Saved in:
| Main Authors: | Hu, Rui, Zhang, Yifan, Li, Zhuoran, Huang, Longbo |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2410.02596 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Beyond the Proxy: Trajectory-Distilled Guidance for Offline GFlowNet Training
by: Chen, Ruishuo, et al.
Published: (2025)
by: Chen, Ruishuo, et al.
Published: (2025)
Reparameterization Flow Policy Optimization
by: Zhong, Hai, et al.
Published: (2026)
by: Zhong, Hai, et al.
Published: (2026)
PowerFlow: Unlocking the Dual Nature of LLMs via Principled Distribution Matching
by: Chen, Ruishuo, et al.
Published: (2026)
by: Chen, Ruishuo, et al.
Published: (2026)
Beyond Shallow Behavior: Task-Efficient Value-Based Multi-Task Offline MARL via Skill Discovery
by: Wang, Xun, et al.
Published: (2025)
by: Wang, Xun, et al.
Published: (2025)
OM2P: Offline Multi-Agent Mean-Flow Policy
by: Li, Zhuoran, et al.
Published: (2025)
by: Li, Zhuoran, et al.
Published: (2025)
Reparameterization Proximal Policy Optimization
by: Zhong, Hai, et al.
Published: (2025)
by: Zhong, Hai, et al.
Published: (2025)
Finite-time Convergence Analysis of Actor-Critic with Evolving Reward
by: Hu, Rui, et al.
Published: (2025)
by: Hu, Rui, et al.
Published: (2025)
Z-Error Loss for Training Neural Networks
by: Godin, Guillaume
Published: (2025)
by: Godin, Guillaume
Published: (2025)
Network Topology Optimization via Deep Reinforcement Learning
by: Li, Zhuoran, et al.
Published: (2022)
by: Li, Zhuoran, et al.
Published: (2022)
Real-Time Parallel Counterfactual Regret Minimization
by: Li, Boning, et al.
Published: (2026)
by: Li, Boning, et al.
Published: (2026)
Layer-Aware Influence for Online Data Valuation Estimation
by: Yang, Ziao, et al.
Published: (2025)
by: Yang, Ziao, et al.
Published: (2025)
Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning
by: Yang, Puning, et al.
Published: (2025)
by: Yang, Puning, et al.
Published: (2025)
Reward Learning through Ranking Mean Squared Error
by: Kharyal, Chaitanya, et al.
Published: (2026)
by: Kharyal, Chaitanya, et al.
Published: (2026)
Value-Based Deep Multi-Agent Reinforcement Learning with Dynamic Sparse Training
by: Hu, Pihe, et al.
Published: (2024)
by: Hu, Pihe, et al.
Published: (2024)
SoftSignSGD(S3): An Enhanced Optimizer for Practical DNN Training and Loss Spikes Minimization Beyond Adam
by: Peng, Hanyang, et al.
Published: (2025)
by: Peng, Hanyang, et al.
Published: (2025)
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)
Training and Evaluating Language Models with Template-based Data Generation
by: Zhang, Yifan
Published: (2024)
by: Zhang, Yifan
Published: (2024)
Enhancing Trustworthiness of Graph Neural Networks with Rank-Based Conformal Training
by: Wang, Ting, et al.
Published: (2025)
by: Wang, Ting, et al.
Published: (2025)
How to Square Tensor Networks and Circuits Without Squaring Them
by: Loconte, Lorenzo, et al.
Published: (2025)
by: Loconte, Lorenzo, et al.
Published: (2025)
MemLoss: Enhancing Adversarial Training with Recycling Adversarial Examples
by: Mahdi, Soroush, et al.
Published: (2025)
by: Mahdi, Soroush, et al.
Published: (2025)
Exploring Loss Design Techniques For Decision Tree Robustness To Label Noise
by: Sztukiewicz, Lukasz, et al.
Published: (2024)
by: Sztukiewicz, Lukasz, et al.
Published: (2024)
Adversarial Training for Robust Coverage Network under Worst-case Facility Losses
by: Miao, Changhao, et al.
Published: (2026)
by: Miao, Changhao, et al.
Published: (2026)
Hybrid Attribution Priors for Explainable and Robust Model Training
by: Zhang, Zhuoran, et al.
Published: (2025)
by: Zhang, Zhuoran, et al.
