Deepak Ravikumar

According to our database, Deepak Ravikumar authored at least 23 papers between 2020 and 2026.

Collaborative distances:

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

2026

Loss Knows Best: Detecting Annotation Errors in Videos via Loss Trajectories.

Praditha Alwis, Soumyadeep Chandra, Deepak Ravikumar, Kaushik Roy

CoRR, February, 2026

From Clutter to Clarity: Visual Recognition through Foveated Object-Centric Learning (FocL).

Amitangshu Mukherjee, Deepak Ravikumar, Kaushik Roy

Trans. Mach. Learn. Res., 2026

2025

GradientSpace: Unsupervised Data Clustering for Improved Instruction Tuning.

Shrihari Sridharan, Deepak Ravikumar, Anand Raghunathan, Kaushik Roy

CoRR, December, 2025

The Easy Path to Robustness: Coreset Selection using Sample Hardness.

Pranav Ramesh, Arjun Roy, Deepak Ravikumar, Kaushik Roy, Gopalakrishnan Srinivasan

CoRR, October, 2025

TRIM: Token-wise Attention-Derived Saliency for Data-Efficient Instruction Tuning.

Manish Nagaraj, Sakshi Choudhary, Utkarsh Saxena, Deepak Ravikumar, Kaushik Roy

CoRR, October, 2025

Finding the Muses: Identifying Coresets through Loss Trajectories.

Manish Nagaraj, Deepak Ravikumar, Efstathia Soufleri, Kaushik Roy

CoRR, March, 2025

Coresets from Trajectories: Selecting Data via Correlation of Loss Differences.

Manish Nagaraj, Deepak Ravikumar, Kaushik Roy

Trans. Mach. Learn. Res., 2025

Building Resilient AI: Strengthening Data, Security, and Robustness in Neural Networks.

Deepak Ravikumar, Jimmy Gammell, Kaushik Roy

Proceedings of the 31st IEEE International Symposium on On-Line Testing and Robust System Design, 2025

Towards Memorization Estimation: Fast, Formal and Free.

Deepak Ravikumar, Efstathia Soufleri, Abolfazl Hashemi, Kaushik Roy

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Improved Out-of-Distribution Detection with Additive Angular Margin Loss.

Deepak Ravikumar, Efstathia Soufleri, Kaushik Roy

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2025

SAP: Corrective Machine Unlearning with Scaled Activation Projection for Label Noise Robustness.

Sangamesh Kodge, Deepak Ravikumar, Gobinda Saha, Kaushik Roy

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Intelligent Pooling: Proactive Resource Provisioning in Large-scale Cloud Service.

Deepak Ravikumar, Alex Yeo, Yiwen Zhu, Aditya Lakra, Harsha Nagulapalli, Santhosh Ravindran, Steve Suh, Niharika Dutta, Andrew Fogarty, Yoonjae Park, Sumeet Khushalani, Arijit Tarafdar, Kunal Parekh, Subru Krishnan

Proc. VLDB Endow., March, 2024

DP-ImgSyn: Dataset Alignment for Obfuscated, Differentially Private Image Synthesis.

Efstathia Soufleri, Deepak Ravikumar, Kaushik Roy

Trans. Mach. Learn. Res., 2024

Homogenizing Non-IID Datasets via In-Distribution Knowledge Distillation for Decentralized Learning.

Deepak Ravikumar, Gobinda Saha, Sai Aparna Aketi, Kaushik Roy

Trans. Mach. Learn. Res., 2024

Advancing Compressed Video Action Recognition through Progressive Knowledge Distillation.

Efstathia Soufleri, Deepak Ravikumar, Kaushik Roy

CoRR, 2024

Verifix: Post-Training Correction to Improve Label Noise Robustness with Verified Samples.

Sangamesh Kodge, Deepak Ravikumar, Gobinda Saha, Kaushik Roy

CoRR, 2024

Curvature Clues: Decoding Deep Learning Privacy with Input Loss Curvature.

Deepak Ravikumar, Efstathia Soufleri, Kaushik Roy

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Unveiling Privacy, Memorization, and Input Curvature Links.

Deepak Ravikumar, Efstathia Soufleri, Abolfazl Hashemi, Kaushik Roy

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

Memorization Through the Lens of Curvature of Loss Function Around Samples.

Isha Garg, Deepak Ravikumar, Kaushik Roy

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

2023

TREND: Transferability-Based Robust ENsemble Design.

Deepak Ravikumar, Sangamesh Kodge, Isha Garg, Kaushik Roy

IEEE Trans. Artif. Intell., June, 2023

Intra-Class Mixup for Out-of-Distribution Detection.

Deepak Ravikumar, Sangamesh Kodge, Isha Garg, Kaushik Roy

IEEE Access, 2023

2022

Norm-Scaling for Out-of-Distribution Detection.

Deepak Ravikumar, Kaushik Roy

CoRR, 2022

2020

Exploring Vicinal Risk Minimization for Lightweight Out-of-Distribution Detection.

Deepak Ravikumar, Sangamesh Kodge, Isha Garg, Kaushik Roy

CoRR, 2020