1.4k citations · 3.6k across the 31 of their papers we have counts for
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Hierarchical Representations for Efficient Architecture Search
Hanxiao Liu, Karen Simonyan, Oriol Vinyals +2
We explore efficient neural architecture search methods and show that a simple yet powerful evolutionary algorithm can discover new architectures with excellent performance. Our ap…
Learning Depthwise Separable Graph Convolution from Data Manifold
Guokun Lai, Hanxiao Liu, Yiming Yang
Convolution Neural Network (CNN) has gained tremendous success in computer vision tasks with its outstanding ability to capture the local latent features. Recently, there has been…
Analogical Inference for Multi-Relational Embeddings
Hanxiao Liu, Yuexin Wu, Yiming Yang
Large-scale multi-relational embedding refers to the task of learning the latent representations for entities and relations in large knowledge graphs. An effective and scalable sol…
RACE: Large-scale ReAding Comprehension Dataset From Examinations
Guokun Lai, Qizhe Xie, Hanxiao Liu +2
We present RACE, a new dataset for benchmark evaluation of methods in the reading comprehension task. Collected from the English exams for middle and high school Chinese students i…
A Comparative Study of Word Embeddings for Reading Comprehension
Bhuwan Dhingra, Hanxiao Liu, Ruslan Salakhutdinov +1
The focus of past machine learning research for Reading Comprehension tasks has been primarily on the design of novel deep learning architectures. Here we show that seemingly minor…
Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks
Guokun Lai, Wei-Cheng Chang, Yiming Yang +1
Multivariate time series forecasting is an important machine learning problem across many domains, including predictions of solar plant energy output, electricity consumption, and…