conftrace_

gradient estimator

59 papers

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Also known as

GE

Co-occurring keywords

variance reduction (523) variational inference (2069) stochastic optimization (1060) generative model (2892) gradient estimation (150) stochastic gradient (296) discrete latent variable (43) control variate (54) stochastic gradient descent (1091) evidence lower bound (68)

Papers

Stochastic Interior-Point Methods for Smooth Conic Optimization with Applications JMLR 2025
Online Nonsubmodular Optimization with Delayed Feedback in the Bandit Setting AAAI 2025
Hybrid Decentralized Optimization: Leveraging Both First- and Zeroth-Order Optimizers for Faster Convergence AAAI 2025
Stability and Generalization for Stochastic (Compositional) Optimizations IJCAI 2025
Zeroth-Order Methods for Nonconvex Stochastic Problems with Decision-Dependent Distributions AAAI 2025
Minimax Excess Risk of First-Order Methods for Statistical Learning with Data-Dependent Oracles AISTATS 2024
Stochastic Zeroth-Order Optimization under Strongly Convexity and Lipschitz Hessian: Minimax Sample Complexity NIPS 2024
Asymptotics of Alpha-Divergence Variational Inference Algorithms with Exponential Families NIPS 2024
Countering the Communication Bottleneck in Federated Learning: A Highly Efficient Zero-Order Optimization Technique JMLR 2024
An Efficient High-dimensional Gradient Estimator for Stochastic Differential Equations NIPS 2024
Sequential Monte Carlo for Inclusive KL Minimization in Amortized Variational Inference AISTATS 2024
Implicit Bilevel Optimization: Differentiating through Bilevel Optimization Programming AAAI 2023
Differentiable Sampling of Categorical Distributions Using the CatLog-Derivative Trick NIPS 2023
A Fully First-Order Method for Stochastic Bilevel Optimization ICML 2023
Cold Analysis of Rao-Blackwellized Straight-Through Gumbel-Softmax Gradient Estimator ICML 2023
On Biased Stochastic Gradient Estimation JMLR 2022
Multi-Sample Training for Neural Image Compression NIPS 2022
A Multi-Document Coverage Reward for RELAXed Multi-Document Summarization ACL 2022
A gradient estimator via L1-randomization for online zero-order optimization with two point feedback NIPS 2022
Robust SDE-Based Variational Formulations for Solving Linear PDEs via Deep Learning ICML 2022
ARMS: Antithetic-REINFORCE-Multi-Sample Gradient for Binary Variables ICML 2021
Multilevel Monte Carlo Variational Inference JMLR 2021
Efficient Neural Network Training via Forward and Backward Propagation Sparsification NIPS 2021
PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization ICML 2021
On Signal-to-Noise Ratio Issues in Variational Inference for Deep Gaussian Processes ICML 2021