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Learning Paradigms

14,108 papers (9 classified directly here)

Subtopics

Transfer Learning (8,166) Few-Shot Learning (2,562) Meta-Learning (1,529) Federated Learning (1,360) Zero-Shot Learning (867) Multi-Task Learning (135) Continual Learning (118) Domain Adaptation (117) Self-Supervised Learning (100) Active Learning (75) Semi-Supervised Learning (41) Unsupervised Learning (26) In-Context Learning (19) Weakly Supervised Learning (11) Domain Generalization (9)

Papers per year

4
19
58
1128
2227
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'15
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Papers (including subtopics)

Low-Rank Generalized Linear Bandit Problems AISTATS 2021
CADA: Communication-Adaptive Distributed Adam AISTATS 2021
Predictive Complexity Priors AISTATS 2021
Revisiting Model-Agnostic Private Learning: Faster Rates and Active Learning AISTATS 2021
Provable Hierarchical Imitation Learning via EM AISTATS 2021
Mean-Variance Analysis in Bayesian Optimization under Uncertainty AISTATS 2021
Noise Contrastive Meta-Learning for Conditional Density Estimation using Kernel Mean Embeddings AISTATS 2021
Latent Derivative Bayesian Last Layer Networks AISTATS 2021
On Data Efficiency of Meta-learning AISTATS 2021
Hyperparameter Transfer Learning with Adaptive Complexity AISTATS 2021
Amortized Bayesian Prototype Meta-learning: A New Probabilistic Meta-learning Approach to Few-shot Image Classification AISTATS 2021
A Variational Information Bottleneck Approach to Multi-Omics Data Integration AISTATS 2021
Collaborative Classification from Noisy Labels AISTATS 2021
Online probabilistic label trees AISTATS 2021
Free-rider Attacks on Model Aggregation in Federated Learning AISTATS 2021
No-regret Algorithms for Multi-task Bayesian Optimization AISTATS 2021
Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference AISTATS 2021
Federated f-Differential Privacy AISTATS 2021
Optimal query complexity for private sequential learning against eavesdropping AISTATS 2021
The Sample Complexity of Meta Sparse Regression AISTATS 2021
A Theory of Multiple-Source Adaptation with Limited Target Labeled Data AISTATS 2021
Federated Learning with Compression: Unified Analysis and Sharp Guarantees AISTATS 2021
Variational Selective Autoencoder: Learning from Partially-Observed Heterogeneous Data AISTATS 2021
Shuffled Model of Differential Privacy in Federated Learning AISTATS 2021
Convergence and Accuracy Trade-Offs in Federated Learning and Meta-Learning AISTATS 2021