Jing Liu

Providing Proactive Fault Tolerance as a Service for Cloud Applications

2016

Lack of flexible and cost-effective fault tolerance mechanism is one of major obstacles for enhancing availability and efficiency of cloud application systems. We propose a novel fault tolerance as a service scheme, where cloud applications …

News Citation Recommendation with Implicit and Explicit Semantics

2016

In this work, we focus on the problem of news citation recommendation. The task aims to recommend news citations for both authors and readers to create and search news references. Due to the sparsity issue …

The Meanings and Strategies of Quality Evaluation System about Innovation and Entrepreneurship in Higher Vocational Colleges

2019

The innovation and entrepreneurship education evaluation system play an important role in the process of implementing innovation and entrepreneurship education in higher vocational colleges. On the basis of studying the meanings of the evaluation system …

A Two-phase Evolutionary Algorithm for Solving the Accuracy-diversity Dilemma in Recommendation

2020

Generating both accurate and diverse recommendations is required for modern recommender systems. Accurate recommendations can well meet the needs of users, while diverse recommendations can bring users novelty, discover the unknown preferences of users, and …

Simplified bacterial foraging optimization with quorum sensing for global optimization

2021 · International Journal of Intelligent Systems

Bacterial foraging optimization (BFO) has been exploited for function optimization, owing to its innovative ideas gleaned from the microbiological system. This paper first discusses its three crucial limitations: high computational cost, difficulty in parameter settings, …

Learning Causal Temporal Relation and Feature Discrimination for Anomaly Detection

2021 · IEEE Transactions on Image Processing

Weakly supervised anomaly detection is a challenging task since frame-level labels are not given in the training phase. Previous studies generally employ neural networks to learn features and produce frame-level predictions and then use multiple …

Evolutionary Multitasking AUC Optimization

2022 · arXiv (Cornell University)

Learning to optimize the area under the receiver operating characteristics curve (AUC) performance for imbalanced data has attracted much attention in recent years. Although there have been several methods of AUC optimization, scaling up AUC …

Computationally Identifying Funneling and Focusing Questions in Classroom Discourse

2022

Responsive teaching is a highly effective strategy that promotes student learning. In math classrooms, teachers might funnel students towards a normative answer or focus students to reflect on their own thinking, deepening their understanding of …

PPDS: Privacy Preserving Data Sharing for AI applications Based on Smart Contracts

2022 · 2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC)

With the development of artificial intelligence, the need for data sharing is becoming more and more urgent. However, the existing data sharing methods can no longer fully meet the data sharing needs. Privacy breaches, lack …

MSN-net: Multi-Scale Normality Network for Video Anomaly Detection

2023

Existing unsupervised video anomaly detection methods often suffer from performance degradation due to the overgeneralization of deep models. In this paper, we propose a simple yet effective Multi-Scale Normality network (MSN-net) that uses hierarchical memories …

Robust Acoustic and Semantic Contextual Biasing in Neural Transducers for Speech Recognition

2023 · arXiv (Cornell University)

Attention-based contextual biasing approaches have shown significant improvements in the recognition of generic and/or personal rare-words in End-to-End Automatic Speech Recognition (E2E ASR) systems like neural transducers. These approaches employ cross-attention to bias the model …

Open-Vocabulary Video Anomaly Detection

2023 · arXiv (Cornell University)

Video anomaly detection (VAD) with weak supervision has achieved remarkable performance in utilizing video-level labels to discriminate whether a video frame is normal or abnormal. However, current approaches are inherently limited to a closed-set setting …

Self-supervised Bipartite Graph Representation Learning: A Dirichlet Max-margin Matrix Factorization Approach

2024 · ACM Transactions on Intelligent Systems and Technology

Bipartite graph representation learning aims to obtain node embeddings by compressing sparse vectorized representations of interactions between two types of nodes, e.g., users and items. Incorporating structural attributes among homogeneous nodes, such as user communities, …

Revealing the Unstable Foundations of eBPF-Based Kernel Extensions

2025

eBPF programs significantly enhance kernel capabilities, but encounter substantial compatibility challenges due to their deep integration with unstable kernel internals. We introduce DepSurf, a tool that identifies dependency mismatches between eBPF programs and kernel images. …

Hierarchically controlled differential evolution algorithm

2025 · Expert Systems with Applications

Differential Evolution (DE), as a population-based metaheuristic global optimization technique, has demonstrated outstanding performance in solving continuous space optimization problems. However, when dealing with complex optimization tasks, DE still faces challenges such as susceptibility to …

CA‐CNN‐GRU Communication Modulation Signal Classification Method Based on Multi‐Scale Feature

2025 · IEEJ Transactions on Electrical and Electronic Engineering

Automatic Modulation Classification (AMC) is critical in communication and information processing, enabling efficient identification of modulation types. However, low SNR environments challenge AMC's accuracy, impacting system reliability and anti‐jamming capability. To address this issue, a …

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