1.1k citations · 4k across the 47 of their papers we have counts for
6 papers · 1 filter
CompILE: Compositional Imitation Learning and Execution
Thomas Kipf, Yujia Li, Hanjun Dai +5
We introduce Compositional Imitation Learning and Execution (CompILE): a framework for learning reusable, variable-length segments of hierarchically-structured behavior from demons…
Kernel Exponential Family Estimation via Doubly Dual Embedding
Bo Dai, Hanjun Dai, Arthur Gretton +3
We investigate penalized maximum log-likelihood estimation for exponential family distributions whose natural parameter resides in a reproducing kernel Hilbert space. Key to our ap…
Adversarial Attack on Graph Structured Data
Hanjun Dai, Hui Li, Tian Tian +4
Deep learning on graph structures has shown exciting results in various applications. However, few attentions have been paid to the robustness of such models, in contrast to numero…
KG^2: Learning to Reason Science Exam Questions with Contextual Knowledge Graph Embeddings
Yuyu Zhang, Hanjun Dai, Kamil Toraman +1
The AI2 Reasoning Challenge (ARC), a new benchmark dataset for question answering (QA) has been recently released. ARC only contains natural science questions authored for human ex…
Syntax-Directed Variational Autoencoder for Structured Data
Hanjun Dai, Yingtao Tian, Bo Dai +2
Deep generative models have been enjoying success in modeling continuous data. However it remains challenging to capture the representations for discrete structures with formal gra…
Additive Margin Softmax for Face Verification
Feng Wang, Weiyang Liu, Haijun Liu +1
In this paper, we propose a conceptually simple and geometrically interpretable objective function, i.e. additive margin Softmax (AM-Softmax), for deep face verification. In genera…