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Found 8 papers, 1 papers with code
Multilinear Kernel Regression and Imputation via Manifold Learning
This paper introduces a novel nonparametric framework for data imputation, coined multilinear kernel regression and imputation via the manifold assumption (MultiL-KRIM).
Multi-Linear Kernel Regression and Imputation in Data Manifolds
This paper introduces an efficient multi-linear nonparametric (kernel-based) approximation framework for data regression and imputation, and its application to dynamic magnetic-resonance imaging (dMRI).
Fast Temporal Wavelet Graph Neural Networks
To facilitate reliable and timely forecast for the human brain and traffic networks, we propose the Fast Temporal Wavelet Graph Neural Networks (FTWGNN) that is both time- and memory-efficient for learning tasks on timeseries data with the underlying graph structure, thanks to the theories of multiresolution analysis and wavelet theory on discrete spaces.
Neural-Progressive Hedging: Enforcing Constraints in Reinforcement Learning with Stochastic Programming
We propose a framework, called neural-progressive hedging (NP), that leverages stochastic programming during the online phase of executing a reinforcement learning (RL) policy.
Probabilistic Inference for Learning from Untrusted Sources
Federated learning brings potential benefits of faster learning, better solutions, and a greater propensity to transfer when heterogeneous data from different parties increases diversity.
Variational Bayesian Inference for Crowdsourcing Predictions
Crowdsourcing has emerged as an effective means for performing a number of machine learning tasks such as annotation and labelling of images and other data sets.
Credit Assignment For Collective Multiagent RL With Global Rewards
Scaling decision theoretic planning to large multiagent systems is challenging due to uncertainty and partial observability in the environment.
Policy Gradient With Value Function Approximation For Collective Multiagent Planning
Decentralized (PO)MDPs provide an expressive framework for sequential decision making in a multiagent system.
