Lin Liu

Learning information recommendation based on text vector model and support vector machine

2020 · Journal of Intelligent & Fuzzy Systems

The difficulty of knowledge point recommendation based on the learning diagnosis model lies in how to perform feature recognition and selection of recommended knowledge points. At present, the recommendation system has certain problems in the …

Assessing the Fairness of Classifiers with Collider Bias.

2020 · arXiv (Cornell University)

The increasing maturity of machine learning technologies and their applications to decisions relate to everyday decision making have brought concerns about the fairness of the decisions. However, current fairness assessment systems often suffer from collider …

Sequential Search with Off-Policy Reinforcement Learning

2021

Recent years have seen a significant amount of interests in Sequential Recommendation (SR), which aims to understand and model the sequential user behaviors and the interactions between users and items over time. Surprisingly, despite the …

Efficient Learning to Learn a Robust CTR Model for Web-scale Online Sponsored Search Advertising

2021

Click-through rate (CTR) prediction is crucial for online sponsored search advertising. Several successful CTR models have been adopted in the industry, including the regularized logistic regression (LR). Nonetheless, the learning process suffers from two limitations: …

Rectifying Pseudo Labels

2021

Graph Convolutional Networks (GCNs) are powerful representation learning methods for non-Euclidean data. Compared with the Euclidean data, labeling the non-Euclidean data is more expensive. Meanwhile, most existing GCNs only utilize few labeled data but ignore …

A Hybrid Deep Feature-Based Deformable Image Registration Method for Pathology Images

2022 · arXiv (Cornell University)

Pathologists need to combine information from differently stained pathology slices for accurate diagnosis. Deformable image registration is a necessary technique for fusing multi-modal pathology slices. This paper proposes a hybrid deep feature-based deformable image registration …

Requirements Engineering for Machine Learning: A Review and Reflection

2022 · arXiv (Cornell University)

Today, many industrial processes are undergoing digital transformation, which often requires the integration of well-understood domain models and state-of-the-art machine learning technology in business processes. However, requirements elicitation and design decision making about when, where …

Attention Weighted Mixture of Experts with Contrastive Learning for Personalized Ranking in E-commerce

2023 · arXiv (Cornell University)

Ranking model plays an essential role in e-commerce search and recommendation. An effective ranking model should give a personalized ranking list for each user according to the user preference. Existing algorithms usually extract a user …

Exploring Effective Mask Sampling Modeling for Neural Image Compression

2023 · arXiv (Cornell University)

Image compression aims to reduce the information redundancy in images. Most existing neural image compression methods rely on side information from hyperprior or context models to eliminate spatial redundancy, but rarely address the channel redundancy. …

Peer Effect Estimation in the Presence of Simultaneous Feedback and Unobserved Confounders

2025 · arXiv (Cornell University)

Estimating peer causal effects within complex real-world networks such as social networks is challenging, primarily due to simultaneous feedback between peers and unobserved confounders. Existing methods either address unobserved confounders while ignoring the simultaneous feedback, …