Researcher profile

Ang Li

12 papers in the PaperMetrix corpus

Publications

Papers by this author

  1. DeepObfuscator: Adversarial Training Framework for Privacy-Preserving Image Classification

    2019 · arXiv (Cornell University)

    Deep learning has been widely utilized in many computer vision applications and achieved remarkable commercial success. However, running deep learning models on mobile devices is generally challenging due to limitation of the available computing resources. …

  2. A Bayesian Approach for Characterizing and Mitigating Gate and Measurement Errors

    2020 · arXiv (Cornell University)

    Various noise models have been developed in quantum computing study to describe the propagation and effect of the noise which is caused by imperfect implementation of hardware. Identifying parameters such as gate and readout error …

  3. A Framework to Preserve User Privacy for Machine Learning as a Service

    2020

    Suffered from the contradiction between the limited capacity of local devices and large size of DNN models, a practical solution is transferring the heavy computational tasks from the local to the server side such as …

  4. Retrieval of Scientific and Technological Resources for Experts and Scholars

    2022 · arXiv (Cornell University)

    Institutions of higher learning, research institutes and other scientific research units have abundant scientific and technological resources of experts and scholars, and these talents with great scientific and technological innovation ability are an important force …

  5. A Reference Implementation for a Quantum Message Passing Interface

    2023

    Practical applications of quantum computing are currently limited by the number of qubits that can be set with reasonable fidelity for each system. Therefore, a distributed quantum computing system with multiple quantum computers coherently connected …

  6. Design and implementation of an intelligent recommendation system for product information on an e-commerce platform based on machine learning

    2023

    The rapid growth of e-commerce platforms has resulted in an overwhelming abundance of product information, leading to choice paralysis and information overload for users. To address these challenges and enhance the user experience, an intelligent …

  7. Design of Automatic Identification System for Substation Monitoring Interface Based on Machine Vision

    2023

    Substation is one of the key nodes in building a new energy system. The level of intelligence in substations directly affects the safety and efficiency of smart grids. In order to test and evaluate the …

  8. Benchmarking Optimizers for Qumode State Preparation with Variational Quantum Algorithms

    2024 · arXiv (Cornell University)

    Quantum state preparation involves preparing a target state from an initial system, a process integral to applications such as quantum machine learning and solving systems of linear equations. Recently, there has been a growing interest …

  9. Moderator: Moderating Text-to-Image Diffusion Models through Fine-grained Context-based Policies

    2024

    We present Moderator, a policy-based model management system that allows administrators to specify fine-grained content moderation policies and modify the weights of a text-to-image (TTI) model to make it significantly more challenging for users to …

  10. A Perspective on Quantum Computing Applications in Quantum Chemistry using 25--100 Logical Qubits

    2025 · arXiv (Cornell University)

    The intersection of quantum computing and quantum chemistry represents a promising frontier for achieving quantum utility in domains of both scientific and societal relevance. Owing to the exponential growth of classical resource requirements for simulating …

  11. Commercial LLM Agents Are Already Vulnerable to Simple Yet Dangerous Attacks

    2025 · arXiv (Cornell University)

    A high volume of recent ML security literature focuses on attacks against aligned large language models (LLMs). These attacks may extract private information or coerce the model into producing harmful outputs. In real-world deployments, LLMs …