Rényi Divergence Deep Mutual Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Huang, Weipeng, Tao, Junjie, Deng, Changbo, Fan, Ming, Wan, Wenqiang, Xiong, Qi, Piao, Guangyuan |
|---|---|
| Format: | Preprint |
| Published: |
2022
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Correcting Noisy Multilabel Predictions: Modeling Label Noise through Latent Space Shifts
by: Huang, Weipeng, et al.
Published: (2025)
by: Huang, Weipeng, et al.
Published: (2025)
Enhancing Text-Based Hierarchical Multilabel Classification for Mobile Applications via Contrastive Learning
by: Guo, Jiawei, et al.
Published: (2025)
by: Guo, Jiawei, et al.
Published: (2025)
Mutual-Taught for Co-adapting Policy and Reward Models
by: Shi, Tianyuan, et al.
Published: (2025)
by: Shi, Tianyuan, et al.
Published: (2025)
Scalable Hyperparameter-Divergent Ensemble Training with Automatic Learning Rate Exploration for Large Models
by: Cheng, Hailing, et al.
Published: (2026)
by: Cheng, Hailing, et al.
Published: (2026)
Generalized Cauchy-Schwarz Divergence and Its Deep Learning Applications
by: Lu, Mingfei, et al.
Published: (2024)
by: Lu, Mingfei, et al.
Published: (2024)
Learning Divergence Fields for Shift-Robust Graph Representations
by: Wu, Qitian, et al.
Published: (2024)
by: Wu, Qitian, et al.
Published: (2024)
A Unified Framework for Rethinking Policy Divergence Measures in GRPO
by: Wu, Qingyuan, et al.
Published: (2026)
by: Wu, Qingyuan, et al.
Published: (2026)
Divergence-Augmented Policy Optimization
by: Wang, Qing, et al.
Published: (2025)
by: Wang, Qing, et al.
Published: (2025)
DN-CL: Deep Symbolic Regression against Noise via Contrastive Learning
by: Liu, Jingyi, et al.
Published: (2024)
by: Liu, Jingyi, et al.
Published: (2024)
Rényi Neural Processes
by: Wang, Xuesong, et al.
Published: (2024)
by: Wang, Xuesong, et al.
Published: (2024)
Learning to Compress Graphs via Dual Agents for Consistent Topological Robustness Evaluation
by: Chai, Qisen, et al.
Published: (2025)
by: Chai, Qisen, et al.
Published: (2025)
Advancing Loss Functions in Recommender Systems: A Comparative Study with a Rényi Divergence-Based Solution
by: Zhang, Shengjia, et al.
Published: (2025)
by: Zhang, Shengjia, et al.
Published: (2025)
$α$-GAN by Rényi Cross Entropy
by: Ding, Ni, et al.
Published: (2025)
by: Ding, Ni, et al.
Published: (2025)
Federated Learning Framework via Distributed Mutual Learning
by: Gupta, Yash
Published: (2025)
by: Gupta, Yash
Published: (2025)
A Survey on Deep Learning based Time Series Analysis with Frequency Transformation
by: Yi, Kun, et al.
Published: (2023)
by: Yi, Kun, et al.
Published: (2023)
RiemannGL: Riemannian Geometry Changes Graph Deep Learning
by: Sun, Li, et al.
Published: (2026)
by: Sun, Li, et al.
Published: (2026)
Mutual Information Regularized Offline Reinforcement Learning
by: Ma, Xiao, et al.
Published: (2022)
by: Ma, Xiao, et al.
Published: (2022)
Diverse Policies Recovering via Pointwise Mutual Information Weighted Imitation Learning
by: Yang, Hanlin, et al.
Published: (2024)
by: Yang, Hanlin, et al.
Published: (2024)
Spatio-temporal Causal Learning for Streamflow Forecasting
by: Wan, Shu, et al.
Published: (2024)
by: Wan, Shu, et al.
Published: (2024)
Deep Frequency Derivative Learning for Non-stationary Time Series Forecasting
by: Fan, Wei, et al.
Published: (2024)
by: Fan, Wei, et al.
Published: (2024)
Dissecting Deep RL with High Update Ratios: Combatting Value Divergence
by: Hussing, Marcel, et al.
Published: (2024)
by: Hussing, Marcel, et al.
Published: (2024)
Bridging the Gap Between Bayesian Deep Learning and Ensemble Weather Forecasts
by: Xiong, Xinlei, et al.
