In this work, we study the worst-case to average-case hardness of the Learning with Errors problem (LWE) under an alternative measure of hardness - the maximum success probability achievable by a probabilistic polynomial-time (PPT) algorithm. Previous works by Regev (STOC 2005), Peikert (STOC 2009), and Brakerski, Peikert, Langlois, Regev, Stehle ... more >>>

In a pair of recent breakthroughs \cite{CHR,Li} it was shown that the classes $S_2^E, ZPE^{NP}$, and $\Sigma_2^E$ require exponential circuit complexity, giving the first unconditional improvements to a classical result of Kannan. These results were obtained by designing a surprising new algorithm for the total search problem Range Avoidance: given ... more >>>

The Parameterized Inapproximability Hypothesis (PIH), which is an analog of the PCP theorem in parameterized complexity, asserts that, there is a constant $\varepsilon> 0$ such that for any computable function $f:\mathbb{N}\to\mathbb{N}$, no $f(k)\cdot n^{O(1)}$-time algorithm can, on input a $k$-variable CSP instance with domain size $n$, find an assignment satisfying ... more >>>