项目作者: iszhaoxin

项目描述 :
高级语言: HTML
项目地址: git://github.com/iszhaoxin/my-notebook.git
创建时间: 2018-04-05T11:18:36Z
项目社区:https://github.com/iszhaoxin/my-notebook

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My-notebooks

These are the notebooks what I have read for quick recall whenever I want to check sone points I have learned.

All IN CHINESE

1. Books&courses

Notebooks about books and courses I read.

1.1 Casuality

causality models reasoning and inference by Pearl.J

State :
  • [Unfinished] chapter 1 : Introduction to Probabilities, Graphs, and Causal Models

1.2 Deep learning

Deep Learning

State :
1.3 PRML

Pattern Recognition and Machine Learning

State :
  • [Unfinished] chapter1 : Introduction
    • Only 1.5 section
  • [Finished] chapter2 : Probability Distributions
  • [Finished] chapter8 : Graphical Models
  • [Unfinished] chapter9 : Mixture Models and EM
  • [Unfinished] chapter10 : Approximate Inference
1.4 Gaussian Process

Gaussian Processes for Machine Learning

State :
  • [Unfinished] chapter2 : Regression

2. Papers

Notebooks of some important papers I have read about NLP and ML, DL

2.1 Deep learning

2.2 Generative model

2.3 Knowledge graph

2.4 Representation learning

2.5 Application of graph neural network(GNN) in NLP

2.6 Theory about graph neural network

2.7 Research on language characteristics

2.8 Relation extraction

2.9 Casuality inference

2.10 Dialogue system

2.11 Coreference resolution

2.12 Machine translation

2.13 Machine reading

2.14 Entity alignment

  • BIG-ALIGN: Fast Bipartite Graph Alignment
  • Cross-lingual Knowledge Graph Alignment via Graph Convolutional Networks
  • LinkNBed: Multi-Graph Representation Learning with Entity Linkage
  • A Joint Embedding Method for Entity Alignment of Knowledge Bases
  • Cross-lingual Entity Alignment via Joint Attribute-Preserving Embedding
  • Iterative Entity Alignment via Joint Knowledge Embeddings
  • Multilingual Knowledge Graph Embeddings for Cross-lingual Knowledge Alignment

3. Topics

3.1 About programing

  • How to deal with big file
  • Introduction about Chainer
  • Introduction about Pandas
  • Introduction about tensorflow
  • Programing tricks in python
  • Python mechanism
  • Introduction about SQL

