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09/04/2023
Restoration Guarantee of Image Inpainting via Low Rank Patch Matrix Completion
In recent years, patch-based image restoration approaches have demonstra...
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06/26/2023
Nonconvex Stochastic Bregman Proximal Gradient Method with Application to Deep Learning
The widely used stochastic gradient methods for minimizing nonconvex com...
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06/06/2023
Online Tensor Learning: Computational and Statistical Trade-offs, Adaptivity and Optimal Regret
We investigate a generalized framework for estimating latent low-rank te...
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05/10/2023
Computationally Efficient and Statistically Optimal Robust High-Dimensional Linear Regression
High-dimensional linear regression under heavy-tailed noise or outlier c...
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11/29/2022
Towards Generalized Open Information Extraction
Open Information Extraction (OpenIE) facilitates the open-domain discove...
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10/26/2022
Provable Sample-Efficient Sparse Phase Retrieval Initialized by Truncated Power Method
We study the sparse phase retrieval problem, recovering an s-sparse leng...
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07/14/2022
Layout-Aware Information Extraction for Document-Grounded Dialogue: Dataset, Method and Demonstration
Building document-grounded dialogue systems have received growing intere...
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05/24/2022
A Survey on Neural Open Information Extraction: Current Status and Future Directions
Open Information Extraction (OpenIE) facilitates domain-independent disc...
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03/02/2022
Computationally Efficient and Statistically Optimal Robust Low-rank Matrix and Tensor Estimation
Low-rank matrix estimation under heavy-tailed noise is challenging, both...
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08/27/2021
Provable Tensor-Train Format Tensor Completion by Riemannian Optimization
The tensor train (TT) format enjoys appealing advantages in handling str...
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03/16/2021
Generalized Low-rank plus Sparse Tensor Estimation by Fast Riemannian Optimization
We investigate a generalized framework to estimate a latent low-rank plu...
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12/12/2020
Image Restoration: Structured Low Rank Matrix Framework for Piecewise Smooth Functions and Beyond
Recently, mapping a signal/image into a low rank Hankel/Toeplitz matrix ...
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10/06/2020
Joint Semantics and Data-Driven Path Representation for Knowledge Graph Inference
Inference on a large-scale knowledge graph (KG) is of great importance f...
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09/25/2020
AutoETER: Automated Entity Type Representation for Knowledge Graph Embedding
Recent advances in Knowledge Graph Embed-ding (KGE) allow for representi...
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11/20/2019