"active learning" Papers
53 papers found • Page 1 of 2
Conference
Active Seriation: Efficient Ordering Recovery with Statistical Guarantees
James Cheshire, Yann Issartel
Active Symbolic Discovery of Ordinary Differential Equations via Phase Portrait Sketching
Nan Jiang, Md Nasim, Yexiang Xue
Active Test-time Vision-Language Navigation
Heeju Ko, Sung June Kim, Gyeongrok Oh et al.
AutoSciLab: A Self-Driving Laboratory for Interpretable Scientific Discovery
Saaketh Desai, Sadhvikas Addamane, Jeffrey Y. Tsao et al.
Diffusion-Driven Two-Stage Active Learning for Low-Budget Semantic Segmentation
Jeongin Kim, Wonho Bae, YouLee Han et al.
Efficient Active Imitation Learning with Random Network Distillation
Emilien Biré, Anthony Kobanda, Ludovic Denoyer et al.
Efficient Biological Data Acquisition through Inference Set Design
Ihor Neporozhnii, Julien Roy, Emmanuel Bengio et al.
Enhancing Deep Batch Active Learning for Regression with Imperfect Data Guided Selection
Yinjie Min, Furong Xu, Xinyao Li et al.
Epistemic Uncertainty Estimation in Regression Ensemble Models with Pairwise Epistemic Estimators
Lucas Berry, David Meger
Formal Models of Active Learning from Contrastive Examples
Farnam Mansouri, Hans Simon, Adish Singla et al.
Generalized Top-k Mallows Model for Ranked Choices
Shahrzad Haddadan, Sara Ahmadian
Informed Initialization for Bayesian Optimization and Active Learning
Carl Hvarfner, David Eriksson, Eytan Bakshy et al.
Joint Out-of-Distribution Filtering and Data Discovery Active Learning
Sebastian Schmidt, Leonard Schenk, Leo Schwinn et al.
LICORICE: Label-Efficient Concept-Based Interpretable Reinforcement Learning
Zhuorui Ye, Stephanie Milani, Geoff Gordon et al.
MolParser: End-to-end Visual Recognition of Molecule Structures in the Wild
Xi Fang, Jiankun Wang, Xiaochen Cai et al.
Program Synthesis via Test-Time Transduction
Kang-il Lee, Jahyun Koo, Seunghyun Yoon et al.
ProSpero: Active Learning for Robust Protein Design Beyond Wild-Type Neighborhoods
Michal Kmicikiewicz, Vincent Fortuin, Ewa Szczurek
Reinforced Active Learning for Large-Scale Virtual Screening with Learnable Policy Model
Yicong Chen, Jiahua Rao, Jiancong Xie et al.
Robust Regression of General ReLUs with Queries
Ilias Diakonikolas, Daniel Kane, Mingchen Ma
Sharpe Ratio-Guided Active Learning for Preference Optimization in RLHF
Syrine Belakaria, Joshua Kazdan, Charles Marx et al.
Structural-Entropy-Based Sample Selection for Efficient and Effective Learning
Tianchi Xie, Jiangning Zhu, Guozu Ma et al.
The Catechol Benchmark: Time-series Solvent Selection Data for Few-shot Machine Learning
Toby Boyne, Juan Campos, Rebecca Langdon et al.
Towards Cost-Effective Learning: A Synergy of Semi-Supervised and Active Learning
Tianxiang Yin, Ningzhong Liu, Han Sun
Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations
Richard Bergna, Sergio Calvo Ordoñez, Felix Opolka et al.
Active Coarse-to-Fine Segmentation of Moveable Parts from Real Images
Ruiqi Wang, Akshay Gadi Patil, Fenggen Yu et al.
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
Bad Students Make Great Teachers: Active Learning Accelerates Large-Scale Visual Understanding
Talfan Evans, Shreya Pathak, Hamza Merzic et al.
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.
Epistemic Uncertainty Quantification For Pre-Trained Neural Networks
Hanjing Wang, Qiang Ji
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
Yikun Ban, Ishika Agarwal, Ziwei Wu et al.
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.
Think Twice Before Selection: Federated Evidential Active Learning for Medical Image Analysis with Domain Shifts
Jiayi Chen, Benteng Ma, Hengfei Cui et al.