Quanming Yao

AutoCross

2019

Feature crossing captures interactions among categorical features and is useful to enhance learning from tabular data in real-world businesses. In this paper, we present AutoCross, an automatic feature crossing tool provided by 4Paradigm to its …

Tensorizing Subgraph Search in the Supernet.

2021 · arXiv (Cornell University)

Recently, a special kind of graph, i.e., supernet, which allows two nodes connected by multi-choice edges, has exhibited its power in neural architecture search (NAS) by searching for better architectures for computer vision (CV) and …

AutoWeird: Weird Translational Scoring Function Identified by Random Search

2022 · arXiv (Cornell University)

Scoring function (SF) measures the plausibility of triplets in knowledge graphs. Different scoring functions can lead to huge differences in link prediction performances on different knowledge graphs. In this report, we describe a weird scoring …

Meta-Graph Based Recommendation Fusion over Heterogeneous Information Networks

2017

Heterogeneous Information Network (HIN) is a natural and general representation of data in modern large commercial recommender systems which involve heterogeneous types of data. HIN based recommenders face two problems: how to represent the high-level …