Relative Value Iteration for Stochastic Differential Games

We study zero-sum stochastic differential games with player dynamics governed by a nondegenerate controlled diffusion process. Under the assumption of uniform stability, we establish the existence of a solution to the Isaac's equation for the ergodic game and characterize the optimal stationary strategies. The data is not assumed to be bounded, nor do we assume geometric ergodicity. Thus our results extend previous work in the literature. We also study a relative value iteration scheme that takes the form of a parabolic Isaac's equation. Under the hypothesis of geometric ergodicity we show that the relative value iteration converges to the elliptic Isaac's equation as time goes to infinity. We use these results to establish convergence of the relative value iteration for risk-sensitive control problems under an asymptotic flatness assumption

McBits Revisited

This paper presents a constant-time fast implementation for a high-security code-based encryption system. The implementation is based on the “McBits” paper by Bernstein, Chou, and Schwabe in 2013: we use the same FFT algorithms for root finding and syndrome computation, similar algorithms for secret permutation, and bitslicing for low-level operations. As opposed to McBits, where a high decryption throughput is achieved by running many decryption operations in parallel, we take a different approach to exploit the internal parallelism in one decryption operation for the use of more applications. As the result, we manage to achieve a slightly better decryption throughput at a much higher security level than McBits. As a minor contribution, we also present a constant-time implementation for encryption and key-pair generation, with similar techniques used for decryption