A recommendation system suggests products to users based on data about user preferences. It is typically modeled by a problem of completing an $m\times n$ matrix of small rank $k$. We give the first classical algorithm to produce a recommendation in $O(\text{poly}(k)\text{polylog}(m,n))$ time, which is an exponential improvement on previous ... more >>>

We develop general lower bound arguments for approximating tropical
(min,+) and (max,+) circuits, and use them to prove the
first non-trivial, even super-polynomial, lower bounds on the size
of such circuits approximating some explicit optimization
problems. In particular, these bounds show that the approximation
powers of pure dynamic programming algorithms ... more >>>

Several works have shown unconditional hardness (via integrality gaps) of computing equilibria using strong hierarchies of convex relaxations. Such results however only apply to the problem of computing equilibria that optimize a certain objective function and not to the (arguably more fundamental) task of finding \emph{any} equilibrium.

We present ... more >>>