Ming Li
33 papers in the PaperMetrix corpus
Papers by this author
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The SYSU System for the Interspeech 2015 Automatic Speaker Verification Spoofing and Countermeasures Challenge
2015 · arXiv (Cornell University)
Many existing speaker verification systems are reported to be vulnerable against different spoofing attacks, for example speaker-adapted speech synthesis, voice conversion, play back, etc. In order to detect these spoofed speech signals as a countermeasure, …
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An Approach to the Match between Experts and Users in a Fuzzy Linguistic Environment
2016 · Information
Knowledge management systems are widely used to manage the knowledge in organizations. Consulting experts is an effective way to utilize tacit knowledge. The paper aims to optimize the match between users and experts to improve …
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Learning unified features from natural and programming languages for locating buggy source code
2016 · International Joint Conference on Artificial Intelligence
Bug reports provide an effective way for end-users to disclose potential bugs hidden in a software system, while automatically locating the potential buggy source code according to a bug report remains a great challenge in …
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An approximate optimal chernoff fusion method via importance sampling
2017
This paper focuses on addressing the decentralized data fusion (DDF) problem in dynamic sensor networks based on Chernoff rule. Generally, the Chernoff rule is challenging to implement since the fused probability density functions (pdfs) that …
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Semi-Supervised AUC Optimization Without Guessing Labels of Unlabeled Data
2018 · Proceedings of the AAAI Conference on Artificial Intelligence
Semi-supervised learning, which aims to construct learners that automatically exploit the large amount of unlabeled data in addition to the limited labeled data, has been widely applied in many real-world applications. AUC is a well-known …
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Distributed Deep Forest and its Application to Automatic Detection of Cash-out Fraud
2018 · arXiv (Cornell University)
Internet companies are facing the need for handling large-scale machine learning applications on a daily basis and distributed implementation of machine learning algorithms which can handle extra-large scale tasks with great performance is widely needed. …
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Quantum anomaly detection with density estimation and multivariate Gaussian distribution
2019 · Physical Review A
We study quantum anomaly detection with density estimation and multivariate Gaussian distribution. Both algorithms are constructed using the standard gate-based model of quantum computing. Compared with the corresponding classical algorithms, the resource complexities of our …
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Analysis of Length Normalization in End-to-End Speaker Verification System
2018
The classical i-vectors and the latest end-to-end deep speaker embeddings are the two representative categories of utterancelevel representations in automatic speaker verification systems.Traditionally, once i-vectors or deep speaker embeddings are extracted, we rely on an …
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Data‐driven XGBoost‐based filter for target tracking
2019 · The Journal of Engineering
In recent years, the data‐driven approach has been introduced in the field of target tracking as a powerful tool developing the end‐to‐end mapping relationship between input features and outputs. Typically, in data‐driven methods, neural networks …
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Study on the Modification on DS Theory of Evidence Based on Evidence Support Level
2019 · DEStech Transactions on Computer Science and Engineering
To avoid the unreasonable evidence theory caused by the high conflict evidence, the modification on DS Theory of Evidence (DSTE) based on evidence support level is proposed in this paper. First of all, various modifications …
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A framework for rocket and satellite launch information management systems based on blockchain technology
2019 · Enterprise Information Systems
The paper proposed the framework for rocket and satellite launch information management systems based on blockchain technology to meet the requirements for the storage and use of credible information. First, the launch stages of a …
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Data Inference from Encrypted Databases: A Multi-dimensional Order-Preserving Matching Approach
2020 · arXiv (Cornell University)
Due to increasing concerns of data privacy, databases are being encrypted before they are stored on an untrusted server. To enable search operations on the encrypted data, searchable encryption techniques have been proposed. Representative schemes …
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Within-sample variability-invariant loss for robust speaker recognition under noisy environments
2020 · arXiv (Cornell University)
Despite the significant improvements in speaker recognition enabled by deep neural networks, unsatisfactory performance persists under noisy environments. In this paper, we train the speaker embedding network to learn the "clean" embedding of the noisy …
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Acoustic Word Embedding System for Code-Switching Query-by-example Spoken Term Detection
2020 · ArXiv.org
In this paper, we propose a deep convolutional neural network-based acoustic word embedding system on code-switching query by example spoken term detection. Different from previous configurations, we combine audio data in two languages for training …
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GhostImage: Remote Perception Attacks against Camera-based Image\n Classification Systems
2020 · arXiv (Cornell University)
In vision-based object classification systems imaging sensors perceive the\nenvironment and machine learning is then used to detect and classify objects\nfor decision-making purposes; e.g., to maneuver an automated vehicle around an\nobstacle or to raise an alarm …
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Exploring Voice Conversion based Data Augmentation in Text-Dependent Speaker Verification
2020 · arXiv (Cornell University)
In this paper, we focus on improving the performance of the text-dependent speaker verification system in the scenario of limited training data. The speaker verification system deep learning based text-dependent generally needs a large scale …
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An approach for constructing expert yellow pages for community question answering sites
