YLTsai0609 / paper101

Yu Long's note about machine learning and deep learning

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Computer Vision

Rethinking Pre-training and Self-training

A_Survey_on_3D_Skeleton-Based_Action_Recognition_Using_Learning_Method 2020 B Ren

CrowdHuman: A Benchmark for Detecting Human in a Crowd 2018 S Shao

Learning_Depth_from_Single_Monocular_Images 2006 AY Ng

Make_Skeleton-based_Action_Recognition_Model_Smaller_Faster_and_Better 2019 F Yang

Making_Convolutional_Networks_Shift-Invariant_Again 2019 R Zhang

On_Geometric_Features_for_Skeleton-Based_Action_Recognition_using_Multilayer_LSTM_Networks 2017 S Zhang

Personalized Activity Recognition with Deep Triplet Embeddings 2020 DM Burns

PersonLab: Person Pose Estimation and Instance Segmentation with a Bottom-Up, Part-Based, Geometric Embedding Model 2018 G Papandreou

Simple_Online_and_Realtime_Tracking 2016 A Bewley

Spatial_Tranformer_Networks 2015 M Jaderberg

Stacked_Capsule_Autoencoders 2019 AR Kosiorek

Survey_on_emotional_body_gesture_recognition 2018 F Noroozi

Visualizing_and_Understanding_Convolutional_Networks 2014 MD Zeiler

Zero-Shot_Object_Detection 2019 S Rahman

Recommendation System

Embedding

Factorization Machines 2010

Sparse Linear Methods for Top-N Recommender Systems 2011, Xia Ning, George Karypis

Real-time Personalization using Embeddings for Search Ranking at Airbnb 2018 Mihajlo Grbovic

Billion-scale Commodity Embedding for E-commerce Recommendation in Alibaba 2018 Jizhe Wang

AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction 2020 Bin Liu

Random walk

brief random walk approach survey

WTF: The Who to Follow Service at Twitter 2013 Pankaj Gupta

Related Pins at Pinterest: The Evolution of a Real-World Recommender System 2017 David C. Liu

Pixie: A System for Recommending 3+ Billion Items to 200+ Million Users in Real-Time 2018 Chantat Eksombatchai

Learning Tree-based Deep Model for Recommender Systems 2018 Han Zhu

RecWalk: Nearly Uncoupled Random Walks for Top-N Recommendation 2019 Athanasios N. Nikolakopoulos

Graph Convolution

Learning and Reasoning on Graph for Recommendation WSDM 2020 Conference Tutorial

Graph Convolutional Neural Networks for Web-Scale Recommender Systems 2018 Rex Ying

Hybird Model(Ratings and Content)

Collaborative_topic_modeling 2011

Collaborative topic poisson factorization 2014

Collaborative deep learning for recommendations system 2015

Collaborative topic regression for online recommender systems: An online and Bayesian approach 2017

Metrics

Diversity, Serendipity, Novelty, and Coverage: A Survey and Empirical Analysis of Beyond-Accuracy Objectives in Recommender Systems ACM 2016

A Generic Top-N Recommendation Framework For Trading-off Accuracy, Novelty, and Coverage

Engineering

Online Learning for Recommendations at Grubhub 2021 Alex Egg ACM

Related Pins at Pinterest: The Evolution of a Real-World Recommender System 2018 David C. Liu

DRecPy: A Python Framework for Developing Deep Learning-Based Recommenders 2020 Fábio Colaço

The Optimization of Cost-Model for Join Operator on Spark SQL Platform 2018 Xin Lian, Tianyu Zhang

TopK Join

Scalable similarity-based neighborhood methods with MapReduce 2012

Challenges_in_Deploying_Machine_Learning_a_Survey_of_Case_Studies

Natural Language Processing

Name Entity Recognition

PoI

整合多種搜尋結果以提高 POI 搜尋的準確性

POI 擷取:商家名稱辨識與地址配對之研究

基於已知名稱搜尋結果的網路實體辨識模型建立工具

PTT 網站餐廳美食類別擷取之研究

General Tech

Optimization and Generalization

Memory In Memory: A Predictive Neural Network for Learning Higher-OrderNon-Stationarity from Spatiotemporal Dynamics 2019 Y Wang

When_Does_Label_Smoothing_Help 2019 Rafael Müller

Similarity Learning

Circle Loss: A Unified Perspective of Pair Similarity Optimization 2020 Y Sun

Neural Network Architecture Search

Proving_the_Lottery_Ticket_Hypothesis_Pruning_is_All_You_Need 2020 E Malach

GAN

Modeling Tabular Data using Conditional GAN

Statistical Modeling

Where To Next? A Dynamic Model of User Preferences, 2021, Apr, Spotify

Other

Deep_Learning_in_Mobile_and_Wireless_Networking_A_Survey

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Yu Long's note about machine learning and deep learning


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