Deep Learning
End-to-end Learning of LDA by Mirror-Descent Back Propagation over a Deep Architecture
Jianshu Chen, Ji He, Yelong Shen, Lin Xiao, Xiaodong He, Jianfeng Gao, Xinying Song, Li Deng
Neural Information Processing Systems http://nips.cc/
Large Scale Adversarial Representation Learning
Neural Information Processing Systems http://nips.cc/
Metalearned Neural Memory
We leverage training and algorithmic techniques from metalearning to update the neural memory function in one shot.
Semantic-Guided Multi-Attention Localization for Zero-Shot Learning
Yizhe Zhu, Jianwen Xie, Zhiqiang Tang, Xi Peng, Ahmed Elgammal
Neural Information Processing Systems http://nips.cc/
Biologically Inspired Mechanisms for Adversarial Robustness
A convolutional neural network strongly robust to adversarial perturbations at reasonable computational and performance cost has not yet been demonstrated.
Visalogy: Answering Visual Analogy Questions
Fereshteh Sadeghi, C. Lawrence Zitnick, Ali Farhadi
In this paper, we study the problem of answering visual analogy questions. These questions take the form of image A is to image B as image C is to what . Answering these questions entails discovering the mapping from image A to image B and then extending the mapping to image C and searching for the image D such that the relation from A to B holds for C to D. We pose this problem as learning an embedding that encourages pairs of analogous images with similar transformations to be close together using convolutional neural networks with a quadruple Siamese architecture. We introduce a dataset of visual analogy questions in natural images, and show first results of its kind on solving analogy questions on natural images.
Learning-Based Low-Rank Approximations
Piotr Indyk, Ali Vakilian, Yang Yuan
Neural Information Processing Systems http://nips.cc/