Search Results for author: XiaoDong Li

Found 29 papers, 10 papers with code

Stable Principal Component Pursuit

1 code implementation14 Jan 2010 Zihan Zhou, XiaoDong Li, John Wright, Emmanuel Candes, Yi Ma

We further prove that the solution to a related convex program (a relaxed PCP) gives an estimate of the low-rank matrix that is simultaneously stable to small entrywise noise and robust to gross sparse errors.

Information Theory Information Theory

Rapid, Robust, and Reliable Blind Deconvolution via Nonconvex Optimization

1 code implementation15 Jun 2016 XiaoDong Li, Shuyang Ling, Thomas Strohmer, Ke Wei

To the best of our knowledge, our algorithm is the first blind deconvolution algorithm that is numerically efficient, robust against noise, and comes with rigorous recovery guarantees under certain subspace conditions.

Information Theory Information Theory

Consistency of Spectral Clustering on Hierarchical Stochastic Block Models

no code implementations30 Apr 2020 Lihua Lei, XiaoDong Li, Xingmei Lou

We study the hierarchy of communities in real-world networks under a generic stochastic block model, in which the connection probabilities are structured in a binary tree.

Clustering Stochastic Block Model

A Deep Drift-Diffusion Model for Image Aesthetic Score Distribution Prediction

no code implementations15 Oct 2020 Xin Jin, Xiqiao Li, Heng Huang, XiaoDong Li, Xinghui Zhou

In this paper, we propose a Deep Drift-Diffusion (DDD) model inspired by psychologists to predict aesthetic score distribution from images.

Binary Classification

Instance Space Analysis for the Car Sequencing Problem

no code implementations18 Dec 2020 Yuan Sun, Samuel Esler, Dhananjay Thiruvady, Andreas T. Ernst, XiaoDong Li, Kerri Morgan

We investigate an important research question for solving the car sequencing problem, that is, which characteristics make an instance hard to solve?

Dimensionality Reduction

A Robust Maximum Likelihood Distortionless Response Beamformer based on a Complex Generalized Gaussian Distribution

no code implementations19 Feb 2021 Weixin Meng, Chengshi Zheng, XiaoDong Li

The proposed beamformer can be regarded as a generalization of the minimum power distortionless response beamformer and its improved variations.

Speech Enhancement

Competition on Dynamic Optimization Problems Generated by Generalized Moving Peaks Benchmark (GMPB)

1 code implementation11 Jun 2021 Danial Yazdani, Michalis Mavrovouniotis, Changhe Li, Wenjian Luo, Mohammad Nabi Omidvar, Amir H. Gandomi, Trung Thanh Nguyen, Juergen Branke, XiaoDong Li, Shengxiang Yang, Xin Yao

This document introduces the Generalized Moving Peaks Benchmark (GMPB), a tool for generating continuous dynamic optimization problem instances that is used for the CEC 2024 Competition on Dynamic Optimization.

Learning Primal Heuristics for Mixed Integer Programs

1 code implementation2 Jul 2021 Yunzhuang Shen, Yuan Sun, Andrew Eberhard, XiaoDong Li

This paper proposes a novel primal heuristic for Mixed Integer Programs, by employing machine learning techniques.

Combinatorial Optimization

Learning Linear Polytree Structural Equation Models

1 code implementation22 Jul 2021 Xingmei Lou, Yu Hu, XiaoDong Li

Under the Gaussian polytree models, we study sufficient conditions on the sample sizes for the well-known Chow-Liu algorithm to exactly recover both the skeleton and the equivalence class of the polytree, which is uniquely represented by a CPDAG.

Generating Large-scale Dynamic Optimization Problem Instances Using the Generalized Moving Peaks Benchmark

1 code implementation23 Jul 2021 Mohammad Nabi Omidvar, Danial Yazdani, Juergen Branke, XiaoDong Li, Shengxiang Yang, Xin Yao

This document describes the generalized moving peaks benchmark (GMPB) and how it can be used to generate problem instances for continuous large-scale dynamic optimization problems.

