gradient estimator

A First-order Generative Bilevel Optimization Framework for Diffusion Models ICML 2025 Disentangling impact of capacity, objective, batchsize, estimators, and step-size on flow VI AISTATS 2025 Do Stochastic, Feel Noiseless: Stable Stochastic Optimization via a Double Momentum Mechanism ICLR 2025 Hybrid Decentralized Optimization: Leveraging Both First- and Zeroth-Order Optimizers for Faster Convergence AAAI 2025 Online Nonsubmodular Optimization with Delayed Feedback in the Bandit Setting AAAI 2025 POTEC: Off-Policy Contextual Bandits for Large Action Spaces via Policy Decomposition ICLR 2025 Revisiting Zeroth-Order Optimization: Minimum-Variance Two-Point Estimators and Directionally Aligned Perturbations ICLR 2025 Stability and Generalization for Stochastic (Compositional) Optimizations IJCAI 2025 Stochastic Interior-Point Methods for Smooth Conic Optimization with Applications JMLR 2025 Zeroth-Order Methods for Nonconvex Stochastic Problems with Decision-Dependent Distributions AAAI 2025 An Efficient High-dimensional Gradient Estimator for Stochastic Differential Equations NeurIPS 2024 Asymptotics of Alpha-Divergence Variational Inference Algorithms with Exponential Families NeurIPS 2024 Countering the Communication Bottleneck in Federated Learning: A Highly Efficient Zero-Order Optimization Technique JMLR 2024 Improved Dimensionality Dependence for Zeroth-Order Optimisation over Cross-Polytopes ICML 2024 Minimax Excess Risk of First-Order Methods for Statistical Learning with Data-Dependent Oracles AISTATS 2024 Sequential Monte Carlo for Inclusive KL Minimization in Amortized Variational Inference AISTATS 2024 SILVER: Single-loop variance reduction and application to federated learning ICML 2024 Stochastic Zeroth-Order Optimization under Strongly Convexity and Lipschitz Hessian: Minimax Sample Complexity NeurIPS 2024 A Fully First-Order Method for Stochastic Bilevel Optimization ICML 2023 Cold Analysis of Rao-Blackwellized Straight-Through Gumbel-Softmax Gradient Estimator ICML 2023 Differentiable Sampling of Categorical Distributions Using the CatLog-Derivative Trick NeurIPS 2023 How gradient estimator variance and bias impact learning in neural networks ICLR 2023 Implicit Bilevel Optimization: Differentiating through Bilevel Optimization Programming AAAI 2023 SIMPLE: A Gradient Estimator for k-Subset Sampling ICLR 2023 A gradient estimator via L1-randomization for online zero-order optimization with two point feedback NeurIPS 2022