KrishnaTeja Killamsetty

According to our database1, KrishnaTeja Killamsetty authored at least 20 papers between 2020 and 2024.

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

Timeline

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PhD thesis 
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Links

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Bibliography

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

2023
SCoRe: Submodular Combinatorial Representation Learning for Real-World Class-Imbalanced 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

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

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

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

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

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

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

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

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


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