Focusing on Persons: Colorizing Old Images Learning from Modern Historical Movies

1 code implementation14 Aug 2021 Xin Jin, Zhonglan Li, Ke Liu, Dongqing Zou, XiaoDong Li, Xingfan Zhu, Ziyin Zhou, Qilong Sun, Qingyu Liu

Classification sub-module supplies classifying of images according to the eras, nationalities and garment types; Parsing sub-network supplies the semantic for person contours, clothing and background in the image to achieve more accurate colorization of clothes and persons and prevent color overflow.

Classification Colorization +2

Unbiased IoU for Spherical Image Object Detection

no code implementations18 Aug 2021 Qiang Zhao, Bin Chen, Hang Xu, Yike Ma, XiaoDong Li, Bailan Feng, Chenggang Yan, Feng Dai

In this paper, we first identify that spherical rectangles are unbiased bounding boxes for objects in spherical images, and then propose an analytical method for IoU calculation without any approximations.

Object object-detection +1

Enhancing Column Generation by a Machine-Learning-Based Pricing Heuristic for Graph Coloring

1 code implementation8 Dec 2021 Yunzhuang Shen, Yuan Sun, XiaoDong Li, Andrew Eberhard, Andreas Ernst

In each iteration of CG, our MLPH leverages an ML model to predict the optimal solution of the pricing problem, which is then used to guide a sampling method to efficiently generate multiple high-quality columns.

BIG-bench Machine Learning

Novelty-Driven Binary Particle Swarm Optimisation for Truss Optimisation Problems

1 code implementation15 Dec 2021 Hirad Assimi, Frank Neumann, Markus Wagner, XiaoDong Li

Topology optimisation of trusses can be formulated as a combinatorial and multi-modal problem in which locating distinct optimal designs allows practitioners to choose the best design based on their preferences.

Pseudo-labelling and Meta Reweighting Learning for Image Aesthetic Quality Assessment

no code implementations8 Jan 2022 Xin Jin, Hao Lou, Huang Heng, XiaoDong Li, Shuai Cui, Xiaokun Zhang, Xiqiao Li

In the tasks of image aesthetic quality evaluation, it is difficult to reach both the high score area and low score area due to the normal distribution of aesthetic datasets.

Binary Classification Classification +1

A deep complex multi-frame filtering network for stereophonic acoustic echo cancellation

no code implementations3 Feb 2022 Linjuan Cheng, Chengshi Zheng, Andong Li, Yuquan Wu, Renhua Peng, XiaoDong Li

In hands-free communication system, the coupling between loudspeaker and microphone generates echo signal, which can severely influence the quality of communication.

Acoustic echo cancellation

Low-latency Monaural Speech Enhancement with Deep Filter-bank Equalizer

no code implementations14 Feb 2022 Chengshi Zheng, Wenzhe Liu, Andong Li, Yuxuan Ke, XiaoDong Li

To improve the performance of traditional low-latency speech enhancement algorithms, a deep filter-bank equalizer (FBE) framework was proposed, which integrated a deep learning-based subband noise reduction network with a deep learning-based shortened digital filter mapping network.

Speech Enhancement

Efficient Joint DOA and TOA Estimation for Indoor Positioning with 5G Picocell Base Stations

no code implementations20 Jun 2022 Mengguan Pan, Peng Liu, Shengheng Liu, Wangdong Qi, Yongming Huang, Xiaohu You, Xinghua Jia, XiaoDong Li

Secondly, based on the deployment reality that 5G picocell gNBs only have a small-scale antenna array but have a large signal bandwidth, the proposed scheme decouples the estimation of time-of-arrival (TOA) and direction-of-arrival (DOA) to reduce the huge complexity induced by two-dimensional joint processing.

