28 citations · 42 across the 3 of their papers we have counts for
3 papers
cs.LG2020★ 1 cited
Learning Unstable Dynamical Systems with Time-Weighted Logarithmic Loss
Kamil Nar, Yuan Xue, Andrew M. Dai
When training the parameters of a linear dynamical model, the gradient descent algorithm is likely to fail to converge if the squared-error loss is used as the training loss functi…
cs.LG2019★ 13 cited
Persistency of Excitation for Robustness of Neural Networks
Kamil Nar, S. Shankar Sastry
When an online learning algorithm is used to estimate the unknown parameters of a model, the signals interacting with the parameter estimates should not decay too quickly for the o…
cs.LG2019★ 28 cited
Cross-Entropy Loss and Low-Rank Features Have Responsibility for Adversarial Examples
Kamil Nar, Orhan Ocal, S. Shankar Sastry +1
State-of-the-art neural networks are vulnerable to adversarial examples; they can easily misclassify inputs that are imperceptibly different than their training and test data. In t…