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YouTube-8M: A Large-Scale Video Classification Benchmark
Many recent advancements in Computer Vision are attributed to large datasets. Open-source software packages for Machine Learning and inexpensive commodity hardware have reduced the barrier of entryExpand
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Local Low-Rank Matrix Approximation
Matrix approximation is a common tool in recommendation systems, text mining, and computer vision. A prevalent assumption in constructing matrix approximations is that the partially observed matrixExpand
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Local collaborative ranking
Personalized recommendation systems are used in a wide variety of applications such as electronic commerce, social networks, web search, and more. Collaborative filtering approaches to recommendationExpand
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A Comparative Study of Collaborative Filtering Algorithms
Collaborative ltering is a rapidly advancing research area. Every year several new techniques are proposed and yet it is not clear which of the techniques work best and under what conditions. In thisExpand
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N-GCN: Multi-scale Graph Convolution for Semi-supervised Node Classification
Graph Convolutional Networks (GCNs) have shown significant improvements in semi-supervised learning on graph-structured data. Concurrently, unsupervised learning of graph embeddings has benefitedExpand
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LLORMA: Local Low-Rank Matrix Approximation
Matrix approximation is a common tool in recommendation systems, text mining, and computer vision. A prevalent assumption in constructing matrix approximations is that the partially observed matrixExpand
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Learning multiple-question decision trees for cold-start recommendation
For cold-start recommendation, it is important to rapidly profile new users and generate a good initial set of recommendations through an interview process --- users should be queried adaptively in aExpand
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PREA: personalized recommendation algorithms toolkit
Recommendation systems are important business applications with significant economic impact. In recent years, a large number of algorithms have been proposed for recommendation systems. In thisExpand
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Personalized Academic Research Paper Recommendation System
A huge number of academic papers are coming out from a lot of conferences and journals these days. In these circumstances, most researchers rely on key-based search or browsing through proceedings ofExpand
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Deep-Hurricane-Tracker: Tracking and Forecasting Extreme Climate Events
Tracking and predicting extreme events in large-scale spatio-temporal climate data are long standing challenges in climate science. In this paper, we propose Convolutional LSTM (ConvLSTM)-basedExpand
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