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Pranjal Awasthi
On Robustness to Adversarial Examples and Polynomial Optimization
Pranjal Awasthi, Abhratanu Dutta, Aravindan Vijayaraghavan
We study the design of computationally e cient algorithms with provable guarantees, that are robust to adversarial (test time) perturbations. While there has been an explosion of recent work on this topic due to its connections to test time robustness of deep networks, there is limited theoretical understanding of several basic questions like (i) when and how can one design provably robust learning algorithms?
On Robustness to Adversarial Examples and Polynomial Optimization
Pranjal Awasthi, Abhratanu Dutta, Aravindan Vijayaraghavan
We study the design of computationally e cient algorithms with provable guarantees, that are robust to adversarial (test time) perturbations. While there has been an explosion of recent work on this topic due to its connections to test time robustness of deep networks, there is limited theoretical understanding of several basic questions like (i) when and how can one design provably robust learning algorithms?