4 papers · 1 filter
A Simple Algorithm for Best Separable State
Prashanti Anderson, Samuel B. Hopkins, Amit Rajaraman
We study the best separable state problem (BSS), which asks for the maximum acceptance probability of a quantum measurement over unentangled states. In classical terms, the goal is…
Markov Chains Approximate Message Passing
Amit Rajaraman, David X. Wu
Markov chain Monte Carlo algorithms have long been observed to obtain near-optimal performance in various Bayesian inference settings. However, developing a supporting theory that…
Faster MAX-CUT on Bounded Threshold Rank Graphs
Prashanti Anderson, Samuel B. Hopkins, Amit Rajaraman +1
We design new algorithms for approximating 2CSPs on graphs with bounded threshold rank, that is, whose normalized adjacency matrix has few eigenvalues larger than , sm…
Locally Stationary Distributions: A Framework for Analyzing Slow-Mixing Markov Chains
Kuikui Liu, Sidhanth Mohanty, Prasad Raghavendra +2
Many natural Markov chains fail to mix to their stationary distribution in polynomially many steps. Often, this slow mixing is inevitable since it is computationally intractable to…