Ziniu Hu

Unbiased LambdaMART: An Unbiased Pairwise Learning-to-Rank Algorithm

2018 · arXiv (Cornell University)

Although click data is widely used in search systems in practice, so far the inherent bias, most notably position bias, has prevented it from being used in training of a ranker for search, i.e., learning-to-rank. …

Motif-Driven Contrastive Learning of Graph Representations

2020 · arXiv (Cornell University)

Pre-training Graph Neural Networks (GNN) via self-supervised contrastive learning has recently drawn lots of attention. However, most existing works focus on node-level contrastive learning, which cannot capture global graph structure. The key challenge to conducting …

ProgSG: Cross-Modality Representation Learning for Programs in Electronic Design Automation

2023 · arXiv (Cornell University)

Recent years have witnessed the growing popularity of domain-specific accelerators (DSAs), such as Google's TPUs, for accelerating various applications such as deep learning, search, autonomous driving, etc. To facilitate DSA designs, high-level synthesis (HLS) is …

Strategist: Self-improvement of LLM Decision Making via Bi-Level Tree Search

2024 · arXiv (Cornell University)

Traditional reinforcement learning and planning typically requires vast amounts of data and training to develop effective policies. In contrast, large language models (LLMs) exhibit strong generalization and zero-shot capabilities, but struggle with tasks that require …

Heterogeneous Graph Transformer

2020

Recent years have witnessed the emerging success of graph neural networks (GNNs) for modeling structured data. However, most GNNs are designed for homogeneous graphs, in which all nodes and edges belong to the same types, …