Approximated Likelihood Ratio: A Forward-Only and Parallel Framework for Boosting Neural Network Training
Fuente:
arXiv
Saved in:
| Main Authors: | Zhang, Zeliang, Jiang, Jinyang, Liu, Zhuo, Liang, Susan, Peng, Yijie, Xu, Chenliang |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Forward Learning for Gradient-based Black-box Saliency Map Generation
by: Zhang, Zeliang, et al.
Published: (2024)
by: Zhang, Zeliang, et al.
Published: (2024)
FLOPS: Forward Learning with OPtimal Sampling
by: Ren, Tao, et al.
Published: (2024)
by: Ren, Tao, et al.
Published: (2024)
Forward Learning with Differential Privacy
by: Feng, Mingqian, et al.
Published: (2025)
by: Feng, Mingqian, et al.
Published: (2025)
Learning to Transform Dynamically for Better Adversarial Transferability
by: Zhu, Rongyi, et al.
Published: (2024)
by: Zhu, Rongyi, et al.
Published: (2024)
Forward Only Learning for Orthogonal Neural Networks of any Depth
by: Caillon, Paul, et al.
Published: (2025)
by: Caillon, Paul, et al.
Published: (2025)
Implicit Statistical Inference in Transformers: Approximating Likelihood-Ratio Tests In-Context
by: Chaudhry, Faris, et al.
Published: (2026)
by: Chaudhry, Faris, et al.
Published: (2026)
When Demonstrations Meet Generative World Models: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning
by: Zeng, Siliang, et al.
Published: (2023)
by: Zeng, Siliang, et al.
Published: (2023)
Closing the Loop: Coordinating Inventory and Recommendation via Deep Reinforcement Learning on Multiple Timescales
by: Jiang, Jinyang, et al.
Published: (2025)
by: Jiang, Jinyang, et al.
Published: (2025)
Half-order Fine-Tuning for Diffusion Model: A Recursive Likelihood Ratio Optimizer
by: Ren, Tao, et al.
Published: (2025)
by: Ren, Tao, et al.
Published: (2025)
Energy Consumption in Parallel Neural Network Training
by: Huber, Philipp, et al.
Published: (2025)
by: Huber, Philipp, et al.
Published: (2025)
Feed-Forward Optimization With Delayed Feedback for Neural Network Training
by: Flügel, Katharina, et al.
Published: (2023)
by: Flügel, Katharina, et al.
Published: (2023)
Can VLMs Truly Forget? Benchmarking Training-Free Visual Concept Unlearning
by: Tan, Zhangyun, et al.
Published: (2026)
by: Tan, Zhangyun, et al.
Published: (2026)
Dynamic Universal Approximation Theory: Foundations for Parallelism in Neural Networks
by: Wang, Wei, et al.
Published: (2024)
by: Wang, Wei, et al.
Published: (2024)
XQSV: A Structurally Variable Network to Imitate Human Play in Xiangqi
by: Zhou, Chenliang
Published: (2024)
by: Zhou, Chenliang
Published: (2024)
On the Improvement of Generalization and Stability of Forward-Only Learning via Neural Polarization
by: Terres-Escudero, Erik B., et al.
Published: (2024)
by: Terres-Escudero, Erik B., et al.
Published: (2024)
Know When to Abstain: Optimal Selective Classification with Likelihood Ratios
by: Heng, Alvin, et al.
Published: (2025)
by: Heng, Alvin, et al.
Published: (2025)
Deep Reinforcement Learning for Solving Management Problems: Towards A Large Management Mode
by: Jiang, Jinyang, et al.
Published: (2024)
by: Jiang, Jinyang, et al.
Published: (2024)
LNN-PINN: A Unified Physics-Only Training Framework with Liquid Residual Blocks
by: Tao, Ze, et al.
Published: (2025)
by: Tao, Ze, et al.
Published: (2025)
Optimizing Dense Feed-Forward Neural Networks
by: Balderas, Luis, et al.
Published: (2023)
by: Balderas, Luis, et al.
Published: (2023)
Forward Target Propagation: A Forward-Only Approach to Global Error Credit Assignment via Local Losses
by: As-Saquib, Nazmus Saadat, et al.
Published: (2025)
by: As-Saquib, Nazmus Saadat, et al.
Published: (2025)
Towards Universal Neural Likelihood Inference
by: Brahmavar, Shreyas Bhat, et al.
Published: (2025)
by: Brahmavar, Shreyas Bhat, et al.
Published: (2025)
LOGIN: A Large Language Model Consulted Graph Neural Network Training Framework
by: Qiao, Yiran, et al.
