Saved in:
| Main Authors: | Fox, Derek, Hernandez, Samuel, Tong, Qianqian |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2407.16968 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Minimum Variance Unbiased N:M Sparsity for the Neural Gradients
by: Chmiel, Brian, et al.
Published: (2022)
by: Chmiel, Brian, et al.
Published: (2022)
A Variance-Reduced Cubic-Regularized Newton for Policy Optimization
by: Sun, Cheng, et al.
Published: (2025)
by: Sun, Cheng, et al.
Published: (2025)
Operationalizing Fairness: Post-Hoc Threshold Optimization Under Hard Resource Limits
by: Singh, Moirangthem Tiken, et al.
Published: (2026)
by: Singh, Moirangthem Tiken, et al.
Published: (2026)
Improving Decision Sparsity
by: Sun, Yiyang, et al.
Published: (2024)
by: Sun, Yiyang, et al.
Published: (2024)
New Insight of Variance reduce in Zero-Order Hard-Thresholding: Mitigating Gradient Error and Expansivity Contradictions
by: Yuan, Xinzhe, et al.
Published: (2026)
by: Yuan, Xinzhe, et al.
Published: (2026)
Grokking as a Variance-Limited Phase Transition: Spectral Gating and the Epsilon-Stability Threshold
by: Acharya, Pratyush, et al.
Published: (2026)
by: Acharya, Pratyush, et al.
Published: (2026)
EXION: Exploiting Inter- and Intra-Iteration Output Sparsity for Diffusion Models
by: Heo, Jaehoon, et al.
Published: (2025)
by: Heo, Jaehoon, et al.
Published: (2025)
GEM-Style Constraints for PEFT with Dual Gradient Projection in LoRA
by: Tekmen, Brian, et al.
Published: (2026)
by: Tekmen, Brian, et al.
Published: (2026)
Large Language Model Compression with Global Rank and Sparsity Optimization
by: Zhou, Changhai, et al.
Published: (2025)
by: Zhou, Changhai, et al.
Published: (2025)
Ensuring Safety in an Uncertain Environment: Constrained MDPs via Stochastic Thresholds
by: Zuo, Qian, et al.
Published: (2025)
by: Zuo, Qian, et al.
Published: (2025)
Multi-View Graph Feature Propagation for Privacy Preservation and Feature Sparsity
by: Harari, Etzion, et al.
Published: (2025)
by: Harari, Etzion, et al.
Published: (2025)
Reducing Credit Assignment Variance via Counterfactual Reasoning Paths
by: Ding, Fei, et al.
Published: (2026)
by: Ding, Fei, et al.
Published: (2026)
Optimizing Chain-of-Thought Reasoners via Gradient Variance Minimization in Rejection Sampling and RL
by: Yao, Jiarui, et al.
Published: (2025)
by: Yao, Jiarui, et al.
Published: (2025)
Variance-Reduction Guidance: Sampling Trajectory Optimization for Diffusion Models
by: Xu, Shifeng, et al.
Published: (2025)
by: Xu, Shifeng, et al.
Published: (2025)
On the Role of Preference Variance in Preference Optimization
by: Guo, Jiacheng, et al.
Published: (2025)
by: Guo, Jiacheng, et al.
Published: (2025)
Homeostasis and Sparsity in Transformer
by: Kotyuzanskiy, Leonid, et al.
Published: (2024)
by: Kotyuzanskiy, Leonid, et al.
Published: (2024)
Polar Sparsity: High Throughput Batched LLM Inferencing with Scalable Contextual Sparsity
by: Shrestha, Susav, et al.
Published: (2025)
by: Shrestha, Susav, et al.
Published: (2025)
A Universal Banach--Bregman Framework for Stochastic Iterations: Unifying Stochastic Mirror Descent, Learning and LLM Training
by: Zhang, Johnny R., et al.
Published: (2025)
by: Zhang, Johnny R., et al.
Published: (2025)
Temporal Pair Consistency for Variance-Reduced Flow Matching
by: Maduabuchi, Chika, et al.
Published: (2026)
by: Maduabuchi, Chika, et al.
Published: (2026)
Ratio-Variance Regularized Policy Optimization for Efficient LLM Fine-tuning
by: Luo, Yu, et al.
Published: (2026)
by: Luo, Yu, et al.
Published: (2026)
Model-Based Epistemic Variance of Values for Risk-Aware Policy Optimization
by: Luis, Carlos E., et al.
Published: (2023)
by: Luis, Carlos E., et al.
