Deep Learning
Amortized Inference Regularization
Rui Shu, Hung H. Bui, Shengjia Zhao, Mykel J. Kochenderfer, Stefano Ermon
Canonically, the variational principle suggests to prefer an expressive inference model so that the variational approximation is accurate.
Neural Code Comprehension: A Learnable Representation of Code Semantics
Tal Ben-Nun, Alice Shoshana Jakobovits, Torsten Hoefler
Sifting through, categorizing, and understanding code thus becomes an essential task for a variety of fields.
Global Gated Mixture of Second-order Pooling for Improving Deep Convolutional Neural Networks
Qilong Wang, Zilin Gao, Jiangtao Xie, Wangmeng Zuo, Peihua Li
The proposed method is evaluated on two large scale image benchmarks (i.e.,
Learning towards Minimum Hyperspherical Energy
Weiyang Liu, Rongmei Lin, Zhen Liu, Lixin Liu, Zhiding Yu, Bo Dai, Le Song
Neural Information Processing Systems http://nips.cc/
A Linear Speedup Analysis of Distributed Deep Learning with Sparse and Quantized Communication
Neural Information Processing Systems http://nips.cc/
SNIPER: Efficient Multi-Scale Training
Bharat Singh, Mahyar Najibi, Larry S. Davis
Hence, the number of chips generated per image during training adaptively changes based on the scene complexity.
Generalized Zero-Shot Learning with Deep Calibration Network
Shichen Liu, Mingsheng Long, Jianmin Wang, Michael I. Jordan
Zero-shot learning leverages semantic representations such as attributes or class prototypes to bridge source and target classes.
Scalable Hyperparameter Transfer Learning
Valerio Perrone, Rodolphe Jenatton, Matthias W. Seeger, Cedric Archambeau
In this work, we aim to warm-start BO in the context of hyperparameter optimization (HPO).
Deep, complex, invertible networks for inversion of transmission effects in multimode optical fibres
Oisín Moran, Piergiorgio Caramazza, Daniele Faccio, Roderick Murray-Smith
The experimental data is used to train complex-weighted models with a range of regularisation approaches.
Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders
Tengfei Ma, Jie Chen, Cao Xiao
Neural Information Processing Systems http://nips.cc/