Helpful Snapshot: Title: Meta Structure: Computing Relevance in Large Heterogeneous Information Networks Authors: Zhipeng Huang*, The ... Title: CaSMoS: A Framework for Learning Candidate Selection Models over Structured Queries and Documents Authors: Fedor ...
Kdd2016 Paper 110 - Context Specific Notes
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Context Specific Notes
Title: Convex Optimization for Linear Query Processing under Approximate Differential Privacy Authors: Ganzhao Yuan*, South ... Title: Predictors without Borders: Behavioral Modeling of Product Adoption in Three Developing Countries Authors: Muhammad ... Title: Compute Job Memory Recommender System Using Machine Learning Authors: Taraneh Taghavi*, Qualcomm Inc.
Overview Useful Overview
Title: Compute Job Memory Recommender System Using Machine Learning Authors: Taraneh Taghavi*, Qualcomm Inc. Title: FRAUDAR: Bounding Graph Fraud in the Face of Camouflage Authors: Bryan Hooi*, Carnegie Mellon University Hyun Ah ...
General Background
Title: Ranking Causal Anomalies via Temporal and Dynamical Analysis on Vanishing Correlations Authors: Wei Cheng*, NEC ... Title: Improving Survey Aggregation with Sparsely Represented Signals Authors: Tianlin Shi, Stanford University Forest ... Title: Meta Structure: Computing Relevance in Large Heterogeneous Information Networks Authors: Zhipeng Huang*, The ...
General Review Notes
Title: Meta Structure: Computing Relevance in Large Heterogeneous Information Networks Authors: Zhipeng Huang*, The ... Title: CaSMoS: A Framework for Learning Candidate Selection Models over Structured Queries and Documents Authors: Fedor ...
Important details found
- Title: Convex Optimization for Linear Query Processing under Approximate Differential Privacy Authors: Ganzhao Yuan*, South ...
- Title: Predictors without Borders: Behavioral Modeling of Product Adoption in Three Developing Countries Authors: Muhammad ...
- Title: Meta Structure: Computing Relevance in Large Heterogeneous Information Networks Authors: Zhipeng Huang*, The ...
- Title: Improving Survey Aggregation with Sparsely Represented Signals Authors: Tianlin Shi, Stanford University Forest ...
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