3.2 About machine learning

  • Bagging, boosting
  • Bayes error
  • Befree
  • Dropout
  • Hessian matrix
  • Imbalance data
  • LSTMs
  • MLE&MAP
  • Regularation
  • Semantics parsing
  • Text similarity
  • posterior&prior
  • Convolution neural network
  • Variational inference
  • NER
  • Inductive bias
  • Lapalance matrix in network thermal conduction
  • Lagrangian
  • Spectral clustering
  • Metrics
2016-RDF Graph Alignment with Bisimulation_1649312276353.pdf
2018-LinkNBed- Multi-Graph Representation Learning with Entity Linkage_1649312276420.pdf
2016-A Joint Embedding Method for Entity Alignment of Knowledge Bases_1649312276516.pdf
2017-Cross-lingual Entity Alignment via Joint Attribute-Preserving Embedding_1649312276604.pdf
2017-Iterative Entity Alignment via Joint Knowledge Embeddings_1649312276664.pdf
2017-Multilingual Knowledge Graph Embeddings for Cross-lingual Knowledge Alignment_1649312276712.pdf
2466-hierarchical-topic-models-and-the-nested-chinese-restaurant-process_1649312276745.pdf
nonparametric_1649312276862.pdf
strange geometry_1649312276947.pdf
2009(NIPS)Supervised dictionary learning_1649312277017.pdf
2014.10:Improving zero-shot learning by mitigating the hubness problem_1649312277055.pdf
A survey of sparse representation_1649312277137.pdf
Gaussian Word Embedding with a Wasserstein Distance Loss_1649312277229.pdf
Maximum Likelihood Estimation of Intrinsic Dimension_1649312277272.pdf
Hyperbolic Entailment Cones for Learning Hierarchical Embeddings_1649312277438.pdf
Hyperbolic Neural Networks_1649312277515.pdf
ThesisDamienFrancoisJan2007_1649312277859.pdf
out_of_vocabulary_1649312278073.pdf
1804.09843_1649312278290.pdf
radovanovic10a_1649312278411.pdf
2014.10:Improving zero-shot learning by mitigating the hubness problem_1649312278474.pdf
5477-neural-word-embedding-as-implicit-matrix-factorization_1649312278597.pdf
1301.3781_1649312278750.pdf
1310.4546_1649312278851.pdf
1802.05365_1649312278962.pdf
Improved Word Representation Learning with Sememes_1649312279132.pdf
strange geometry of skip-gram with negative sampling_1649312279233.pdf
多峰概率分布表示词向量_1649312279278.pdf
apples-apples-semantics_1649312279425.pdf
1809.02630_1649312280038.pdf
7293-adapted-deep-embeddings-a-synthesis-of-methods-for-k-shot-inductive-transfer-learning_1649312280214.pdf
8083-multilingual-anchoring-interactive-topic-modeling-and-alignment-across-languages_1649312280352.pdf
8090-learning-plannable-representations-with-causal-infogan_1649312280440.pdf
8104-a-statistical-recurrent-model-on-the-manifold-of-symmetric-positive-definite-matrices_1649312280498.pdf
8110-glomo-unsupervised-learning-of-transferable-relational-graphs_1649312280551.pdf
8146-co-regularized-alignment-for-unsupervised-domain-adaptation_1649312280676.pdf
8152-the-global-anchor-method-for-quantifying-linguistic-shifts-and-domain-adaptation_1649312280760.pdf
8153-identification-and-estimation-of-causal-effects-from-dependent-data_1649312280817.pdf
8155-learning-and-testing-causal-models-with-interventions_1649312280883.pdf
8156-implicit-bias-of-gradient-descent-on-linear-convolutional-networks_1649312280934.pdf
8179-latent-alignment-and-variational-attention_1649312280998.pdf
8183-deep-anomaly-detection-using-geometric-transformations_1649312281071.pdf
8184-large-scale-computation-of-means-and-clusters-for-persistence-diagrams-using-optimal-transport_1649312281136.pdf
8205-persistence-fisher-kernel-a-riemannian-manifold-kernel-for-persistence-diagrams_1649312281238.pdf
8235-learning-and-inference-in-hilbert-space-with-quantum-graphical-models_1649312281296.pdf
8236-unsupervised-image-to-image-translation-using-domain-specific-variational-information-bound_1649312281486.pdf
8250-deep-generative-models-with-learnable-knowledge-constraints_1649312281642.pdf
8251-the-sparse-manifold-transform_1649312281833.pdf
8262-understanding-regularized-spectral-clustering-via-graph-conductance_1649312281947.pdf
8282-domain-adaptation-by-using-causal-inference-to-predict-invariant-conditional-distributions_1649312281962.pdf
8283-smoothed-analysis-of-discrete-tensor-decomposition-and-assemblies-of-neurons_1649312281973.pdf
8286-removing-hidden-confounding-by-experimental-grounding_1649312282050.pdf
8290-computationally-and-statistically-efficient-learning-of-causal-bayes-nets-using-path-queries_1649312282118.pdf
0d227d1a6fbe6e5ae401d6cc4e6bc7f849e99acc_1649312282163.pdf
1c9f6ef4b3d02a397e1b8ee17c6f62b7917fe696_1649312282231.pdf
3185dc96d7609dca3448484dd1104906ee592300_1649312282344.pdf
4d68c5f5ad3c6f3e45be4c6ffd599724f9c767a4_1649312282440.pdf
4f77b9b97858d2579091acf7c0ca6ba700b6f91f_1649312282497.pdf
53d66b681a21610179d7c3db8b62c13474b7ff5e_1649312282540.pdf
ae6b06b831804268b11ea0acb359857b63aef179_1649312282637.pdf
af4cf7ff968c42391f478da661979e402ad278ce_1649312282751.pdf
bad8fd4dc39db05453b1d4902ff97592b7d3c72e_1649312282839.pdf
d70821e9867c967f02ed7b2eb093b95ef3fa0e3d_1649312282886.pdf
1705.02426_1649312282921.pdf
1801.08641_1649312282970.pdf
1809.11017_1649312283097.pdf
TransH_1649312283218.pdf
TransR_1649312283267.pdf
acl18_kg_geometry_paper_1649312283369.pdf
document_1649312283465.pdf
trouillon16_1649312283639.pdf
1705.02364_1649312283699.pdf
representationlearningreview_1649312283845.pdf
D16-1058_1649312283912.pdf
1707.00896_1649312284100.pdf
1312.6184_1649312284147.pdf
LDA数学八卦_1649312284298.pdf
1607.01759_1649312284388.pdf
1607.04606_1649312284438.pdf
基于文档主题结构的关键词提取方法研究_1649312284662.pdf
10.1.1.401.8198_1649312284795.pdf
Deep Reinforcement Learning for Dialogue Generation_1649312285006.pdf
f63096e07757781f0e672bf98fdf9d45af5502d0_1649312285200.pdf
1507.05523_1649312285353.pdf
tricks in dm_1649312285647.pdf
2018-11-07_Recent Named Entity Recognition and Classification techniques: A systematic review_1649312249778.pdf
2018-11-08_A transition-based joint model for disease named entity recognition and normalization_1649312249798.pdf
2018-11-08_D3NER: biomedical named entity recognition using CRF-biLSTM improved with fine-tuned embeddings of various linguistic information _1649312249822.pdf
2018-11-08_Entity Linking with Effective Acronym Expansion, Instance Selection and Topic Modeling_1649312249915.pdf
2018-11-08_In-domain Context-aware Token Embeddings Improve Biomedical Named Entity Recognition_1649312250163.pdf
2018-11-08_Joint Learning of the Embedding of Words and Entities for Named Entity Disambiguation_1649312250477.pdf
2018-11-08_Named Entity Recognition in the Medical Domain with Constrained CRF Models_1649312250554.pdf
2018-11-08_Named Entity Recognition in the Medical Domain with Constrained CRF Models_E17-1079_1649312250587.pdf
2018-11-08_Pangloss: Fast Entity Linking in Noisy Text Environments_1649312250638.pdf
2018-11-08_SWELLSHARK: A Generative Model for Biomedical Named Entity Recognition without Labeled Data_1649312250735.pdf
2018-11-11_Deep Learning for Named Entity Recognition #1_ Public Datasets and Annotation Methods_1649312251250.pdf
2018-11-11_Entity-aware Image Caption Generation__1649312251753.pdf
2018-11-12_Combining word and entity embeddings for entity linking_1649312251853.pdf
2018-11-12_Comparison of MetaMap and cTAKES for entity extraction in clinical notes_1649312251970.pdf
2018-11-12_Entity Linking: An Issue to Extract Corresponding Entity With Knowledge Base_1649312252143.pdf