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cs.LG2021
Mitigating Sampling Bias and Improving Robustness in Active Learning
Ranganath Krishnan, Alok Sinha, Nilesh Ahuja +3
This paper presents simple and efficient methods to mitigate sampling bias in active learning while achieving state-of-the-art accuracy and model robustness. We introduce supervise…
cs.LG2021
RHNAS: Realizable Hardware and Neural Architecture Search
Yash Akhauri, Adithya Niranjan, J. Pablo Muñoz +6
The rapidly evolving field of Artificial Intelligence necessitates automated approaches to co-design neural network architecture and neural accelerators to maximize system efficien…