2021 · Expert Systems
Abstract The rapid increase in the number of community‐based question‐and‐answer services is attracting many users. Questions are posted and answered by community members. These users, who can help other users answer questions, can be considered …
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Periscope: A Keystroke Inference Attack Using Human Coupled Electromagnetic Emanations
2021
This study presents Periscope, a novel side-channel attack that exploits human-coupled electromagnetic (EM) emanations from touchscreens to infer sensitive inputs on a mobile device. Periscope is motivated by the observation that finger movement over the …
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Cloud Resource Scheduling Algorithm Based on Combination Weight
2022 · 2022 IEEE 10th Joint International Information Technology and Artificial Intelligence Conference (ITAIC)
The default scheduling algorithm in the cloud environment only considers the two performance indicators of CPU and memory, and uses a unified weight to calculate the candidate node score, which cannot meet the needs of …
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Large-scale coherent Ising machine based on optoelectronic parametric oscillator
2022 · Light Science & Applications
Ising machines based on analog systems have the potential to accelerate the solution of ubiquitous combinatorial optimization problems. Although some artificial spins to support large-scale Ising machines have been reported, e.g., superconducting qubits in quantum …
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Physical Layer Data Manipulation Attacks on the CAN Bus
2022
The Controller Area Network (CAN) bus standard is the most common in-vehicle network that provides communication between Electronic Control Units (ECUs). CAN messages lack authentication and data integrity protection mechanisms and hence are vulnerable to …
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Remote Perception Attacks against Camera-based Object Recognition Systems and Countermeasures
2023 · ACM Transactions on Cyber-Physical Systems
In vision-based object recognition systems, imaging sensors perceive the environment and then objects are detected and classified for decision-making purposes, e.g., to maneuver an automated vehicle around an obstacle or to raise alarms for intruders …
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Approximating Human-Like Few-shot Learning with GPT-based Compression
2023 · arXiv (Cornell University)
In this work, we conceptualize the learning process as information compression. We seek to equip generative pre-trained models with human-like learning capabilities that enable data compression during inference. We present a novel approach that utilizes …
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APIDocBooster: An Extract-Then-Abstract Framework Leveraging Large Language Models for Augmenting API Documentation
2023 · arXiv (Cornell University)
API documentation is often the most trusted resource for programming. Many approaches have been proposed to augment API documentation by summarizing complementary information from external resources such as Stack Overflow. Existing extractive-based summarization approaches excel …
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Semi-Supervised Disease Classification Based on Limited Medical Image Data
2024 · IEEE Journal of Biomedical and Health Informatics
Inrecent years, significant progress has been made in the field of learning from positive and unlabeled examples (PU learning), particularly in the context of advancing image and text classification tasks. However, applying PU learning to …
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HA-SCN: Learning Hierarchical Aligned Subtree Convolutional Networks for Graph Classification
2024
In this paper, we propose a Hierarchical Aligned Subtree Convolutional Network (HA-SCN) for graph classification. Our idea is to transform graphs of arbitrary sizes into fixed-sized aligned graphs and construct a normalized K-layer m-ary subtree …
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Management model for enhancing artificial intelligence education of primary schools in Fujian Province
2024 · International Journal of Management in Education
In the current era of Artificial Intelligence (AI), all citizens need to have a certain degree of AI literacy. In China, AI education in primary schools is in the stage of rapid development. The 'Compulsory …
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Multi-Reward as Condition for Instruction-based Image Editing
2024 · arXiv (Cornell University)
High-quality training triplets (instruction, original image, edited image) are essential for instruction-based image editing. Predominant training datasets (e.g., InsPix2Pix) are created using text-to-image generative models (e.g., Stable Diffusion, DALL-E) which are not trained for image …
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From Aleatoric to Epistemic: Exploring Uncertainty Quantification Techniques in Artificial Intelligence
2025 · arXiv (Cornell University)
Uncertainty quantification (UQ) is a critical aspect of artificial intelligence (AI) systems, particularly in high-risk domains such as healthcare, autonomous systems, and financial technology, where decision-making processes must account for uncertainty. This review explores the …
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Exploring Federated Pruning for Large Language Models
2025 · arXiv (Cornell University)
LLM pruning has emerged as a promising technology for compressing LLMs, enabling their deployment on resource-limited devices. However, current methodologies typically require access to public calibration samples, which can be challenging to obtain in privacy-sensitive …
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End-to-End Open-Domain Question Answering with
2019
Wei Yang, Yuqing Xie, Aileen Lin, Xingyu Li, Luchen Tan, Kun Xiong, Ming Li, Jimmy Lin. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics (Demonstrations). 2019.
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Data Augmentation for BERT Fine-Tuning in Open-Domain Question Answering
2019 · arXiv (Cornell University)
Recently, a simple combination of passage retrieval using off-the-shelf IR techniques and a BERT reader was found to be very effective for question answering directly on Wikipedia, yielding a large improvement over the previous state …
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A Novel Learnable Dictionary Encoding Layer for End-to-End Language Identification
2018
A novel learnable dictionary encoding layer is proposed in this paper for end-to-end language identification. It is inline with the conventional GMM i-vector approach both theoretically and practically. We imitate the mechanism of traditional GMM …