PaperMetrixEvidence-aware discovery
EN
Interface language English EN العربية AR Türkçe TR
Create account
Researcher profile

Yun Fu

6 papers in the PaperMetrix corpus

Publications

Papers by this author

  1. Generative Correlation Discovery Network for Multi-label Learning

    2019

    The goal of Multi-label learning is to predict multiple labels of each single instance. This is a challenging problem since the training data is limited, long-tail label distribution, and complicated label correlations. Generally, more training …

  2. Deep Decision Tree Transfer Boosting

    2019 · IUScholarWorks (Indiana University)

    Instance transfer approaches consider source and target data together during the training process, and borrow examples from the source domain to augment the training data, when there is limited or no label in the target …

  3. SLA$^2$P: Self-supervised Anomaly Detection with Adversarial Perturbation

    2021 · arXiv (Cornell University)

    Anomaly detection is a fundamental yet challenging problem in machine learning due to the lack of label information. In this work, we propose a novel and powerful framework, dubbed as SLA$^2$P, for unsupervised anomaly detection. …

  4. Self-Training Large Language Models for Improved Visual Program Synthesis With Visual Reinforcement

    2024

    Visual program synthesis is a promising approach to ex-ploit the reasoning abilities of large language models for compositional computer vision tasks. Previous work has used few-shot prompting with frozen LLMs to synthesize visual programs. Training …

  5. Author Topic Model based Collaborative Filtering for Personalized POI Recommendation

    2015 · IEEE Transactions on Multimedia

    From social media has emerged continuous needs for automatic travel recommendations. Collaborative filtering (CF) is the most well-known approach. However, existing approaches generally suffer from various weaknesses. For example , sparsity can significantly degrade the …

  6. Deep Collaborative Filtering via Marginalized Denoising Auto-encoder

    2015

    Collaborative filtering (CF) has been widely employed within recommender systems to solve many real-world problems. Learning effective latent factors plays the most important role in collaborative filtering. Traditional CF methods based upon matrix factorization techniques …