"meta-learning" Papers
50 papers found
Conference
A Meta-Learning Approach to Bayesian Causal Discovery
Anish Dhir, Matthew Ashman, James Requeima et al.
ConfigX: Modular Configuration for Evolutionary Algorithms via Multitask Reinforcement Learning
Hongshu Guo, Zeyuan Ma, Jiacheng Chen et al.
DataRater: Meta-Learned Dataset Curation
Dan Andrei Calian, Greg Farquhar, Iurii Kemaev et al.
Differentially Private Bilevel Optimization: Efficient Algorithms with Near-Optimal Rates
Andrew Lowy, Daogao Liu
Dimension Agnostic Neural Processes
Hyungi Lee, Chaeyun Jang, Dong Bok Lee et al.
Drug-TTA: Test-Time Adaptation for Drug Virtual Screening via Multi-task Meta-Auxiliary Learning
Ao Shen, Ming'zhi Yuan, Yingfan MA et al.
End-to-End Implicit Neural Representations for Classification
Alexander Gielisse, Jan van Gemert
Enhancing Online Reinforcement Learning with Meta-Learned Objective from Offline Data
Shilong Deng, Zetao Zheng, Hongcai He et al.
FAMNet: Frequency-aware Matching Network for Cross-domain Few-shot Medical Image Segmentation
Yuntian Bo, Yazhou Zhu, Lunbo Li et al.
Fast Rate Bounds for Multi-Task and Meta-Learning with Different Sample Sizes
Hossein Zakerinia, Christoph Lampert
Few-Shot Image Quality Assessment via Adaptation of Vision-Language Models
Xudong Li, Zihao Huang, Yan Zhang et al.
LiFT: Learning to Fine-Tune via Bayesian Parameter Efficient Meta Fine-Tuning
Minyoung Kim, Timothy Hospedales
Memory-Reduced Meta-Learning with Guaranteed Convergence
Honglin Yang, Ji Ma, Xiao Yu
MetaBox-v2: A Unified Benchmark Platform for Meta-Black-Box Optimization
Zeyuan Ma, Yue-Jiao Gong, Hongshu Guo et al.
Meta-Dynamical State Space Models for Integrative Neural Data Analysis
Ayesha Vermani, Josue Nassar, Hyungju Jeon et al.
MetaGS: A Meta-Learned Gaussian-Phong Model for Out-of-Distribution 3D Scene Relighting
Yumeng He, Yunbo Wang
MetaOOD: Automatic Selection of OOD Detection Models
Yuehan Qin, Yichi Zhang, Yi Nian et al.
MetaWriter: Personalized Handwritten Text Recognition Using Meta-Learned Prompt Tuning
Wenhao Gu, Li Gu, Ching Suen et al.
Personalized Dynamic Music Emotion Recognition with Dual-Scale Attention-Based Meta-Learning
Dengming Zhang, Weitao You, Ziheng Liu et al.
PersonalLLM: Tailoring LLMs to Individual Preferences
Thomas Zollo, Andrew Siah, Naimeng Ye et al.
PIED: Physics-Informed Experimental Design for Inverse Problems
Apivich Hemachandra, Gregory Kang Ruey Lau, See-Kiong Ng et al.
Provable Meta-Learning with Low-Rank Adaptations
Jacob Block, Sundararajan Srinivasan, Liam Collins et al.
Provably Efficient Multi-Task Meta Bandit Learning via Shared Representations
Jiabin Lin, Shana Moothedath
qNBO: quasi-Newton Meets Bilevel Optimization
Sheng Fang, Yongjin Liu, Wei Yao et al.
Task-Specific Preconditioner for Cross-Domain Few-Shot Learning
Suhyun Kang, Jungwon Park, Wonseok Lee et al.
Teaching Models to Improve on Tape
Liat Bezalel, Eyal Orgad, Amir Globerson
Test Time Scaling for Neural Processes
Hyungi Lee, Moonseok Choi, Hyunsu Kim et al.
Understanding Prompt Tuning and In-Context Learning via Meta-Learning
Tim Genewein, Kevin Li, Jordi Grau-Moya et al.
Why In-Context Learning Models are Good Few-Shot Learners?
Shiguang Wu, Yaqing Wang, Quanming Yao
Adaptive FSS: A Novel Few-Shot Segmentation Framework via Prototype Enhancement
Jing Wang, Jiangyun Li, Chen Chen et al.
A Nearly Optimal Single Loop Algorithm for Stochastic Bilevel Optimization under Unbounded Smoothness
Xiaochuan Gong, Jie Hao, Mingrui Liu
Exploring Active Learning in Meta-Learning: Enhancing Context Set Labeling
Wonho Bae, Jing Wang, Danica J. Sutherland
Few-Shot Character Understanding in Movies as an Assessment to Meta-Learning of Theory-of-Mind
Mo Yu, Qiujing Wang, Shunchi Zhang et al.
Few-Shot Learning from Augmented Label-Uncertain Queries in Bongard-HOI
Qinqian Lei, Bo Wang, Robby T. Tan
Fine-Grained Prototypes Distillation for Few-Shot Object Detection
Zichen Wang, Bo Yang, Haonan Yue et al.
Human-like Category Learning by Injecting Ecological Priors from Large Language Models into Neural Networks
Akshay Kumar Jagadish, Julian Coda-Forno, Mirko Thalmann et al.
Improving Generalization in Offline Reinforcement Learning via Adversarial Data Splitting
Da Wang, Lin Li, Wei Wei et al.
Learning Low-dimensional Latent Dynamics from High-dimensional Observations: Non-asymptotics and Lower Bounds
Yuyang Zhang, Shahriar Talebi, Na Li
Learning Modality Knowledge Alignment for Cross-Modality Transfer
Wenxuan Ma, Shuang Li, Lincan Cai et al.
Learning to Continually Learn with the Bayesian Principle
Soochan Lee, Hyeonseong Jeon, Jaehyeon Son et al.
Learning to Obstruct Few-Shot Image Classification over Restricted Classes
Amber Yijia Zheng, Chiao-An Yang, Raymond Yeh
Learning Universal Predictors
Jordi Grau-Moya, Tim Genewein, Marcus Hutter et al.
MALIBO: Meta-learning for Likelihood-free Bayesian Optimization
Jiarong Pan, Stefan Falkner, Felix Berkenkamp et al.
Memory Efficient Neural Processes via Constant Memory Attention Block
Leo Feng, Frederick Tung, Hossein Hajimirsadeghi et al.
MetaDiff: Meta-Learning with Conditional Diffusion for Few-Shot Learning
Baoquan Zhang, Chuyao Luo, Demin Yu et al.
Meta Evidential Transformer for Few-Shot Open-Set Recognition
Hitesh Sapkota, Krishna Neupane, Qi Yu
Nonsmooth Implicit Differentiation: Deterministic and Stochastic Convergence Rates
Riccardo Grazzi, Massimiliano Pontil, Saverio Salzo
One Meta-tuned Transformer is What You Need for Few-shot Learning
Xu Yang, Huaxiu Yao, Ying WEI
Test-Time Domain Adaptation by Learning Domain-Aware Batch Normalization
Yanan Wu, Zhixiang Chi, Yang Wang et al.
Test-Time Personalization with Meta Prompt for Gaze Estimation
Huan Liu, Julia Qi, Zhenhao Li et al.