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09/20/2023
Construction of Paired Knowledge Graph-Text Datasets Informed by Cyclic Evaluation
Datasets that pair Knowledge Graphs (KG) and text together (KG-T) can be...
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05/16/2023
Growing and Serving Large Open-domain Knowledge Graphs
Applications of large open-domain knowledge graphs (KGs) to real-world p...
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04/04/2023
High-Throughput Vector Similarity Search in Knowledge Graphs
There is an increasing adoption of machine learning for encoding data in...
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09/27/2022
Hamiltonian Adaptive Importance Sampling
Importance sampling (IS) is a powerful Monte Carlo (MC) methodology for ...
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01/26/2021
Adaptive Neuro Fuzzy Networks based on Quantum Subtractive Clustering
Data mining techniques can be used to discover useful patterns by explor...
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07/27/2020
Off-policy Evaluation in Infinite-Horizon Reinforcement Learning with Latent Confounders
Off-policy evaluation (OPE) in reinforcement learning is an important pr...
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03/24/2020
Black-box Off-policy Estimation for Infinite-Horizon Reinforcement Learning
Off-policy estimation for long-horizon problems is important in many rea...
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05/26/2018
Unsupervised Learning with Stein's Unbiased Risk Estimator
Learning from unlabeled and noisy data is one of the grand challenges of...
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07/11/2017
DeepCodec: Adaptive Sensing and Recovery via Deep Convolutional Neural Networks
In this paper we develop a novel computational sensing framework for sen...
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04/21/2017
Learned D-AMP: Principled Neural Network based Compressive Image Recovery
Compressive image recovery is a challenging problem that requires fast a...
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01/14/2017
Learning to Invert: Signal Recovery via Deep Convolutional Networks
The promise of compressive sensing (CS) has been offset by two significa...
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11/03/2015
Consistent Parameter Estimation for LASSO and Approximate Message Passing
We consider the problem of recovering a vector β_o ∈R^p from n random an...
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08/17/2015
A Deep Learning Approach to Structured Signal Recovery
In this paper, we develop a new framework for sensing and recovering str...
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09/23/2013
