Deep Learning
Data Cleansing for Models Trained with SGD
In this paper, we propose an algorithm that can identify influential instances without using any domain knowledge.
Hyperparameter Ensembles for Robustness and Uncertainty Quantification
In this paper, we design ensembles not only over weights, but over hyperparameters to improve the state of the art in both settings.
Improved Multimodal Deep Learning with Variation of Information
Kihyuk Sohn, Wenling Shang, Honglak Lee
Neural Information Processing Systems http://nips.cc/
SMYRF: Efficient Attention using Asymmetric Clustering
We propose a novel type of balanced clustering algorithm to approximate attention.
Paraphrase Generation with Latent Bag of Words
Yao Fu, Yansong Feng, John P. Cunningham
Neural Information Processing Systems http://nips.cc/
Deep Convolutional Neural Network for Image Deconvolution
Li Xu, Jimmy SJ Ren, Ce Liu, Jiaya Jia
Neural Information Processing Systems http://nips.cc/
Benchmarking Deep Learning Interpretability in Time Series Predictions
These methods are mostly used in vision and language tasks, and their applications to time series data is relatively unexplored.