Exploring Kdd2016 Paper 995
Exploring Kdd2016 Paper 995 reveals several interesting facts.
- Title: Smart Broadcasting: Do you want to be seen? Authors: Mohammad Reza Karimi*, Sharif University Erfan Tavakoli, Sharif ...
- Title: Parallel Lasso Screening for Big Data Optimization Authors: Qingyang Li*, Arizona State University Shuang Qiu, University of ...
- Title: Communication Efficient Distributed Kernel Principal Component Analysis Authors: Yingyu Liang*, Princeton University Bo ...
- Title: Deep Crossing: Web-Scale Modeling without Manually Crafted Combinatorial Features Authors: Ying Shan*, Microsoft ...
- Title: Overcoming key weaknesses of Distance-based Neighbourhood Methods using a Data Dependent Dissimilarity Authors: Kai ...
In-Depth Information on Kdd2016 Paper 995
Title: Robust Extreme Multi-label Learning Authors: Chang Xu*, Peking University Dacheng Tao, University of Technology Sydney ... Title: Improving Survey Aggregation with Sparsely Represented Signals Authors: Tianlin Shi, Stanford University Forest ... Title: Contextual Intent Tracking for Personal Assistants Authors: Yu Sun*, University of Melbourne Nicholas Jing Yuan, Microsoft ... Author: Chang Xu, Peking University Abstract: Tail labels in the multi-label learning problem undermine the low-rank assumption.
Title: ABRA: Approximating Betweenness Centrality in Static and Dynamic Graphs with Rademacher Averages Authors: Matteo ...
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