Jieping Ye

Margin Based PU Learning

2018 · Proceedings of the AAAI Conference on Artificial Intelligence

The PU learning problem concerns about learning from positive and unlabeled data. A popular heuristic is to iteratively enlarge training set based on some margin-based criterion. However, little theoretical analysis has been conducted to support …

Sim2Rec: A Simulator-based Decision-making Approach to Optimize Real-World Long-term User Engagement in Sequential Recommender Systems

2023 · arXiv (Cornell University)

Long-term user engagement (LTE) optimization in sequential recommender systems (SRS) is shown to be suited by reinforcement learning (RL) which finds a policy to maximize long-term rewards. Meanwhile, RL has its shortcomings, particularly requiring a …

Self-Learning Symmetric Multi-View Probabilistic Clustering

2024 · IEEE Transactions on Knowledge and Data Engineering

Multi-view Clustering (MVC) has achieved significant progress, with many efforts dedicated to learn knowledge from multiple views. However, most existing methods are either not applicable or require additional steps for incomplete MVC. Such a limitation …

SciPIP: An LLM-based Scientific Paper Idea Proposer

2024 · arXiv (Cornell University)

The rapid advancement of large language models (LLMs) has opened new possibilities for automating the proposal of innovative scientific ideas. This process involves two key phases: literature retrieval and idea generation. However, existing approaches often …

An Attention-Based Graph Neural Network for Heterogeneous Structural Learning

2020 · Proceedings of the AAAI Conference on Artificial Intelligence

In this paper, we focus on graph representation learning of heterogeneous information network (HIN), in which various types of vertices are connected by various types of relations. Most of the existing methods conducted on HIN …