Published: (2025)
Algebraic Approach to Ridge-Regularized Mean Squared Error Minimization in Minimal ReLU Neural Network
by: Fukasaku, Ryoya, et al.
Published: (2025)
by: Fukasaku, Ryoya, et al.
Published: (2025)
Rethinking the Design Space of Reinforcement Learning for Diffusion Models: On the Importance of Likelihood Estimation Beyond Loss Design
by: Choi, Jaemoo, et al.
Published: (2026)
by: Choi, Jaemoo, et al.
Published: (2026)
Beyond Backpropagation: Exploring Innovative Algorithms for Energy-Efficient Deep Neural Network Training
by: Spyra, Przemysław
Published: (2025)
by: Spyra, Przemysław
Published: (2025)
Exploring Physics-Informed Neural Networks for Crop Yield Loss Forecasting
by: Miranda, Miro, et al.
Published: (2024)
by: Miranda, Miro, et al.
Published: (2024)
FlowTS: Time Series Generation via Rectified Flow
by: Hu, Yang, et al.
Published: (2024)
by: Hu, Yang, et al.
Published: (2024)
Learning to be Reproducible: Custom Loss Design for Robust Neural Networks
by: Ahmed, Waqas, et al.
Published: (2026)
by: Ahmed, Waqas, et al.
Published: (2026)
FSX: Message Flow Sensitivity Enhanced Structural Explainer for Graph Neural Networks
by: Feng, Bizu, et al.
Published: (2026)
by: Feng, Bizu, et al.
Published: (2026)
Training with Confidence: Catching Silent Errors in Deep Learning Training with Automated Proactive Checks
by: Jiang, Yuxuan, et al.
Published: (2025)
by: Jiang, Yuxuan, et al.
Published: (2025)
Beyond Losses Reweighting: Empowering Multi-Task Learning via the Generalization Perspective
by: Phan, Hoang, et al.
Published: (2022)
by: Phan, Hoang, et al.
Published: (2022)
Fast Adversarial Training against Sparse Attacks Requires Loss Smoothing
by: Zhong, Xuyang, et al.
Published: (2025)
by: Zhong, Xuyang, et al.
Published: (2025)
Loop Corrections to the Training Error and Generalization Gap of Random Feature Models
by: Kim, Taeyoung
Published: (2026)
by: Kim, Taeyoung
Published: (2026)
Beyond Efficiency: Molecular Data Pruning for Enhanced Generalization
by: Chen, Dingshuo, et al.
Published: (2024)
by: Chen, Dingshuo, et al.
Published: (2024)
Enhancing Deep Learning with Optimized Gradient Descent: Bridging Numerical Methods and Neural Network Training
by: Ma, Yuhan, et al.
Published: (2024)
by: Ma, Yuhan, et al.
Published: (2024)
Beyond Correctness: Harmonizing Process and Outcome Rewards through RL Training
by: Ye, Chenlu, et al.
Published: (2025)
by: Ye, Chenlu, et al.
Published: (2025)
General Proximal Flow Networks
by: Strunk, Alexander, et al.
Published: (2026)
by: Strunk, Alexander, et al.
Published: (2026)
The Sample Complexity of Online Strategic Decision Making with Information Asymmetry and Knowledge Transportability
by: Hu, Jiachen, et al.
Published: (2025)
by: Hu, Jiachen, et al.
Published: (2025)
Offline-to-Online Multi-Agent Reinforcement Learning with Offline Value Function Memory and Sequential Exploration
by: Zhong, Hai, et al.
Published: (2024)
by: Zhong, Hai, et al.
Published: (2024)
Similar Items
-
Beyond the Proxy: Trajectory-Distilled Guidance for Offline GFlowNet Training
by: Chen, Ruishuo, et al.
Published: (2025) -
Reparameterization Flow Policy Optimization
by: Zhong, Hai, et al.
Published: (2026) -
PowerFlow: Unlocking the Dual Nature of LLMs via Principled Distribution Matching
by: Chen, Ruishuo, et al.
Published: (2026) -
Beyond Shallow Behavior: Task-Efficient Value-Based Multi-Task Offline MARL via Skill Discovery
by: Wang, Xun, et al.
Published: (2025) -
OM2P: Offline Multi-Agent Mean-Flow Policy
by: Li, Zhuoran, et al.
Published: (2025)