2024 "active learning" Papers

Active Generation for Image Classification

Tao Huang, Jiaqi Liu, Shan You et al.

Active Learning Guided by Efficient Surrogate Learners

Yunpyo An, Suyeong Park, Kwang In Kim

Active Preference Learning for Large Language Models

William Muldrew, Peter Hayes, Mingtian Zhang et al.

Active Statistical Inference

Tijana Zrnic, Emmanuel J Candes

A Unified Framework for Learning with Nonlinear Model Classes from Arbitrary Linear Samples

Ben Adcock, Juan Cardenas, Nick Dexter

Bidirectional Uncertainty-Based Active Learning for Open-Set Annotation

ChenChen Zong, Ye-Wen Wang, Kun-Peng Ning et al.

Conditional Normalizing Flows for Active Learning of Coarse-Grained Molecular Representations

Henrik Schopmans, Pascal Friederich

Conformal Validity Guarantees Exist for Any Data Distribution (and How to Find Them)

Drew Prinster, Samuel Stanton, Anqi Liu et al.

Deletion-Anticipative Data Selection with a Limited Budget

Rachael Hwee Ling Sim, Jue Fan, Xiao Tian et al.

Domain-wise Data Acquisition to Improve Performance under Distribution Shift

Yue He, Dongbai Li, Pengfei Tian et al.

Efficient Active Domain Adaptation for Semantic Segmentation by Selecting Information-rich Superpixels

Yuan Gao, Zilei Wang, Yixin Zhang et al.

Entropic Open-Set Active Learning

Bardia Safaei, Vibashan VS, Celso de Melo et al.

Exploring Active Learning in Meta-Learning: Enhancing Context Set Labeling

Wonho Bae, Jing Wang, Danica J. Sutherland

Generative Active Learning for Long-tailed Instance Segmentation

Muzhi Zhu, Chengxiang Fan, Hao Chen et al.

Hyperbolic Active Learning for Semantic Segmentation under Domain Shift

Luca Franco, Paolo Mandica, Konstantinos Kallidromitis et al.

Inconsistency-Based Data-Centric Active Open-Set Annotation

Ruiyu Mao, Ouyang Xu, Yunhui Guo

Knowledge-aware Reinforced Language Models for Protein Directed Evolution

Yuhao Wang, Qiang Zhang, Ming Qin et al.

Learn from the Learnt: Source-Free Active Domain Adaptation via Contrastive Sampling and Visual Persistence

Mengyao Lyu, Tianxiang Hao, Xinhao Xu et al.

Neural Active Learning Beyond Bandits

Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI

Theodore Papamarkou, Maria Skoularidou, Konstantina Palla et al.

Provably Neural Active Learning Succeeds via Prioritizing Perplexing Samples

Dake Bu, Wei Huang, Taiji Suzuki et al.

The Non-linear $F$-Design and Applications to Interactive Learning

Alekh Agarwal, Jian Qian, Alexander Rakhlin et al.

Training Greedy Policy for Proposal Batch Selection in Expensive Multi-Objective Combinatorial Optimization

Deokjae Lee, Hyun Oh Song, Kyunghyun Cho

Two-Stage Active Learning for Efficient Temporal Action Segmentation

Yuhao Su, Ehsan Elhamifar

Uncertainty for Active Learning on Graphs

Dominik Fuchsgruber, Tom Wollschläger, Bertrand Charpentier et al.