Poster "meta-learning" Papers
22 papers found
Differentially Private Bilevel Optimization: Efficient Algorithms with Near-Optimal Rates
Andrew Lowy, Daogao Liu
End-to-End Implicit Neural Representations for Classification
Alexander Gielisse, Jan van Gemert
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
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.
MetaOOD: Automatic Selection of OOD Detection Models
Yuehan Qin, Yichi Zhang, Yi Nian 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.
Why In-Context Learning Models are Good Few-Shot Learners?
Shiguang Wu, Yaqing Wang, Quanming Yao
A Nearly Optimal Single Loop Algorithm for Stochastic Bilevel Optimization under Unbounded Smoothness
Xiaochuan Gong, Jie Hao, Mingrui Liu
Few-Shot Character Understanding in Movies as an Assessment to Meta-Learning of Theory-of-Mind
Mo Yu, Qiujing Wang, Shunchi Zhang 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 Universal Predictors
Jordi Grau-Moya, Tim Genewein, Marcus Hutter et al.
Memory Efficient Neural Processes via Constant Memory Attention Block
Leo Feng, Frederick Tung, Hossein Hajimirsadeghi 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