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Learning Paradigms

2,054 papers (7 classified directly here)

Subtopics

Meta-Learning (973) Federated Learning (894) Curriculum Learning (202)

Papers per year

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Papers (including subtopics)

A Closer Look at the Training Strategy for Modern Meta-Learning NIPS 2020
Discovering Reinforcement Learning Algorithms NIPS 2020
Ensemble Distillation for Robust Model Fusion in Federated Learning NIPS 2020
Privacy Amplification via Random Check-Ins NIPS 2020
Robust Meta-learning for Mixed Linear Regression with Small Batches NIPS 2020
Meta-Neighborhoods NIPS 2020
Federated Accelerated Stochastic Gradient Descent NIPS 2020
Graph Meta Learning via Local Subgraphs NIPS 2020
Minibatch vs Local SGD for Heterogeneous Distributed Learning NIPS 2020
Federated Principal Component Analysis NIPS 2020
Bootstrapping neural processes NIPS 2020
Online Structured Meta-learning NIPS 2020
FedSplit: an algorithmic framework for fast federated optimization NIPS 2020
Synthetic Data Generators -- Sequential and Private NIPS 2020
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization NIPS 2020
A Scalable Approach for Privacy-Preserving Collaborative Machine Learning NIPS 2020
Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes NIPS 2020
Curriculum Learning by Dynamic Instance Hardness NIPS 2020
Federated Bayesian Optimization via Thompson Sampling NIPS 2020
Neural Complexity Measures NIPS 2020
MetaSDF: Meta-Learning Signed Distance Functions NIPS 2020
Make One-Shot Video Object Segmentation Efficient Again NIPS 2020
Learning Compositional Rules via Neural Program Synthesis NIPS 2020
Convergence of Meta-Learning with Task-Specific Adaptation over Partial Parameters NIPS 2020
MetaPerturb: Transferable Regularizer for Heterogeneous Tasks and Architectures NIPS 2020