mainly on machine learning
- Knowledge Graph Completion via Complex Tensor Factorization
to study on
- OpenKE: An Open Toolkit for Knowledge Embedding
to study on
- Learning Entity and Relation Embeddings for Knowledge Graph Completion
to study on
- FRAUDAR: Bounding Graph Fraud in the Face of Camouflage, 2016
to study on
- M-Zoom: Fast Dense-Block Detection in Tensors with Quality Guarantees, 2016
to study on
- D-Cube: Dense-Block Detection in Terabyte-Scale Tensors, 2017
to study on
- Detecting Near-Duplicates for Web Crawling, 2007
to study on
- A review of unsupervised feature learning and deep learning for time-series modeling, 2014.1
An excellent review on time-series models.
- Auto-Encoding Variational Bayes, 2013.12
A very mathematical paper for me at least, you need to learn a little bit of variational methods.
The hidden layer actually is a generative model. - Adversarial Autoencoders, 2015.11
- Neural machine translation by jointly learning to align and translate, 2014.9
Attention mechanism originator
- Show, Attend and Tell: Neural Image Caption Generation with Visual Attention, 2015.2
Attetion in image caption
- Attention and Augmented Recurrent Neural Networks, 2016.9
Neural Turing Machines, Attention Interfaces, Adaptive Computation Time, Neural Programmers
- Attention Is All You Need, 2017.06
Transformer network architecture proposed
- Efficient Estimation of Word Representations in Vector Space, 2013.01
also known as word2vec