online learning
254 papers with code • 0 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in online learning
Libraries
Use these libraries to find online learning models and implementationsMost implemented papers
DeepWalk: Online Learning of Social Representations
We present DeepWalk, a novel approach for learning latent representations of vertices in a network.
A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning
Sequential prediction problems such as imitation learning, where future observations depend on previous predictions (actions), violate the common i. i. d.
Online Spatial Concept and Lexical Acquisition with Simultaneous Localization and Mapping
We have proposed a nonparametric Bayesian spatial concept acquisition model (SpCoA).
Agglomerative Likelihood Clustering
We consider the problem of fast time-series data clustering.
Towards Easier and Faster Sequence Labeling for Natural Language Processing: A Search-based Probabilistic Online Learning Framework (SAPO)
We show that this method with fast training and theoretical guarantee of convergence, which is easy to implement, can support search-based optimization and obtain top accuracy.
Extending the Tsetlin Machine With Integer-Weighted Clauses for Increased Interpretability
Here, we address the accuracy-interpretability challenge in machine learning by equipping the TM clauses with integer weights.
Online Learning Rate Adaptation with Hypergradient Descent
gbaydin/hypergradient-descent
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ICLR 2018
We introduce a general method for improving the convergence rate of gradient-based optimizers that is easy to implement and works well in practice.
Improved and Scalable Online Learning of Spatial Concepts and Language Models with Mapping
We propose a novel online learning algorithm, called SpCoSLAM 2. 0, for spatial concepts and lexical acquisition with high accuracy and scalability.
Federated Neuromorphic Learning of Spiking Neural Networks for Low-Power Edge Intelligence
kclip/FL-SNN
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To this end, we introduce an online FL-based learning rule for networked on-device SNNs, which we refer to as FL-SNN.
Visual Memorability for Robotic Interestingness via Unsupervised Online Learning
wang-chen/interestingness
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ECCV 2020
In this paper, we explore the problem of interesting scene prediction for mobile robots.
