We introduce the Hamming ball sampler, a novel Markov chain Monte Carlo algorithm, for efficient inference in statistical models involving high-dimensional discrete state spaces. The sampling scheme uses an auxiliary variable construction that adaptively truncates the model space allowing iterative exploration of the full model space. The approach generalizes conventional Gibbs sampling schemes...

–Thompson sampling is a heuristic algorithm for the multi-armed bandit problem which has long tradition in machine learning. The Bayesian spirit sense that it selects arms based on posterior samples of reward probabilities each arm. By forging connection between combinatorial binary bandits and spike-and-slab variable selection, we propose stochastic optimization approach to subset selection ca...

Time and the choice of measurement time scales is fundamental to how we choose represent information data in finance. This implies both units aggregation for resulting statistical measurables used describe a financial system. It also defines measure relationship between different traded instruments. As move from high-frequency scales, when individual trade quote events occur, mesoscales correla...

In the present work, the numerical solution of two-dimensional variable-order fractional cable (VOFC) equation using meshless collocation methods with thin plate spline radial basis functions is considered. In the proposed methods, we first use two schemes of order O(τ2) for the time derivatives and then meshless approach is applied to the space component. Numerical results obtained ...