conftrace_

gradient estimation

150 papers

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Co-occurring keywords

variance reduction (523) reinforcement learning (4352) zeroth-order optimization (102) policy gradient (520) adversarial attack (1621) stochastic optimization (1060) variational inference (2069) generative model (2892) large language model (13587) black-box attack (237)

Papers

Structured Evolution with Compact Architectures for Scalable Policy Optimization ICML 2018
Learning in Integer Latent Variable Models with Nested Automatic Differentiation ICML 2018
A Spectral Approach to Gradient Estimation for Implicit Distributions ICML 2018
Gradient Estimation with Simultaneous Perturbation and Compressive Sensing JMLR 2018
DiCE: The Infinitely Differentiable Monte Carlo Estimator ICML 2018
End-to-End Differentiable Adversarial Imitation Learning ICML 2017
Understanding Synthetic Gradients and Decoupled Neural Interfaces ICML 2017
Adaptive Batch Size for Safe Policy Gradients NIPS 2017
Less than a Single Pass: Stochastically Controlled Stochastic Gradient AISTATS 2017
Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms AISTATS 2017
On the Estimation of the Gradient Lines of a Density and the Consistency of the Mean-Shift Algorithm JMLR 2016
ERRATA: On the Estimation of the Gradient Lines of a Density and the Consistency of the Mean-Shift Algorithm JMLR 2016
Gradient Estimation Using Stochastic Computation Graphs NIPS 2015
Sufficient Dimension Reduction via Direct Estimation of the Gradients of Logarithmic Conditional Densities ACML 2015
Algorithms for CVaR Optimization in MDPs NIPS 2014
Finite Sample Convergence Rates of Zero-Order Stochastic Optimization Methods NIPS 2012
Improving Policy Gradient Estimates with Influence Information ACML 2011
Improved Regret Guarantees for Online Smooth Convex Optimization with Bandit Feedback AISTATS 2011
Analysis and Improvement of Policy Gradient Estimation NIPS 2011
Learning Gradients: Predictive Models that Infer Geometry and Statistical Dependence JMLR 2010
Sensitivity analysis in HMMs with application to likelihood maximization NIPS 2009
Learning Coordinate Covariances via Gradients JMLR 2006
Geometric Variance Reduction in Markov Chains: Application to Value Function and Gradient Estimation JMLR 2006
Policy Gradient in Continuous Time JMLR 2006
Estimation of Gradients and Coordinate Covariation in Classification JMLR 2006