conftrace_

variance reduction

523 papers

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Also known as

VR

Co-occurring keywords

stochastic optimization (1060) stochastic gradient descent (1091) stochastic gradient (296) reinforcement learning (4352) policy gradient (520) nonconvex optimization (316) gradient estimation (150) non-convex optimization (547) importance sampling (318) control variate (54)

Papers

Variance Reduction and Low Sample Complexity in Stochastic Optimization via Proximal Point Method ALT 2026
Stabilizing Policy Gradient Methods via Reward Profiling AAAI 2026
KETCHUP: K-Step Return Estimation for Sequential Knowledge Distillation EACL 2026
Guided Model Merging for Hybrid Data Learning: Leveraging Centralized Data to Refine Decentralized Models WACV 2026
Reusing Samples in Variance Reduction ALT 2026
LLaDA 1.5: Variance-Reduced Preference Optimization for Large Language Diffusion Models ACL 2026
Behaviour Policy Optimization: Provably Lower Variance Return Estimates for Off-Policy Reinforcement Learning AAAI 2026
Improving Value-based Process Verifier via Low-Cost Variance Reduction AAAI 2026
Variance Reduction via Resampling and Experience Replay AAAI 2026
Decentralized Non-convex Stochastic Optimization with Heterogeneous Variance AAAI 2026
Zeroth-Order Methods for Nonconvex Stochastic Problems with Decision-Dependent Distributions AAAI 2025
Accelerated Methods with Compressed Communications for Distributed Optimization Problems Under Data Similarity AAAI 2025
Faster Double Adaptive Gradient Methods AAAI 2025
EF21 with Bells & Whistles: Six Algorithmic Extensions of Modern Error Feedback JMLR 2025
VFOSA: Variance-Reduced Fast Operator Splitting Algorithms for Generalized Equations JMLR 2025
Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback JMLR 2025
Revisiting Fairness in Multitask Learning: A Performance-Driven Approach for Variance Reduction CVPR 2025
Federated Stochastic Bilevel Optimization with Fully First-Order Gradients IJCAI 2025
Efficient Multi-Policy Evaluation for Reinforcement Learning AAAI 2025
Optimal Complexity in Byzantine-Robust Distributed Stochastic Optimization with Data Heterogeneity JMLR 2025
Instance-level Randomization: Toward More Stable LLM Evaluations EMNLP 2025
Sketchy Moment Matching: Toward Fast and Provable Data Selection for Finetuning NIPS 2024
Quantum Algorithms for Non-smooth Non-convex Optimization NIPS 2024
Breaking the Heavy-Tailed Noise Barrier in Stochastic Optimization Problems AISTATS 2024
Weight for Robustness: A Comprehensive Approach towards Optimal Fault-Tolerant Asynchronous ML NIPS 2024