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At NJU. 2017/09 - 2018/06

Large-Scale Sparse Prediction, Outliers Detection
Adaptive Scaling for Sparse Detection in Information Extraction
LOF: Identifying Density-Based Local Outliers
Isolation Forest

deepfm
fnn/pnn
nfm
afm

At A. 2017/07 - 2017/09

Sequential, Attention, CTR, Network Representation Learning
DeepIntent: Learning Attentions for Online Advertising with Recurrent Neural Networks
Attention Is All You Need
Convotional Sequence to Sequence Learning 

Deep Learning based Recommender System: A Survey and New Perspectives

DeepWalk: Online Learning of Social Representations
node2vec: Scalable Feature Learning for Networks
Max-Margin DeepWalk: Discriminative Learning of Network Representation
GraRep:Learning Graph Representations with Global Structural Information
Network Representation Learning with Rich Text Information
Neural Word Embedding as Implict Matrix Factorization

At T. 2017/04 - 2017/06

Deep CTR, Word2vec, FM
Wide & Deep Learning for Recommender Systems	Implemented.

Deep Neural Networks for Youtube Recommendations
Learning over multi-field Categorical Data - A Case Study on User Response Prediction
Deep CTR prediction in Display Advertising
Field-aware Factorization Machines for CTR Prediction

Distributed Representations of Sentences and Documents
Distrubuted Representations of Words and Phrases and their Compositionality

2016 and earlier

Deep Learning
CNN for Dummies. Jianxin Wu
Deep learning Review. Nature
On Optimization Methods for Deep Learning
The Loss Surfaces of Multilayer Networks
ImageNet Classification with Deep Convolutional Neural Networks

Rich feature hierarchies for accurate object detection and semantic segmentation
Fast R-CNN
Optimizations
Asynchronous Distributed Semi-Stochastic Gradient Optimization
Accelerating Stochastic Gradient Descent using Predictive Variance Reduction
Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
On the Duality Gap Convergence of ADMM Methods
Proximal Algorithms
Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization

Lagrange Multipliers without Permanent Scarring
Lagrange Multipliers and the Karush-Kuhn-Tucker conditions
Metric Learning
Metric Learning: A Survey By Brian Kulis
Distance Metric Learning for Large Margin Nearest Neighbor Classification
Information-Theoretic Metric Learning
Distance Metric Learning: A Comprehensive Survey. Liu Yang. Rong Jin.
Topic Modeling & NLP
Miscellaneous
XGBoost: A Scalable Tree Boosting System
Exploratory Undersampling for Class-Imbalance Learning

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