conftrace_

gradient variance

31 papers

Explore in graph

Co-occurring keywords

stochastic gradient descent (1091) variational inference (2069) neural network optimization (1293) stochastic gradient (296) batch size (34) large language model (13587) control variate (54) large-batch training (5) adversarial example (564) language model (4599)

Papers

Gated Differentiable Working Memory for Long-Context Language Modeling ACL 2026
Adaptive Non-Uniform Timestep Sampling for Accelerating Diffusion Model Training CVPR 2025
Training with Fewer Bits: Unlocking Edge LLMs Training with Stochastic Rounding EMNLP 2025
MaZO: Masked Zeroth-Order Optimization for Multi-Task Fine-Tuning of Large Language Models EMNLP 2025
SMEC:Rethinking Matryoshka Representation Learning for Retrieval Embedding Compression EMNLP 2025
Boosting the Transferability of Adversarial Attack on Vision Transformer with Adaptive Token Tuning NIPS 2024
Linear Convergence of Black-Box Variational Inference: Should We Stick the Landing? AISTATS 2024
Joint control variate for faster black-box variational inference AISTATS 2024
Benefits of Non-Linear Scale Parameterizations in Black Box Variational Inference through Smoothness Results and Gradient Variance Bounds AISTATS 2024
From Variance to Veracity: Unbundling and Mitigating Gradient Variance in Differentiable Bundle Adjustment Layers CVPR 2024
PA&DA: Jointly Sampling Path and Data for Consistent NAS CVPR 2023
Model-Based Reparameterization Policy Gradient Methods: Theory and Practical Algorithms NIPS 2023
Influence Scores at Scale for Efficient Language Data Sampling EMNLP 2023
Transferable Adversarial Attacks on Vision Transformers With Token Gradient Regularization CVPR 2023
Practical and Matching Gradient Variance Bounds for Black-Box Variational Bayesian Inference ICML 2023
Fishr: Invariant Gradient Variances for Out-of-Distribution Generalization ICML 2022
Markov Chain Score Ascent: A Unifying Framework of Variational Inference with Markovian Gradients NIPS 2022
The Stability-Efficiency Dilemma: Investigating Sequence Length Warmup for Training GPT Models NIPS 2022
A Deeper Understanding of State-Based Critics in Multi-Agent Reinforcement Learning AAAI 2022
How Sampling Impacts the Robustness of Stochastic Neural Networks NIPS 2022
Large-batch Optimization for Dense Visual Predictions: Training Faster R-CNN in 4.2 Minutes NIPS 2022
Information-Theoretic Generalization Bounds for Stochastic Gradient Descent COLT 2021
ARCH: Efficient Adversarial Regularized Training with Caching EMNLP 2021
An Empirical Study of Stochastic Gradient Descent with Structured Covariance Noise AISTATS 2020
On the interplay between noise and curvature and its effect on optimization and generalization AISTATS 2020