Imagen de Portada

Employing Layerwised Unsupervised Learning to Lessen Data and Loss Requirements in Forward-Forward Algorithms

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Hwang, Taewook, Seo, Hyein, Jung, Sangkeun
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Novel Saliency Analysis for the Forward Forward Algorithm
por: Bakhshi, Mitra
Publicado: (2024)

FEAT: A Preference Feedback Dataset through a Cost-Effective Auto-Generation and Labeling Framework for English AI Tutoring
por: Seo, Hyein, et al.
Publicado: (2025)

Reshaping the Forward-Forward Algorithm with a Similarity-Based Objective
por: Gong, James, et al.
Publicado: (2025)

Learning Flexible Forward Trajectories for Masked Molecular Diffusion
por: Seo, Hyunjin, et al.
Publicado: (2025)

Convolutional Channel-wise Competitive Learning for the Forward-Forward Algorithm
por: Papachristodoulou, Andreas, et al.
Publicado: (2023)

Adaptive Multi-Scale Goodness Aggregation for Forward-Forward Learning
por: Beigzad, Salar, et al.
Publicado: (2026)

Forward Target Propagation: A Forward-Only Approach to Global Error Credit Assignment via Local Losses
por: As-Saquib, Nazmus Saadat, et al.
Publicado: (2025)

Hyperspherical Forward-Forward with Prototypical Representations
por: Sarode, Shalini, et al.
Publicado: (2026)

Backpropagation-free Spiking Neural Networks with the Forward-Forward Algorithm
por: Ghader, Mohammadnavid, et al.
Publicado: (2025)

FLOPS: Forward Learning with OPtimal Sampling
por: Ren, Tao, et al.
Publicado: (2024)

Self-Contrastive Forward-Forward Algorithm
por: Chen, Xing, et al.
Publicado: (2024)

Cumulative-Goodness Free-Riding in Forward-Forward Networks: Real, Repairable, but Not Accuracy-Dominant
por: Yousefiramandi, Amirhossein
Publicado: (2026)

Forward-Forward Learning achieves Highly Selective Latent Representations for Out-of-Distribution Detection in Fully Spiking Neural Networks
por: Terres-Escudero, Erik B., et al.
Publicado: (2024)

Exploring Domain Robust Lightweight Reward Models based on Router Mechanism
por: Namgoong, Hyuk, et al.
Publicado: (2024)

Moonwalk: Inverse-Forward Differentiation
por: Krylov, Dmitrii, et al.
Publicado: (2024)

Selectivity and Shape in the Design of Forward-Forward Goodness Functions
por: Akkus, Talha Ruzgar, et al.
Publicado: (2026)

Forward Only Learning for Orthogonal Neural Networks of any Depth
por: Caillon, Paul, et al.
Publicado: (2025)

On the Role of Transformer Feed-Forward Layers in Nonlinear In-Context Learning
por: Sun, Haoyuan, et al.
Publicado: (2025)

Rethinking Forward Processes for Score-Based Nonlinear Data Assimilation in High Dimensions
por: Yoon, Eunbi, et al.
Publicado: (2026)

Integrating Inverse and Forward Modeling for Sparse Temporal Data from Sensor Networks
por: Vexler, Julian, et al.
Publicado: (2025)

FLEX: Continuous Agent Evolution via Forward Learning from Experience
por: Cai, Zhicheng, et al.
Publicado: (2025)

Optimizing Dense Feed-Forward Neural Networks
por: Balderas, Luis, et al.
Publicado: (2023)

Unsupervised Episode Generation for Graph Meta-learning
por: Jung, Jihyeong, et al.
Publicado: (2023)

DFA-GNN: Forward Learning of Graph Neural Networks by Direct Feedback Alignment
por: Zhao, Gongpei, et al.
Publicado: (2024)

Beyond Backpropagation: Optimization with Multi-Tangent Forward Gradients
por: Flügel, Katharina, et al.
Publicado: (2024)

Using Forwards-Backwards Models to Approximate MDP Homomorphisms
por: Mavor-Parker, Augustine N., et al.
Publicado: (2022)

Continual Learning: Applications and the Road Forward
por: Verwimp, Eli, et al.
Publicado: (2023)

Reverse Forward Curriculum Learning for Extreme Sample and Demonstration Efficiency in Reinforcement Learning
por: Tao, Stone, et al.
Publicado: (2024)

Data Transformation Strategies to Remove Heterogeneity
por: Yoo, Sangbong, et al.
Publicado: (2025)

FedEFC: Federated Learning Using Enhanced Forward Correction Against Noisy Labels
por: Yu, Seunghun, et al.
Publicado: (2025)

Unsupervised Anomaly Detection for Tabular Data Using Noise Evaluation
por: Dai, Wei, et al.
Publicado: (2024)

Fast Forward: Accelerating LLM Prefill with Predictive FFN Sparsity
por: Gautam, Aayush, et al.
Publicado: (2026)

FwdLLM: Efficient FedLLM using Forward Gradient
por: Xu, Mengwei, et al.
Publicado: (2023)

Feed-Forward Optimization With Delayed Feedback for Neural Network Training
por: Flügel, Katharina, et al.
Publicado: (2023)

Optimizing Mastery Learning by Fast-Forwarding Over-Practice Steps
por: Xia, Meng, et al.
Publicado: (2025)

On Using Admissible Bounds for Learning Forward Search Heuristics
por: Núñez-Molina, Carlos, et al.
Publicado: (2023)

Bidirectional Soft Actor-Critic: Leveraging Forward and Reverse KL Divergence for Efficient Reinforcement Learning
por: Zhang, Yixian, et al.
Publicado: (2025)

Thinking Forward and Backward: Effective Backward Planning with Large Language Models
por: Ren, Allen Z., et al.
Publicado: (2024)

Prefix Grouper: Efficient GRPO Training through Shared-Prefix Forward
por: Liu, Zikang, et al.
Publicado: (2025)

Pushing Forward Pareto Frontiers of Proactive Agents with Behavioral Agentic Optimization
por: Yao, Yihang, et al.
Publicado: (2026)