Network medicine framework reveals generic herb-symptom effectiveness of Traditional Chinese Medicine

no code implementations18 Jul 2022 Xiao Gan, Zixin Shu, Xinyan Wang, Dengying Yan, Jun Li, Shany ofaim, Réka Albert, XiaoDong Li, Baoyan Liu, Xuezhong Zhou, Albert-László Barabási

We validate our framework with real-world hospital patient data by showing that (1) shorter network distance between symptoms of inpatients correlates with higher relative risk (co-occurrence), and (2) herb-symptom network proximity is indicative of patients' symptom recovery rate after herbal treatment.

Adaptive Population-based Simulated Annealing for Uncertain Resource Constrained Job Scheduling

no code implementations31 Oct 2022 Dhananjay Thiruvady, Su Nguyen, Yuan Sun, Fatemeh Shiri, Nayyar Zaidi, XiaoDong Li

While a number of optimisation methods have been proposed to tackle the deterministic problem, the uncertainty associated with resource availability, an inevitable challenge in mining operations, has received less attention.

Scheduling

Enhancing Constraint Programming via Supervised Learning for Job Shop Scheduling

no code implementations26 Nov 2022 Yuan Sun, Su Nguyen, Dhananjay Thiruvady, XiaoDong Li, Andreas T. Ernst, Uwe Aickelin

Finally, we demonstrate that hybridising the machine learning-based variable ordering methods with traditional domain-based methods is beneficial.

Job Shop Scheduling Scheduling

Hierarchical Deep Reinforcement Learning for VWAP Strategy Optimization

no code implementations11 Dec 2022 XiaoDong Li, Pangjing Wu, Chenxin Zou, Qing Li

Designing an intelligent volume-weighted average price (VWAP) strategy is a critical concern for brokers, since traditional rule-based strategies are relatively static that cannot achieve a lower transaction cost in a dynamic market.

Hierarchical Reinforcement Learning reinforcement-learning +1

Action Pick-up in Dynamic Action Space Reinforcement Learning

no code implementations3 Apr 2023 Jiaqi Ye, XiaoDong Li, Pangjing Wu, Feng Wang

Then, we design two different AP methods: frequency-based global method and state clustering-based local method, based on the prior optimal policy.

reinforcement-learning

Improving Robustness and Accuracy of Ponzi Scheme Detection on Ethereum Using Time-Dependent Features

no code implementations31 Aug 2023 Phuong Duy Huynh, Son Hoang Dau, XiaoDong Li, Phuc Luong, Emanuele Viterbo

The contract-code-based approach, while achieving very high accuracy, is not robust: first, the source codes of a majority of contracts on Ethereum are not available, and second, a Ponzi developer can fool a contract-code-based detection model by obfuscating the opcode or inventing a new profit distribution logic that cannot be detected (since these models were trained on existing Ponzi logics only).

CDRNP: Cross-Domain Recommendation to Cold-Start Users via Neural Process

no code implementations23 Jan 2024 XiaoDong Li, Jiawei Sheng, Jiangxia Cao, Wenyuan Zhang, Quangang Li, Tingwen Liu

Cross-domain recommendation (CDR) has been proven as a promising way to tackle the user cold-start problem, which aims to make recommendations for users in the target domain by transferring the user preference derived from the source domain.

Meta-Learning

Enhanced Multi-Target Tracking in Dynamic Environments: Distributed Control Methods Within the Random Finite Set Framework

no code implementations25 Jan 2024 Aidan Blair, Amirali Khodadadian Gostar, Alireza Bab-Hadiashar, XiaoDong Li, Reza Hoseinnezhad

Tracking multiple targets in dynamic environments using distributed sensor networks is a challenging problem that has received significant attention in recent years.

Clustering in Dynamic Environments: A Framework for Benchmark Dataset Generation With Heterogeneous Changes

1 code implementation24 Feb 2024 Danial Yazdani, Juergen Branke, Mohammad Sadegh Khorshidi, Mohammad Nabi Omidvar, XiaoDong Li, Amir H. Gandomi, Xin Yao

Clustering in dynamic environments is of increasing importance, with broad applications ranging from real-time data analysis and online unsupervised learning to dynamic facility location problems.

Clustering

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