and Update Summarization using Submodular Information Measures.
CoRR, 2020

Robust Semi-Supervised Learning with Out of Distribution Data.
CoRR, 2020

Data Programming using Semi-Supervision and Subset Selection.
CoRR, 2020

Realistic Video Summarization through VISIOCITY: A New Benchmark and Evaluation Framework.
Proceedings of the AI4TV '20: Proceedings of the 2nd International Workshop on AI for Smart TV Content Production, 2020

Cost Aware Feature Elicitation.
Proceedings of the ACM SIGKDD Workshop on Knowledge-infused Mining and Learning for Social Impact co-located with 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (Virtual) (SIGKDD 2020), 2020

Concave Aspects of Submodular Functions.
Proceedings of the IEEE International Symposium on Information Theory, 2020

Watch Hours in Minutes: Summarizing Videos with User Intent.
Proceedings of the Computer Vision - ECCV 2020 Workshops, 2020

Robust Submodular Minimization with Applications to Cooperative Modeling.
Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

2019
A Unified Framework of Robust Submodular Optimization.
CoRR, 2019

A Framework Towards Domain Specific Video Summarization.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2019

Learning From Less Data: A Unified Data Subset Selection and Active Learning Framework for Computer Vision.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2019

Demystifying Multi-Faceted Video Summarization: Tradeoff Between Diversity, Representation, Coverage and Importance.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2019

A Memoization Framework for Scaling Submodular Optimization to Large Scale Problems.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Near Optimal Algorithms for Hard Submodular Programs with Discounted Cooperative Costs.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Vis-DSS: An Open-Source toolkit for Visual Data Selection and Summarization.
CoRR, 2018

A Unified Batch Online Learning Framework for Click Prediction.
CoRR, 2018

Jensen: An Easily-Extensible C++ Toolkit for Production-Level Machine Learning and Convex Optimization.
CoRR, 2018

Learning From Less Data: Diversified Subset Selection and Active Learning in Image Classification Tasks.
CoRR, 2018

Deployment of Customized Deep Learning based Video Analytics On Surveillance Cameras.
CoRR, 2018

Modeling and Simultaneously Removing Bias via Adversarial Neural Networks.
CoRR, 2018

2017
SVitchboard-II and FiSVer-I: Crafting high quality and low complexity conversational english speech corpora using submodular function optimization.
Comput. Speech Lang., 2017

A Unified Multi-Faceted Video Summarization System.
CoRR, 2017

2016
Algorithms for Optimizing the Ratio of Submodular Functions.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
Mixed Robust/Average Submodular Partitioning: Fast Algorithms, Guarantees, and Applications to Parallel Machine Learning and Multi-Label Image Segmentation.
CoRR, 2015

Polyhedral aspects of Submodularity, Convexity and Concavity.
CoRR, 2015

Mixed Robust/Average Submodular Partitioning: Fast Algorithms, Guarantees, and Applications.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Submodular Hamming Metrics.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

SVitchboard II and fiSVer i: high-quality limited-complexity corpora of conversational English speech.
Proceedings of the 16th Annual Conference of the International Speech Communication Association, 2015

Submodularity in Data Subset Selection and Active Learning.
Proceedings of the 32nd International Conference on Machine Learning, 2015

On Approximate Non-submodular Minimization via Tree-Structured Supermodularity.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

Submodular Point Processes with Applications to Machine learning.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

Summarization of Multi-Document Topic Hierarchies using Submodular Mixtures.
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, 2015

2014
Monotone Closure of Relaxed Constraints in Submodular Optimization: Connections Between Minimization and Maximization.
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Learning Mixtures of Submodular Functions for Image Collection Summarization.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Fast Multi-stage Submodular Maximization.
Proceedings of the 31th International Conference on Machine Learning, 2014

2013
The Lovasz-Bregman Divergence and connections to rank aggregation, clustering, and web ranking.
Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

Curvature and Optimal Algorithms for Learning and Minimizing Submodular Functions.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Submodular Optimization with Submodular Cover and Submodular Knapsack Constraints.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Fast Semidifferential-based Submodular Function Optimization.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
Algorithms for Approximate Minimization of the Difference Between Submodular Functions, with Applications.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

Submodular-Bregman and the Lovász-Bregman Divergences with Applications.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2011
Estimation of the Embedding Capacity in Pixel-pair based Watermarking Schemes
CoRR, 2011

Object Mining for Large Video data.
Proceedings of the British Machine Vision Conference, 2011


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