
Adaptive MultiSource Causal Inference
Data scarcity is a tremendous challenge in causal effect estimation. In ...
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Federated Estimation of Causal Effects from Observational Data
Many modern applications collect data that comes in federated spirit, wi...
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Revisiting the Sample Complexity of Sparse Spectrum Approximation of Gaussian Processes
We introduce a new scalable approximation for Gaussian processes with pr...
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CHEER: Rich Model Helps Poor Model via Knowledge Infusion
There is a growing interest in applying deep learning (DL) to healthcare...
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CASTER: Predicting Drug Interactions with Chemical Substructure Representation
Adverse drugdrug interactions (DDIs) remain a leading cause of morbidit...
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Statistical Model Aggregation via Parameter Matching
We consider the problem of aggregating models learned from sequestered, ...
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Bayesian Nonparametric Federated Learning of Neural Networks
In federated learning problems, data is scattered across different serve...
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Collective Online Learning via Decentralized Gaussian Processes in Massive MultiAgent Systems
Distributed machine learning (ML) is a modern computation paradigm that ...
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Decentralized HighDimensional Bayesian Optimization with Factor Graphs
This paper presents a novel decentralized highdimensional Bayesian opti...
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Stochastic Variational Inference for Fully Bayesian Sparse Gaussian Process Regression Models
This paper presents a novel variational inference framework for deriving...
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NearOptimal Adversarial Policy Switching for Decentralized Asynchronous MultiAgent Systems
A key challenge in multirobot and multiagent systems is generating sol...
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A Generalized Stochastic Variational Bayesian Hyperparameter Learning Framework for Sparse Spectrum Gaussian Process Regression
While much research effort has been dedicated to scaling up sparse Gauss...
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NearOptimal Active Learning of MultiOutput Gaussian Processes
This paper addresses the problem of active learning of a multioutput Ga...
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Interactive POMDP Lite: Towards Practical Planning to Predict and Exploit Intentions for Interacting with SelfInterested Agents
A key challenge in noncooperative multiagent systems is that of develo...
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A General Framework for Interacting BayesOptimally with SelfInterested Agents using Arbitrary Parametric Model and Model Prior
Recent advances in Bayesian reinforcement learning (BRL) have shown that...
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DecisionTheoretic Coordination and Control for Active MultiCamera Surveillance in Uncertain, Partially Observable Environments
A central problem of surveillance is to monitor multiple targets moving ...
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Trong Nghia Hoang
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