
Adam
 Referenced in 458 articles
[sw22205]
 Adam: A Method for Stochastic Optimization. We introduce Adam, an algorithm for firstorder gradient ... based optimization of stochastic objective functions, based on adaptive estimates of lowerorder moments ... require little tuning. Some connections to related algorithms, on which Adam was inspired, are discussed ... analyze the theoretical convergence properties of the algorithm and provide a regret bound...

MSLiP
 Referenced in 109 articles
[sw01410]
 implementation of a nested decomposition algorithm for the multistage stochastic linear programming problem. Many ... deterministic staircase problems are adapted to the stochastic setting and their effect on computation times ... Numerical results compare the performance of the algorithm to MINOS...

HdBCS
 Referenced in 78 articles
[sw29884]
 code software implementing a an efficient stochastic search algorithm for for exploring spaces of Gaussian...

COPASI
 Referenced in 66 articles
[sw12253]
 behavior using ODEs or Gillespie’s stochastic simulation algorithm; arbitrary discrete events can be included...

AdaGrad
 Referenced in 133 articles
[sw22202]
 ADAGRAD: adaptive gradient algorithm; Adaptive subgradient methods for online learning and stochastic optimization. We present ... paradigm stems from recent advances in stochastic optimization and online learning which employ proximal functions ... control the gradient steps of the algorithm. We describe and analyze an apparatus for adaptively...

Pegasos
 Referenced in 100 articles
[sw08752]
 analyze a simple and effective stochastic subgradient descent algorithm for solving the optimization problem ... training example. In contrast, previous analyses of stochastic gradient descent methods for SVMs require ... size of the training set, the resulting algorithm is especially suited for learning from large...

SGDQN
 Referenced in 26 articles
[sw19411]
 gradient descent. The SGDQN algorithm is a stochastic gradient descent algorithm that makes careful ... stochastic gradient descent but requires less iterations to achieve the same accuracy. This algorithm...

EOlib
 Referenced in 19 articles
[sw00239]
 helps you to write your own stochastic optimization algorithms insanely fast.Evolutionary algorithms forms a family ... algorithms inspired by the theory of evolution, that solve various problems. They evolve ... produce the best results. These are stochastic algorithms, because they iteratively use random processes...

RMAX
 Referenced in 32 articles
[sw02539]
 Singh’s E^3 algorithm, covering zerosum stochastic games. (2) It has a built ... under uncertainty” bias used in many RL algorithms. (4) It is simpler, more general ... Tennenholtz’s LSG algorithm for learning in single controller stochastic games. (5) It generalizes...

AISBN
 Referenced in 25 articles
[sw02223]
 evidential reasoning in large Bayesian networks Stochastic sampling algorithms, while an attractive alternative to exact...

Jellyfish
 Referenced in 29 articles
[sw12431]
 Parallel stochastic gradient algorithms for largescale matrix completion. This paper develops Jellyfish, an algorithm...

SMART_
 Referenced in 33 articles
[sw04097]
 Logical and stochastic modeling with smart. We describe the main features of Smart, a software ... modelchecking algorithms, are available. For the study of stochastic and timing behavior, both sparse ... simulation is always applicable regardless of the stochastic nature of the process, but certain classes ... easy integration of new formalisms and solution algorithms...

MCQueue
 Referenced in 141 articles
[sw05198]
 queue, the transient M/M/1 queue). The algorithms in this software package are based on methods ... book H.C. Tijms, A First Course in Stochastic Models, Wiley...

HOGWILD
 Referenced in 59 articles
[sw28396]
 Stochastic Gradient Descent. Stochastic Gradient Descent (SGD) is a popular algorithm that can achieve state...

GillespieSSA
 Referenced in 10 articles
[sw21016]
 package GillespieSSA: Gillespie’s Stochastic Simulation Algorithm (SSA). GillespieSSA provides a simple to use, intuitive ... extensible interface to several stochastic simulation algorithms for generating simulated trajectories of finite population continuous ... Currently it implements Gillespie’s exact stochastic simulation algorithm (Direct method) and several approximate methods...

PRISMgames
 Referenced in 19 articles
[sw12934]
 present PRISMgames, a model checker for stochastic multiplayer games, which supports modelling, automated ... simulator, whilst adding novel model checking algorithms for stochastic games, as well as functionality...

Dizzy
 Referenced in 18 articles
[sw35541]
 original with implementations of faster stochastic simulation algorithms such as the optimised direct method ... Users can compare the effectiveness of the stochastic simulators on the problems which interest them...

CMAES
 Referenced in 111 articles
[sw05063]
 Adaptation Evolution Strategy. Evolution strategies (ES) are stochastic, derivativefree methods for numerical optimization ... They belong to the class of evolutionary algorithms and evolutionary computation. An evolutionary algorithm ... generated by variation, usually in a stochastic way, and then some individuals are selected...

MCELL
 Referenced in 23 articles
[sw06121]
 uses highly optimized Monte Carlo algorithms to track the stochastic behavior of discrete molecules...

PGSL
 Referenced in 11 articles
[sw04748]
 direct stochastic algorithm for global search This paper presents a new algorithm called probabilistic global...