Cover Image

Evidential Deep Active Learning for Semi-Supervised Classification

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhao, Shenkai, Zhang, Xinao, Pan, Lipeng, Xu, Xiaobin, Pelusi, Danilo
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence I.2.6
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Deep Memory Search: A Metaheuristic Approach for Optimizing Heuristic Search
by: Hedar, Abdel-Rahman, et al.
Published: (2024)

EEG Sleep Stage Classification with Continuous Wavelet Transform and Deep Learning
by: Gashti, Mehdi Zekriyapanah, et al.
Published: (2025)

Machine Learning vs Deep Learning: The Generalization Problem
by: Bay, Yong Yi, et al.
Published: (2024)

A Practical Approach to using Supervised Machine Learning Models to Classify Aviation Safety Occurrences
by: Siow, Bryan Y.
Published: (2025)

FreRA: A Frequency-Refined Augmentation for Contrastive Learning on Time Series Classification
by: Tian, Tian, et al.
Published: (2025)

Load and Renewable Energy Forecasting Using Deep Learning for Grid Stability
by: Sarkar, Kamal
Published: (2025)

Working Paper: Active Causal Structure Learning with Latent Variables: Towards Learning to Detour in Autonomous Robots
by: Riscos, Pablo de los, et al.
Published: (2024)

Low-Dimensional Execution Manifolds in Transformer Learning Dynamics: Evidence from Modular Arithmetic Tasks
by: Xu, Yongzhong
Published: (2026)

Enhancing Classification with Semi-Supervised Deep Learning Using Distance-Based Sample Weights
by: Abedinia, Aydin, et al.
Published: (2025)

DYNAMITE: Dynamic Interplay of Mini-Batch Size and Aggregation Frequency for Federated Learning with Static and Streaming Dataset
by: Liu, Weijie, et al.
Published: (2023)

TACO: Tackling Over-correction in Federated Learning with Tailored Adaptive Correction
by: Liu, Weijie, et al.
Published: (2025)

Path-Coupled Bellman Flows for Distributional Reinforcement Learning
by: Xu, Boyang, et al.
Published: (2026)

Lost or Hidden? A Concept-Level Forgetting in Supervised Continual Learning
by: Filus, Katarzyna, et al.
Published: (2026)

Autonomous Deep Agent
by: Yu, Amy, et al.
Published: (2025)

Hybrid-AIRL: Enhancing Inverse Reinforcement Learning with Supervised Expert Guidance
by: Silue, Bram, et al.
Published: (2025)

Extreme AutoML: Analysis of Classification, Regression, and NLP Performance
by: Ratner, Edward, et al.
Published: (2024)

What Do World Models Learn in RL? Probing Latent Representations in Learned Environment Simulators
by: Zhang, Xinyu
Published: (2026)

Shattered Compositionality: Counterintuitive Learning Dynamics of Transformers for Arithmetic
by: Zhao, Xingyu, et al.
Published: (2026)

Deep Residual Echo State Networks: exploring residual orthogonal connections in untrained Recurrent Neural Networks
by: Pinna, Matteo, et al.
Published: (2025)

TS-ACL: Closed-Form Solution for Time Series-oriented Continual Learning
by: Li, Jiaxu, et al.
Published: (2024)

Expressive Value Learning for Scalable Offline Reinforcement Learning
by: Espinosa-Dice, Nicolas, et al.
Published: (2025)

Deep Reinforcement Learning for Adverse Garage Scenario Generation
by: Li, Kai
Published: (2024)

Behavior Learning (BL): Learning Hierarchical Optimization Structures from Data
by: Ma, Zhenyao, et al.
Published: (2026)

An Axiomatic Approach to General Intelligence: SANC(E3) -- Self-organizing Active Network of Concepts with Energy E3
by: Kwon, Daesuk, et al.
Published: (2026)

Bounded Ratio Reinforcement Learning
by: Ao, Yunke, et al.
Published: (2026)

Why Online Reinforcement Learning is Causal
by: Schulte, Oliver, et al.
Published: (2024)

TIAR: Trajectory-Informed Advantage Reweighting for LLM Abstention Learning
by: Pan, Muyu, et al.
Published: (2026)

DataRater: Meta-Learned Dataset Curation
by: Calian, Dan A., et al.
Published: (2025)

Understanding Goal Generalisation in Sequential Reinforcement Learning
by: Brown, Jason Ross, et al.
Published: (2026)

Extrinsicaly Rewarded Soft Q Imitation Learning with Discriminator
by: Furuyama, Ryoma, et al.
Published: (2024)

A Simple Generalisation of the Implicit Dynamics of In-Context Learning
by: Innocenti, Francesco, et al.
Published: (2025)

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda
by: Narendra, Nanjangud C., et al.
Published: (2025)

Multi-Task Reinforcement Learning with Language-Encoded Gated Policy Networks
by: Arora, Rushiv
Published: (2025)

Learning Agents With Prioritization and Parameter Noise in Continuous State and Action Space
by: Mangannavar, Rajesh, et al.
Published: (2024)

What changes after deployment? A survey on On-device Learning in TinyML
by: Pavan, Massimo, et al.
Published: (2026)

FastGRPO: Accelerating Policy Optimization via Concurrency-aware Speculative Decoding and Online Draft Learning
by: Zhang, Yizhou, et al.
Published: (2025)

DELTA: Variational Disentangled Learning for Privacy-Preserving Data Reprogramming
by: Malarkkan, Arun Vignesh, et al.
Published: (2025)

Compositional Concept-Based Neuron-Level Interpretability for Deep Reinforcement Learning
by: Jiang, Zeyu, et al.
Published: (2025)

Causal Discovery in Semi-Stationary Time Series
by: Gao, Shanyun, et al.
Published: (2024)

QuIDE: Mastering the Quantized Intelligence Trade-off via Active Optimization
by: Jiang, Xiantao
Published: (2026)