Copertina

FIRAL: An Active Learning Algorithm for Multinomial Logistic Regression

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Chen, Youguang, Biros, George
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Computer Vision and Pattern Recognition
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

A Scalable Algorithm for Active Learning
di: Chen, Youguang, et al.
Pubblicazione: (2024)

Proximal-IMH: Proximal Posterior Proposals for Independent Metropolis-Hastings with Approximate Operators
di: Chen, Youguang, et al.
Pubblicazione: (2026)

Latent-IMH: Efficient Bayesian Inference for Inverse Problems with Approximate Operators
di: Chen, Youguang, et al.
Pubblicazione: (2026)

Privacy-Preserving CNN Training with Transfer Learning: Multiclass Logistic Regression
di: Chiang, John
Pubblicazione: (2023)

DICE: Discrete Inversion Enabling Controllable Editing for Multinomial Diffusion and Masked Generative Models
di: He, Xiaoxiao, et al.
Pubblicazione: (2024)

Contrastive Learning for Regression on Hyperspectral Data
di: Dhaini, Mohamad, et al.
Pubblicazione: (2024)

Deep Regression Representation Learning with Topology
di: Zhang, Shihao, et al.
Pubblicazione: (2024)

Extensions of the regret-minimization algorithm for optimal design
di: Chen, Youguang, et al.
Pubblicazione: (2025)

Revisiting Unknowns: Towards Effective and Efficient Open-Set Active Learning
di: Zong, Chen-Chen, et al.
Pubblicazione: (2026)

Disjoint Contrastive Regression Learning for Multi-Sourced Annotations
di: Ruan, Xiaoqian, et al.
Pubblicazione: (2021)

Superposition through Active Learning lens
di: Devkar, Akanksha
Pubblicazione: (2024)

Active Learning with a Noisy Annotator
di: Shafir, Netta, et al.
Pubblicazione: (2025)

Conformal Cross-Modal Active Learning
di: Nguyen, Huy Hoang, et al.
Pubblicazione: (2026)

COD: Learning Conditional Invariant Representation for Domain Adaptation Regression
di: Yang, Hao-Ran, et al.
Pubblicazione: (2024)

Spectral-Spatial Contrastive Learning Framework for Regression on Hyperspectral Data
di: Dhaini, Mohamad, et al.
Pubblicazione: (2026)

Active Learning for Multi-class Image Classification
di: Vo, Thien Nhan
Pubblicazione: (2025)

Plug and Play Active Learning for Object Detection
di: Yang, Chenhongyi, et al.
Pubblicazione: (2022)

Improved Algorithm for Deep Active Learning under Imbalance via Optimal Separation
di: Nuggehalli, Shyam, et al.
Pubblicazione: (2023)

ActiveAnno3D -- An Active Learning Framework for Multi-Modal 3D Object Detection
di: Ghita, Ahmed, et al.
Pubblicazione: (2024)

Revisiting Active Learning in the Era of Vision Foundation Models
di: Gupte, Sanket Rajan, et al.
Pubblicazione: (2024)

ALScope: A Unified Toolkit for Deep Active Learning
di: Wu, Chenkai, et al.
Pubblicazione: (2025)

Performance-guided Reinforced Active Learning for Object Detection
di: Liang, Zhixuan, et al.
Pubblicazione: (2026)

Instance-wise Supervision-level Optimization in Active Learning
di: Matsuo, Shinnosuke, et al.
Pubblicazione: (2025)

Map-Relative Pose Regression for Visual Re-Localization
di: Chen, Shuai, et al.
Pubblicazione: (2024)

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation
di: Vepa, Arvind Murari, et al.
Pubblicazione: (2024)

ADROIT: A Self-Supervised Framework for Learning Robust Representations for Active Learning
di: Banerjee, Soumya, et al.
Pubblicazione: (2025)

Improving a Hybrid Graphsage Deep Network for Automatic Multi-objective Logistics Management in Supply Chain
di: Khaleghi, Mehdi, et al.
Pubblicazione: (2025)

Uncertainty Driven Active Learning for Image Segmentation in Underwater Inspection
di: Marnet, Luiza Ribeiro, et al.
Pubblicazione: (2024)

Targeting Negative Flips in Active Learning using Validation Sets
di: Benkert, Ryan, et al.
Pubblicazione: (2024)

Cross-modal Active Complementary Learning with Self-refining Correspondence
di: Qin, Yang, et al.
Pubblicazione: (2023)

Joint Out-of-Distribution Filtering and Data Discovery Active Learning
di: Schmidt, Sebastian, et al.
Pubblicazione: (2025)

Energy-Based Open-Set Active Learning for Object Classification
di: Lyu, Zongyao, et al.
Pubblicazione: (2026)

Enhancing Cost Efficiency in Active Learning with Candidate Set Query
di: Gwon, Yeho, et al.
Pubblicazione: (2025)

Enhancing Active Learning for Sentinel 2 Imagery through Contrastive Learning and Uncertainty Estimation
di: Pogorzelski, David, et al.
Pubblicazione: (2024)

Calibration of Ordinal Regression Networks
di: Kim, Daehwan, et al.
Pubblicazione: (2024)

Aligning Data Selection with Performance: Performance-driven Reinforcement Learning for Active Learning in Object Detection
di: Liang, Zhixuan, et al.
Pubblicazione: (2023)

REBEL: Reinforcement Learning via Regressing Relative Rewards
di: Gao, Zhaolin, et al.
Pubblicazione: (2024)

Semi-Supervised Variational Adversarial Active Learning via Learning to Rank and Agreement-Based Pseudo Labeling
di: Lyu, Zongyao, et al.
Pubblicazione: (2024)

Gender Fairness of Machine Learning Algorithms for Pain Detection
di: Green, Dylan, et al.
Pubblicazione: (2025)

Federated Active Learning Framework for Efficient Annotation Strategy in Skin-lesion Classification
di: Deng, Zhipeng, et al.
Pubblicazione: (2024)