Published: (2024)
by: Qiao, Yiran, et al.
Published: (2024)
SCPL: Enhancing Neural Network Training Throughput with Decoupled Local Losses and Model Parallelism
by: Ho, Ming-Yao, et al.
Published: (2026)
by: Ho, Ming-Yao, et al.
Published: (2026)
Multi-Step Likelihood-Ratio Correction for Reinforcement Learning with Verifiable Rewards
by: Yoon, Deokgyu, et al.
Published: (2026)
by: Yoon, Deokgyu, et al.
Published: (2026)
ParaDySe: A Parallel-Strategy Switching Framework for Dynamic Sequence Lengths in Transformer
by: Ou, Zhixin, et al.
Published: (2025)
by: Ou, Zhixin, et al.
Published: (2025)
An Adaptive Placement and Parallelism Framework for Accelerating RLHF Training
by: Xiao, Youshao, et al.
Published: (2023)
by: Xiao, Youshao, et al.
Published: (2023)
A&B BNN: Add&Bit-Operation-Only Hardware-Friendly Binary Neural Network
by: Ma, Ruichen, et al.
Published: (2024)
by: Ma, Ruichen, et al.
Published: (2024)
Backpropagation-free Spiking Neural Networks with the Forward-Forward Algorithm
by: Ghader, Mohammadnavid, et al.
Published: (2025)
by: Ghader, Mohammadnavid, et al.
Published: (2025)
RiskPO: Risk-based Policy Optimization via Verifiable Reward for LLM Post-Training
by: Ren, Tao, et al.
Published: (2025)
by: Ren, Tao, et al.
Published: (2025)
Data-Algorithm-Architecture Co-Optimization for Fair Neural Networks on Skin Lesion Dataset
by: Sheng, Yi, et al.
Published: (2024)
by: Sheng, Yi, et al.
Published: (2024)
Conformal Inference under High-Dimensional Covariate Shifts via Likelihood-Ratio Regularization
by: Joshi, Sunay, et al.
Published: (2025)
by: Joshi, Sunay, et al.
Published: (2025)
Using Forwards-Backwards Models to Approximate MDP Homomorphisms
by: Mavor-Parker, Augustine N., et al.
Published: (2022)
by: Mavor-Parker, Augustine N., et al.
Published: (2022)
EVA-0: Test-Time Model Evolution with Only Two Forward Passes per Sample
by: Chen, Guohao, et al.
Published: (2026)
by: Chen, Guohao, et al.
Published: (2026)
Forward-Forward Learning achieves Highly Selective Latent Representations for Out-of-Distribution Detection in Fully Spiking Neural Networks
by: Terres-Escudero, Erik B., et al.
Published: (2024)
by: Terres-Escudero, Erik B., et al.
Published: (2024)
MoNTA: Accelerating Mixture-of-Experts Training with Network-Traffc-Aware Parallel Optimization
by: Guo, Jingming, et al.
Published: (2024)
by: Guo, Jingming, et al.
Published: (2024)
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias
by: Hu, Yuanzhe, et al.
Published: (2025)
by: Hu, Yuanzhe, et al.
Published: (2025)
Do More Details Always Introduce More Hallucinations in LVLM-based Image Captioning?
by: Feng, Mingqian, et al.
Published: (2024)
by: Feng, Mingqian, et al.
Published: (2024)
Discover and Mitigate Multiple Biased Subgroups in Image Classifiers
by: Zhang, Zeliang, et al.
Published: (2024)
by: Zhang, Zeliang, et al.
Published: (2024)
Parallelizing Node-Level Explainability in Graph Neural Networks
by: Llorente, Oscar, et al.
Published: (2026)
by: Llorente, Oscar, et al.
Published: (2026)
Prefix Grouper: Efficient GRPO Training through Shared-Prefix Forward
by: Liu, Zikang, et al.
Published: (2025)
by: Liu, Zikang, et al.
Published: (2025)
Similar Items
-
Forward Learning for Gradient-based Black-box Saliency Map Generation
by: Zhang, Zeliang, et al.
Published: (2024) -
FLOPS: Forward Learning with OPtimal Sampling
by: Ren, Tao, et al.
Published: (2024) -
Forward Learning with Differential Privacy
by: Feng, Mingqian, et al.
Published: (2025) -
Learning to Transform Dynamically for Better Adversarial Transferability
by: Zhu, Rongyi, et al.
Published: (2024) -
Forward Only Learning for Orthogonal Neural Networks of any Depth
by: Caillon, Paul, et al.
Published: (2025)