Published: (2025)
by: Xiong, Xinlei, et al.
Published: (2025)
Quantum-Boosted High-Fidelity Deep Learning
by: Wang, Feng-ao, et al.
Published: (2025)
by: Wang, Feng-ao, et al.
Published: (2025)
Towards Generalizable PDE Dynamics Forecasting via Physics-Guided Invariant Learning
by: Li, Siyang, et al.
Published: (2025)
by: Li, Siyang, et al.
Published: (2025)
Robust Multi-Agent Reinforcement Learning by Mutual Information Regularization
by: Li, Simin, et al.
Published: (2023)
by: Li, Simin, et al.
Published: (2023)
Bidirectional-Reachable Hierarchical Reinforcement Learning with Mutually Responsive Policies
by: Luo, Yu, et al.
Published: (2024)
by: Luo, Yu, et al.
Published: (2024)
DeepAFL: Deep Analytic Federated Learning
by: Tang, Jianheng, et al.
Published: (2026)
by: Tang, Jianheng, et al.
Published: (2026)
Representation Convergence: Mutual Distillation is Secretly a Form of Regularization
by: Xie, Zhengpeng, et al.
Published: (2025)
by: Xie, Zhengpeng, et al.
Published: (2025)
From Challenges and Pitfalls to Recommendations and Opportunities: Implementing Federated Learning in Healthcare
by: Li, Ming, et al.
Published: (2024)
by: Li, Ming, et al.
Published: (2024)
MOLE: MOdular Learning FramEwork via Mutual Information Maximization
by: Li, Tianchao, et al.
Published: (2023)
by: Li, Tianchao, et al.
Published: (2023)
Deep Reinforcement Learning for Artificial Upwelling Energy Management
by: Zhang, Yiyuan, et al.
Published: (2023)
by: Zhang, Yiyuan, et al.
Published: (2023)
Conjugate Learning Theory: Uncovering the Mechanisms of Trainability and Generalization in Deep Neural Networks
by: Qi, Binchuan
Published: (2026)
by: Qi, Binchuan
Published: (2026)
Rapid Word Learning Through Meta In-Context Learning
by: Wang, Wentao, et al.
Published: (2025)
by: Wang, Wentao, et al.
Published: (2025)
The Choice of Divergence: A Neglected Key to Mitigating Diversity Collapse in Reinforcement Learning with Verifiable Reward
by: Li, Long, et al.
Published: (2025)
by: Li, Long, et al.
Published: (2025)
Adaptive Divergence Regularized Policy Optimization for Fine-tuning Generative Models
by: Fan, Jiajun, et al.
Published: (2025)
by: Fan, Jiajun, et al.
Published: (2025)
ProtoNAM: Prototypical Neural Additive Models for Interpretable Deep Tabular Learning
by: Xiong, Guangzhi, et al.
Published: (2024)
by: Xiong, Guangzhi, et al.
Published: (2024)
Towards Understanding the Optimization Mechanisms in Deep Learning
by: Qi, Binchuan, et al.
Published: (2025)
by: Qi, Binchuan, et al.
Published: (2025)
Deep Causal Learning: Representation, Discovery and Inference
by: Deng, Zizhen, et al.
Published: (2022)
by: Deng, Zizhen, et al.
Published: (2022)
Mutual Information Tracks Policy Coherence in Reinforcement Learning
by: Reid, Cameron, et al.
Published: (2025)
by: Reid, Cameron, et al.
Published: (2025)
Reinforcement Learning in hyperbolic space for multi-step reasoning
by: Xu, Tao, et al.
Published: (2025)
by: Xu, Tao, et al.
Published: (2025)
Similar Items
-
Correcting Noisy Multilabel Predictions: Modeling Label Noise through Latent Space Shifts
by: Huang, Weipeng, et al.
Published: (2025) -
Enhancing Text-Based Hierarchical Multilabel Classification for Mobile Applications via Contrastive Learning
by: Guo, Jiawei, et al.
Published: (2025) -
Mutual-Taught for Co-adapting Policy and Reward Models
by: Shi, Tianyuan, et al.
Published: (2025) -
Scalable Hyperparameter-Divergent Ensemble Training with Automatic Learning Rate Exploration for Large Models
by: Cheng, Hailing, et al.
Published: (2026) -
Generalized Cauchy-Schwarz Divergence and Its Deep Learning Applications
by: Lu, Mingfei, et al.
Published: (2024)