8 citations · 10 across the 4 of their papers we have counts for
4 papers
Learning Search-Space Specific Heuristics Using Neural Networks
Yu Liu, Ryo Kuroiwa, Alex Fukunaga
We propose and evaluate a system which learns a neuralnetwork heuristic function for forward search-based, satisficing classical planning. Our system learns distance-to-goal estima…
Consistency of Oblique Decision Tree and its Boosting and Random Forest
Haoran Zhan, Yu Liu, Yingcun Xia
Classification and Regression Tree (CART), Random Forest (RF) and Gradient Boosting Tree (GBT) are probably the most popular set of statistical learning methods. However, their sta…
From Caesar Cipher to Unsupervised Learning: A New Method for Classifier Parameter Estimation
Yu Liu, Li Deng, Jianshu Chen +1
Many important classification problems, such as object classification, speech recognition, and machine translation, have been tackled by the supervised learning paradigm in the pas…
Unsupervised Sequence Classification using Sequential Output Statistics
Yu Liu, Jianshu Chen, Li Deng
We consider learning a sequence classifier without labeled data by using sequential output statistics. The problem is highly valuable since obtaining labels in training data is oft…