Published: (2023)
GNN-VPA: A Variance-Preserving Aggregation Strategy for Graph Neural Networks
by: Schneckenreiter, Lisa, et al.
Published: (2024)
by: Schneckenreiter, Lisa, et al.
Published: (2024)
V-ABFT: Variance-Based Adaptive Threshold for Fault-Tolerant Matrix Multiplication in Mixed-Precision Deep Learning
by: Gao, Yiheng, et al.
Published: (2026)
by: Gao, Yiheng, et al.
Published: (2026)
Sparsity and Out-of-Distribution Generalization
by: Aaronson, Scott, et al.
Published: (2026)
by: Aaronson, Scott, et al.
Published: (2026)
Sparsity and Superposition in Mixture of Experts
by: Chaudhari, Marmik, et al.
Published: (2025)
by: Chaudhari, Marmik, et al.
Published: (2025)
Efficient Exploration for Iterative Nash Preference Optimization
by: Nan, Tianlong, et al.
Published: (2026)
by: Nan, Tianlong, et al.
Published: (2026)
Understanding the Challenges in Iterative Generative Optimization with LLMs
by: Nie, Allen, et al.
Published: (2026)
by: Nie, Allen, et al.
Published: (2026)
Comparing Contrastive and Triplet Loss: Variance Analysis and Optimization Behavior
by: Zeng, Donghuo
Published: (2025)
by: Zeng, Donghuo
Published: (2025)
Adaptive Multi-Fidelity Reinforcement Learning for Variance Reduction in Engineering Design Optimization
by: Agrawal, Akash, et al.
Published: (2025)
by: Agrawal, Akash, et al.
Published: (2025)
GVPO: Group Variance Policy Optimization for Large Language Model Post-Training
by: Zhang, Kaichen, et al.
Published: (2025)
by: Zhang, Kaichen, et al.
Published: (2025)
HGOE: Hybrid External and Internal Graph Outlier Exposure for Graph Out-of-Distribution Detection
by: He, Junwei, et al.
Published: (2024)
by: He, Junwei, et al.
Published: (2024)
Towards Bridging Review Sparsity in Recommendation with Textual Edge Graph Representation
by: Wang, Leyao, et al.
Published: (2025)
by: Wang, Leyao, et al.
Published: (2025)
On the Convergence of Experience Replay in Policy Optimization: Characterizing Bias, Variance, and Finite-Time Convergence
by: Zheng, Hua, et al.
Published: (2021)
by: Zheng, Hua, et al.
Published: (2021)
On the Sparsity of the Strong Lottery Ticket Hypothesis
by: Natale, Emanuele, et al.
Published: (2024)
by: Natale, Emanuele, et al.
Published: (2024)
Wasserstein Distances, Neuronal Entanglement, and Sparsity
by: Sawmya, Shashata, et al.
Published: (2024)
by: Sawmya, Shashata, et al.
Published: (2024)
On the Identifiability of Nonlinear ICA: Sparsity and Beyond
by: Zheng, Yujia, et al.
Published: (2022)
by: Zheng, Yujia, et al.
Published: (2022)
Sparsity-Aware Evolution for Model Merging
by: Zhang, Huan, et al.
Published: (2026)
by: Zhang, Huan, et al.
Published: (2026)
Scaling Attention via Feature Sparsity
by: Xie, Yan, et al.
Published: (2026)
by: Xie, Yan, et al.
Published: (2026)
Theoretical Analysis of Sparse Optimization with Reparameterization, Weight Decay, and Adaptive Learning Rate
by: Xu, Huangyu, et al.
Published: (2026)
by: Xu, Huangyu, et al.
Published: (2026)
The Optimal Token Baseline: Variance Reduction for Long-Horizon LLM-RL
by: Li, Yingru, et al.
Published: (2026)
by: Li, Yingru, et al.
Published: (2026)
Similar Items
-
Minimum Variance Unbiased N:M Sparsity for the Neural Gradients
by: Chmiel, Brian, et al.
Published: (2022) -
A Variance-Reduced Cubic-Regularized Newton for Policy Optimization
by: Sun, Cheng, et al.
Published: (2025) -
Operationalizing Fairness: Post-Hoc Threshold Optimization Under Hard Resource Limits
by: Singh, Moirangthem Tiken, et al.
Published: (2026) -
Improving Decision Sparsity
by: Sun, Yiyang, et al.
Published: (2024) -
New Insight of Variance reduce in Zero-Order Hard-Thresholding: Mitigating Gradient Error and Expansivity Contradictions
by: Yuan, Xinzhe, et al.
Published: (2026)