1 citations · 1 across the 6 of their papers we have counts for
6 papers
Selective Prior Synchronization via SYNC Loss
Ishan Mishra, Jiajie Li, Deepak Mishra +1
Prediction under uncertainty is a critical requirement for the deep neural network to succeed responsibly. This paper focuses on selective prediction, which allows DNNs to make inf…
Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs
Kyle O'Brien, Stephen Casper, Quentin Anthony +7
Open-weight AI systems offer unique benefits, including enhanced transparency, open research, and decentralized access. However, they are vulnerable to tampering attacks which can…
Recognize Any Surgical Object: Unleashing the Power of Weakly-Supervised Data
Jiajie Li, Brian R Quaranto, Chenhui Xu +5
We present RASO, a foundation model designed to Recognize Any Surgical Object, offering robust open-set recognition capabilities across a broad range of surgical procedures and obj…
Client Contribution Normalization for Enhanced Federated Learning
Mayank Kumar Kundalwal, Anurag Saraswat, Ishan Mishra +1
Mobile devices, including smartphones and laptops, generate decentralized and heterogeneous data, presenting significant challenges for traditional centralized machine learning mod…
Distilling Calibrated Student from an Uncalibrated Teacher
Ishan Mishra, Sethu Vamsi Krishna, Deepak Mishra
Knowledge distillation is a common technique for improving the performance of a shallow student network by transferring information from a teacher network, which in general, is com…
Probabilistic Trust Intervals for Out of Distribution Detection
Gagandeep Singh, Ishan Mishra, Deepak Mishra
The ability of a deep learning network to distinguish between in-distribution (ID) and out-of-distribution (OOD) inputs is crucial for ensuring the reliability and trustworthiness…