Strachey Lecture: Privacy, Verification, Robustness: A Cryptographer's perspective on ML
Privacy, Verification, Robustness: A Cryptographer's perspective on ML
Cryptographic tools enable the safe use of technology platforms controlled by worst case computationally bounded adversaries.In this talk I will show how cryptographic paradigms and tools can be used to address trust issues in various phases of the machine learning pipeline. We will touch on approaches for achieving privacy, correctness, and robustness in presence of adversaries.
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This series covers the Strachey Lectures, a series of termly computer science lectures named after Christopher Strachey, the first Professor of Computation at the University of Oxford.
Hosted by the Department of Computer Science, University of Oxford, the Strachey Lectures began in 1995 and have included many distinguished speakers over the years. The Strachey Lectures are generously supported by OxFORD Asset Management.