3 citations · 3 across the 2 of their papers we have counts for
4 papers
Efficient Global String Kernel with Random Features: Beyond Counting Substructures
Lingfei Wu, Ian En-Hsu Yen, Siyu Huo +5
Analysis of large-scale sequential data has been one of the most crucial tasks in areas such as bioinformatics, text, and audio mining. Existing string kernels, however, either (i)…
P2L: Predicting Transfer Learning for Images and Semantic Relations
Bishwaranjan Bhattacharjee, John R. Kender, Matthew Hill +7
Transfer learning enhances learning across tasks, by leveraging previously learned representations -- if they are properly chosen. We describe an efficient method to accurately est…
IPC: A Benchmark Data Set for Learning with Graph-Structured Data
Patrick Ferber, Tengfei Ma, Siyu Huo +2
Benchmark data sets are an indispensable ingredient of the evaluation of graph-based machine learning methods. We release a new data set, compiled from International Planning Compe…
Online Planner Selection with Graph Neural Networks and Adaptive Scheduling
Tengfei Ma, Patrick Ferber, Siyu Huo +2
Automated planning is one of the foundational areas of AI. Since no single planner can work well for all tasks and domains, portfolio-based techniques have become increasingly popu…