gradient estimation

ARMS: Antithetic-REINFORCE-Multi-Sample Gradient for Binary Variables ICML 2021 Attack As the Best Defense: Nullifying Image-to-Image Translation GANs via Limit-Aware Adversarial Attack ICCV 2021 A unified view of likelihood ratio and reparameterization gradients AISTATS 2021 CARMS: Categorical-Antithetic-REINFORCE Multi-Sample Gradient Estimator NeurIPS 2021 Deep Bayesian Quadrature Policy Optimization AAAI 2021 Don’t Generate Me: Training Differentially Private Generative Models with Sinkhorn Divergence NeurIPS 2021 Generalized Doubly Reparameterized Gradient Estimators ICML 2021 Improved Contrastive Divergence Training of Energy-Based Models ICML 2021 MALI: A memory efficient and reverse accurate integrator for Neural ODEs ICLR 2021 MAZE: Data-Free Model Stealing Attack Using Zeroth-Order Gradient Estimation CVPR 2021 Nearest Neighbour Based Estimates of Gradients: Sharp Nonasymptotic Bounds and Applications AISTATS 2021 Nonlinear Projection Based Gradient Estimation for Query Efficient Blackbox Attacks AISTATS 2021 On the Convergence of Prior-Guided Zeroth-Order Optimization Algorithms NeurIPS 2021 On Training Implicit Models NeurIPS 2021 Parallel tempering on optimized paths ICML 2021 Randomized Automatic Differentiation ICLR 2021 Random Noise Defense Against Query-Based Black-Box Attacks NeurIPS 2021 Rao-Blackwellizing the Straight-Through Gumbel-Softmax Gradient Estimator ICLR 2021 Recomposing the Reinforcement Learning Building Blocks with Hypernetworks ICML 2021 Reserve Price Optimization for First Price Auctions in Display Advertising ICML 2021 Revisiting Few-sample BERT Fine-tuning ICLR 2021 SA-BNN: State-Aware Binary Neural Network AAAI 2021 Storchastic: A Framework for General Stochastic Automatic Differentiation NeurIPS 2021 Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies ICML 2021 Unifying Gradient Estimators for Meta-Reinforcement Learning via Off-Policy Evaluation NeurIPS 2021