SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
(Bandit) Convex Optimization with Biased Noisy Gradient Oracles
15 references·0 citing·33 second hop
(Bandit) Convex Optimization with Biased Noisy Gradient Oracles (2016)(Bandit) Convex Optimization with Biased …Bandit Convex Optimization: Towards Tight Bounds (2014)Bandit Convex Optimization: T…Stochastic Convex Optimization with Bandit Feedback (2013)Stochastic Convex Optimizatio…Stochastic Recursive Algorithms for Optimization (2012)Stochastic Recursive Algorith…Random gradient-free minimization of convex functions (2011)Random gradient-free minimiza…Improved Regret Guarantees for Online Smooth Convex Optimization with Bandit Feedback (2011)Improved Regret Guarantees fo…Optimal Algorithms for Online Convex Optimization with Multi-Point Bandit Feedback. (2010)Optimal Algorithms for Online…Competing in the dark: An efficient algorithm for bandit linear optimization (2008)Competing in the dark: An eff…Adaptive Online Gradient Descent (2007)Adaptive Online Gradient Desc…Online convex optimization in the bandit setting: gradient descent without a gradient (2004)Online convex optimization in…Accelerated randomized stochastic optimization (2003)Accelerated randomized stocha…Simulation-Based Optimization with Stochastic Approximation Using Common Random Numbers (1999)Simulation-Based Optimization…A one-measurement form of simultaneous perturbation stochastic approximation (1997)A one-measurement form of sim…Multivariate stochastic approximation using a simultaneous perturbation gradient approximation (1992)Multivariate stochastic appro…Lower Rate of Convergence for Locating a Maximum of a Function (1988)Lower Rate of Convergence for…Stochastic Approximation Methods for Constrained and Unconstrained Systems (1978)Stochastic Approximation Meth…Some aspects of the sequential design of experiments (1952)The Nonstochastic Multiarmed Bandit Problem (2002)Prediction, Learning, and Games (2006)Trading Regret for Efficiency: Online Convex Optimization with Long Term Constraints (2011)Online Learning with Predictable Sequences (2012)The best of both worlds: stochastic and adversarial bandits (2012)Online convex programming and generalized infinitesimal gradient ascent (2003)Bandit Convex Optimization for Scalable and Dynamic IoT Management (2018)Exponentiated Gradient versus Gradient Descent for Linear Predictors (1997)Nearly Tight Bounds for the Continuum-Armed Bandit Problem (2004)Multi-armed bandits in metric spaces (2008)Linearly Parameterized Bandits (2010)Introduction to Stochastic Programming (2011)Acceleration of Stochastic Approximation by Averaging (1992)Implementation of the simultaneous perturbation algorithm for stochastic optimization (1998)Convergence of simultaneous perturbation stochastic approximation for nondifferentiable optimization (2003)Two-timescale simultaneous perturbation stochastic approximation using deterministic perturbation sequences (2003)Adaptive multivariate three-timescale stochastic approximation algorithms for simulation based optimization (2005)Stochastic Estimation of the Maximum of a Regression Function (1952)Feature Article: Optimization for simulation: Theory vs. Practice (2002)Simulation optimization: a review of algorithms and applications (2015)Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting (2012)Coordinating Pricing and Inventory Replenishment with Nonparametric Demand Learning (2015)Bandit Convex Optimization with Biased Noisy Gradient Oracles (2017)Multi-Modal Dynamic Pricing (2019)Logarithmic Regret Algorithms for Online Convex Optimization (2006)Efficient Optimal Learning for Contextual Bandits (2011)A Stochastic Approximation Method (1951)Convergence of least squares learning mechanisms in self-referential linear stochastic models (1989)Simulation Budget Allocation for Further Enhancing the Efficiency of Ordinal Optimization (2000)Monte Carlo Sampling Methods (2003)Stochastic Optimization in a Cumulative Prospect Theory Framework (2018)Convergence of Learning Dynamics in Stackelberg Games (2019)
this work references cited by second hop

References

  • 1992Multivariate stochastic approximation using a simultaneous perturbation gradient approximation2,282 cited
  • 1978Stochastic Approximation Methods for Constrained and Unconstrained Systems1,459 cited
  • 2004Online convex optimization in the bandit setting: gradient descent without a gradient599 cited
  • 2010Optimal Algorithms for Online Convex Optimization with Multi-Point Bandit Feedback.255 cited
  • 1997A one-measurement form of simultaneous perturbation stochastic approximation254 cited
  • 2008Competing in the dark: An efficient algorithm for bandit linear optimization182 cited
  • 2007Adaptive Online Gradient Descent180 cited
  • 2013Stochastic Convex Optimization with Bandit Feedback167 cited
  • 2012Stochastic Recursive Algorithms for Optimization108 cited
  • 1999Simulation-Based Optimization with Stochastic Approximation Using Common Random Numbers100 cited
  • 2011Random gradient-free minimization of convex functions89 cited
  • 2014Bandit Convex Optimization: Towards Tight Bounds66 cited
  • 1988Lower Rate of Convergence for Locating a Maximum of a Function55 cited
  • 2011Improved Regret Guarantees for Online Smooth Convex Optimization with Bandit Feedback54 cited
  • 2003Accelerated randomized stochastic optimization

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

46 cited

Cited by

No citing works inside the corpus for this window.