Abstract Stochastic gradient descent method and its variants constitute the core optimization algorithms that achieve good convergence rates for solving machine learning problems. These are obtained especially when these fine-tuned application at hand. Although this tuning process can require large computational costs, recent work has shown costs be reduced by line search methods iteratively adjust step length. We propose an alternative approach to stochastic using a new algorithm based on...

This technical note calls for an interdisciplinary research agenda to study the intersection of policy problems and extreme events. We argue that events can unveil chronic in societies such as political polarization. used social media data following 2014 Soma mining disaster Turkey illustrative case study. Our findings indicate polarized sense-making during hinder effectiveness response recovery operations. conclude with some recommendations using operations improve communications contexts...

We characterize disjoint hypercyclic and supercyclic tuples of unilateral Rolewicz-type operators on $c_0(\N)$ $\ell^p(\N)$, $p \in [1, \infty)$, which are a generalization the backward shift operator. show that hypercyclicity supercyclicity equivalent among subfamily these always satisfy Disjoint Hypercyclicity Criterion. also simultaneous \infty)$.

In the present note, we solve two open questions posed by Salas in [H. Salas, The strong disjoint blow-up/collapse property, J. Funct. Spaces Appl., 2013, Article ID 146517, 6 pages] about hypercyclic operators. First, show that given any family $T_1, \dots, T_N$ of operators, one can always select an operator $T$ such extended T_N, T$ operators remains hypercyclic. fact, prove set which extend is dense topology algebra bounded Second, existence weakly mixing fail to possess a d-hypercyclic...

Stochastic gradient descent method and its variants constitute the core optimization algorithms that achieve good convergence rates for solving machine learning problems. These are obtained especially when these fine-tuned application at hand. Although this tuning process can require large computational costs, recent work has shown costs be reduced by line search methods iteratively adjust step length. We propose an alternative approach to stochastic using a new algorithm based on forward...

We obtain a Disjoint Frequent Hypercyclicity Criterion and show that it characterizes disjoint frequent hypercyclicity for family of unilateral pseudo-shifts on $c_0(\mathbb{N})$ $\ell^p(\mathbb{N})$, $1\le p <\infty$. As an application, we characterize frequently hypercyclic weighted shifts. give analogous results the weaker notions upper reiterative hypercyclicity. Finally, provide counterexamples showing that, although hypercyclicity, coincide shifts this equivalence fails versions these notions.

We characterize disjoint and simultaneously hypercyclic tuples of unilateral pseudo-shift operators on $\ell^p(\mathbb{N})$. As a consequence, complementing the results Bernal Jung, we give characterization for weighted shifts. also characterizations pseudo-shifts that satisfy Disjoint Simultaneous Hypercyclicity Criterions. Contrary to hypercyclicity case, shifts turn out be if only they Criterion.