The following pages link to (Q3997575):
Displaying 50 items.
- Network games; adaptations to Nash-Cournot equilibrium (Q1918427) (← links)
- An algorithm for blind equalization and synchronization (Q1925074) (← links)
- Stochastic Nelder-Mead simplex method -- a new globally convergent direct search method for simulation optimization (Q1926785) (← links)
- Real time estimation of stochastic volatility processes (Q1931658) (← links)
- Exchanges and measures of risks (Q1938970) (← links)
- Structured prediction by joint kernel support estimation (Q1959532) (← links)
- Subspace-based fault detection algorithms for vibration monitoring (Q1961199) (← links)
- Rates of convergence of adaptive step-size of stochastic approximation algorithms (Q1977809) (← links)
- Adaptive sampling of large deviations (Q1990117) (← links)
- Optimal consumption under uncertainty, liquidity constraints, and bounded rationality (Q1994382) (← links)
- General multilevel adaptations for stochastic approximation algorithms. II: CLTs (Q1994904) (← links)
- Convergence and convergence rate of stochastic gradient search in the case of multiple and non-isolated extrema (Q2018557) (← links)
- Convergence of stochastic proximal gradient algorithm (Q2019902) (← links)
- Streaming changepoint detection for transition matrices (Q2036764) (← links)
- Unbiased estimation of the gradient of the log-likelihood in inverse problems (Q2058724) (← links)
- Efficient stochastic optimisation by unadjusted Langevin Monte Carlo. Application to maximum marginal likelihood and empirical Bayesian estimation (Q2058738) (← links)
- Fast incremental expectation maximization for finite-sum optimization: nonasymptotic convergence (Q2058782) (← links)
- Invariant measures for multidimensional fractional stochastic volatility models (Q2093310) (← links)
- Fundamental design principles for reinforcement learning algorithms (Q2094028) (← links)
- Computation for latent variable model estimation: a unified stochastic proximal framework (Q2103576) (← links)
- Tackling algorithmic bias in neural-network classifiers using Wasserstein-2 regularization (Q2103876) (← links)
- The Barron space and the flow-induced function spaces for neural network models (Q2117337) (← links)
- Unbiased estimation of the gradient of the log-likelihood for a class of continuous-time state-space models (Q2121629) (← links)
- Accelerating mini-batch SARAH by step size rules (Q2127094) (← links)
- Online adjoint methods for optimization of PDEs (Q2128627) (← links)
- Reference points and learning (Q2138367) (← links)
- Approximating the operating characteristics of Bayesian uncertainty directed trial designs (Q2156810) (← links)
- Convergence of constant step stochastic gradient descent for non-smooth non-convex functions (Q2158840) (← links)
- An adaptively weighted stochastic gradient MCMC algorithm for Monte Carlo simulation and global optimization (Q2159413) (← links)
- The method of averaged models for discrete-time adaptive systems (Q2173039) (← links)
- Bridging the gap between constant step size stochastic gradient descent and Markov chains (Q2196224) (← links)
- Non asymptotic controls on a recursive superquantile approximation (Q2233588) (← links)
- Strong averaging principle for two-time-scale stochastic McKean-Vlasov equations (Q2238979) (← links)
- On the stability of some controlled Markov chains and its applications to stochastic approximation with Markovian dynamic (Q2258523) (← links)
- The stochastic approximation method for estimation of a distribution function (Q2261928) (← links)
- Learning in games with unstable equilibria (Q2271377) (← links)
- Exchange rates and fundamentals under adaptive learning (Q2271674) (← links)
- Nonlinear randomized urn models: a stochastic approximation viewpoint (Q2274219) (← links)
- A latent discrete Markov random field approach to identifying and classifying historical forest communities based on spatial multivariate tree species counts (Q2291519) (← links)
- Lower error bounds for the stochastic gradient descent optimization algorithm: sharp convergence rates for slowly and fast decaying learning rates (Q2303416) (← links)
- Stochastic proximal-gradient algorithms for penalized mixed models (Q2329762) (← links)
- On the almost sure convergence of adaptive allocation procedures (Q2348729) (← links)
- Interacting generalized Friedman's urn systems (Q2360245) (← links)
- Stochastic approximation to understand simple simulation models (Q2376023) (← links)
- Quantile estimation with adaptive importance sampling (Q2380103) (← links)
- Annealing stochastic approximation Monte Carlo algorithm for neural network training (Q2384162) (← links)
- Learning in perturbed asymmetric games (Q2387315) (← links)
- A generalized urn with multiple drawing and random addition (Q2414949) (← links)
- An approximation of the distribution of learning estimates in macroeconomic models (Q2416791) (← links)
- An adaptive version for the Metropolis adjusted Langevin algorithm with a truncated drift (Q2433262) (← links)
