23 citations · 26 across the 2 of their papers we have counts for
5 papers
Characterizing Datapoints via Second-Split Forgetting
Pratyush Maini, Saurabh Garg, Zachary C. Lipton +1
Researchers investigating example hardness have increasingly focused on the dynamics by which neural networks learn and forget examples throughout training. Popular metrics derived…
Dataset Inference: Ownership Resolution in Machine Learning
Pratyush Maini, Mohammad Yaghini, Nicolas Papernot
With increasingly more data and computation involved in their training, machine learning models constitute valuable intellectual property. This has spurred interest in model steali…
Data-Free Model Extraction
Jean-Baptiste Truong, Pratyush Maini, Robert J. Walls +1
Current model extraction attacks assume that the adversary has access to a surrogate dataset with characteristics similar to the proprietary data used to train the victim model. Th…
Why and when should you pool? Analyzing Pooling in Recurrent Architectures
Pratyush Maini, Keshav Kolluru, Danish Pruthi +1
Pooling-based recurrent neural architectures consistently outperform their counterparts without pooling. However, the reasons for their enhanced performance are largely unexamined.…
Adversarial Robustness Against the Union of Multiple Perturbation Models
Pratyush Maini, Eric Wong, J. Zico Kolter
Owing to the susceptibility of deep learning systems to adversarial attacks, there has been a great deal of work in developing (both empirically and certifiably) robust classifiers…