KrishnaTeja Killamsetty

According to our database, KrishnaTeja Killamsetty authored at least 21 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

SCoRe: Submodular Combinatorial Representation Learning.

Anay Majee, Suraj Kothawade, Krishnateja Killamsetty, Rishabh K. Iyer

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

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

Anay Majee, Suraj Kothawade, Krishnateja Killamsetty, 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

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

KrishnaTeja Killamsetty, Alexandre V. Evfimievski, Tejaswini Pedapati, Kiran Kate, Lucian Popa, Rishabh K. Iyer

CoRR, 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

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.

KrishnaTeja Killamsetty, Guttu Sai Abhishek, Aakriti, Ganesh Ramakrishnan, Alexandre V. Evfimievski, Lucian Popa, Rishabh K. Iyer

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.

Athresh Karanam, KrishnaTeja Killamsetty, Harsha Kokel, Rishabh K. Iyer

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.

Xujiang Zhao, KrishnaTeja Killamsetty, Rishabh K. Iyer, Feng Chen

Proceedings of the IEEE International Conference on Data Mining, 2022

GCR: Gradient Coreset based Replay Buffer Selection for Continual Learning.

Rishabh Tiwari, KrishnaTeja Killamsetty, Rishabh K. Iyer, Pradeep Shenoy

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 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

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

A Nested Bi-level Optimization Framework for Robust Few Shot Learning.

KrishnaTeja Killamsetty, Changbin Li, Chen Zhao, Feng Chen, Rishabh K. Iyer

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

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

SIMILAR: Submodular Information Measures Based Active Learning In Realistic Scenarios.

Suraj Kothawade, Nathan Beck, KrishnaTeja Killamsetty, Rishabh K. Iyer

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.

KrishnaTeja Killamsetty, Xujiang Zhao, Feng Chen, Rishabh K. Iyer

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.

KrishnaTeja Killamsetty, Durga Sivasubramanian, Ganesh Ramakrishnan, Abir De, Rishabh K. Iyer

Proceedings of the 38th International Conference on Machine Learning, 2021

Semi-Supervised Data Programming with Subset Selection.

Ayush Maheshwari, Oishik Chatterjee, KrishnaTeja Killamsetty, Ganesh Ramakrishnan, Rishabh K. Iyer

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.

KrishnaTeja Killamsetty, Durga Sivasubramanian, Ganesh Ramakrishnan, Rishabh K. Iyer

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

A Reweighted Meta Learning Framework for Robust Few Shot Learning.

KrishnaTeja Killamsetty, Changbin Li, Chen Zhao, Rishabh K. Iyer, Feng Chen

CoRR, 2020

Robust Semi-Supervised Learning with Out of Distribution Data.

Xujiang Zhao, KrishnaTeja Killamsetty, Rishabh K. Iyer, Feng Chen

CoRR, 2020

Data Programming using Semi-Supervision and Subset Selection.

Ayush Maheshwari, Oishik Chatterjee, KrishnaTeja Killamsetty, Rishabh K. Iyer, Ganesh Ramakrishnan

CoRR, 2020