ACM Knowledge Discovery and Data Mining, KDD 2015

Stream Sampling for Frequency Cap Statistics

Edith Cohen

Stream Sampling for Frequency Cap Statistics

Structured Hedging for Resource Allocations with Leverage

Nicholas Johnson, Arindam Banerjee

Structured Hedging for Resource Allocations with Leverage

An Effective Marketing Strategy for Revenue Maximization with a Quantity Constraint

Ya-Wen Teng, Chih-Hua Tai, Philip S. Yu, Ming-Syan Chen

An Effective Marketing Strategy for Revenue Maximization with a Quantity Constraint

Predicting Ambulance Demand: a Spatio-Temporal Kernel Approach

Zhengyi Zhou, David S. Matteson

Predicting Ambulance Demand: a Spatio-Temporal Kernel Approach

Petuum: A New Platform for Distributed Machine Learning on Big Data

Eric P. Xing, Qirong Ho, Wei Dai, Jin Kyu Kim, Jinliang Wei, Seunghak Lee, Xun Zheng, Pengtao Xie, Abhimanu Kumar, Yaoliang Yu

Petuum: A New Platform for Distributed Machine Learning on Big Data

From Infrastructure to Culture: A/B Testing Challenges in Large Scale Social Networks

Ya Xu, Nanyu Chen, Addrian Fernandez, Omar Sinno, Anmol Bhasin

From Infrastructure to Culture: A/B Testing Challenges in Large Scale Social Networks

Predicting Winning Price in Real Time Bidding with Censored Data

Wush Chi-Hsuan Wu, Mi-Yen Yeh, Ming-Syan Chen

Predicting Winning Price in Real Time Bidding with Censored Data

• https://github.com/wush978/KDD2015wpp

Deep Learning Architecture with Dynamically Programmed Layers for Brain Connectome Prediction

Vivek Veeriah, Rohit Durvasula, Guo-Jun Qi

Deep Learning Architecture with Dynamically Programmed Layers for Brain Connectome Prediction

Multi-Task Learning for Spatio-Temporal Event Forecasting

Liang Zhao, Qian Sun, Jieping Ye, Feng Chen, Chang-Tien Lu, Naren Ramakrishnan

Multi-Task Learning for Spatio-Temporal Event Forecasting

A Machine Learning Framework to Identify Students at Risk of Adverse Academic Outcomes

Himabindu Lakkaraju, Everaldo Aguiar, Carl Shan, David Miller, Nasir Bhanpuri, Rayid Ghani, Kecia L. Addison

A Machine Learning Framework to Identify Students at Risk of Adverse Academic Outcomes

Transfer Learning for Bilingual Content Classification

Qian Sun, Mohammad Shafkat Amin, Baoshi Yan, Craig Martell, Vita Markman, Anmol Bhasin, Jieping Ye

Transfer Learning for Bilingual Content Classification

Reciprocity in Social Networks with Capacity Constraints

Bo Jiang, Zhi-Li Zhang, Don Towsley

Reciprocity in Social Networks with Capacity Constraints

SAME but Different: Fast and High Quality Gibbs Parameter Estimation

Huasha Zhao, Biye Jiang, John F. Canny, Bobby Jaros

SAME but Different: Fast and High Quality Gibbs Parameter Estimation

• https://github.com/BIDData/BIDMach

Web Personalization and Recommender Systems

Shlomo Berkovsky, Jill Freyne

Web Personalization and Recommender Systems

Fast and Robust Parallel SGD Matrix Factorization

Jinoh Oh, Wook-Shin Han, Hwanjo Yu, Xiaoqian Jiang

Fast and Robust Parallel SGD Matrix Factorization

Dynamic Hierarchical Classification for Patient Risk-of-Readmission

Senjuti Basu Roy, Ankur Teredesai, Kiyana Zolfaghar, Rui Liu, David Hazel, Stacey Newman, Albert Marinez

Dynamic Hierarchical Classification for Patient Risk-of-Readmission

Life-stage Prediction for Product Recommendation in E-commerce

Peng Jiang, Yadong Zhu, Yi Zhang, Quan Yuan

Life-stage Prediction for Product Recommendation in E-commerce

Large Scale Distributed Data Science using Apache Spark

James G. Shanahan, Liang Dai

Large Scale Distributed Data Science using Apache Spark

Going In-Depth: Finding Longform on the Web

Virginia Smith, Miriam Connor, Isabelle Stanton

Going In-Depth: Finding Longform on the Web

Automatic Entity Recognition and Typing from Massive Text Corpora: A Phrase and Network Mining Approach

Xiang Ren, Ahmed El-Kishky, Chi Wang, Jiawei Han

Automatic Entity Recognition and Typing from Massive Text Corpora: A Phrase and Network Mining Approach

Stochastic Divergence Minimization for Online Collapsed Variational Bayes Zero Inference of Latent Dirichlet Allocation

Issei Sato, Hiroshi Nakagawa

Stochastic Divergence Minimization for Online Collapsed Variational Bayes Zero Inference of Latent Dirichlet Allocation

Collective Opinion Spam Detection: Bridging Review Networks and Metadata

Shebuti Rayana, Leman Akoglu

Collective Opinion Spam Detection: Bridging Review Networks and Metadata

Accelerating Dynamic Time Warping Clustering with a Novel Admissible Pruning Strategy

Nurjahan Begum, Liudmila Ulanova, Jun Wang, Eamonn J. Keogh

Accelerating Dynamic Time Warping Clustering with a Novel Admissible Pruning Strategy

Predictive Approaches for Low-Cost Preventive Medicine Program in Developing Countries

Yukino Baba, Hisashi Kashima, Yasunobu Nohara, Eiko Kai, Partha Pratim Ghosh, Rafiqul Islam Maruf, Ashir Ahmed, Masahiro Kuroda, Sozo Inoue, Tatsuo Hiramatsu, Michio Kimura, Shuji Shimizu, Kunihisa Kobayashi, Koji Tsuda, Masashi Sugiyama, Mathieu Blondel, Naonori Ueda, Masaru Kitsuregawa, Naoki Nakashima

Predictive Approaches for Low-Cost Preventive Medicine Program in Developing Countries

Spectral Ensemble Clustering

Hongfu Liu, Tongliang Liu, Junjie Wu, Dacheng Tao, Yun Fu

Spectral Ensemble Clustering

Non-transitive Hashing with Latent Similarity Components

Mingdong Ou, Peng Cui, Fei Wang, Jun Wang, Wenwu Zhu

Non-transitive Hashing with Latent Similarity Components

Adaptation Algorithm and Theory Based on Generalized Discrepancy

Corinna Cortes, Mehryar Mohri, Andres Muñoz Medina

Adaptation Algorithm and Theory Based on Generalized Discrepancy

• http://cims.nyu.edu/~munoz/adapt_code.tar.gz

Monitoring Least Squares Models of Distributed Streams

Moshe Gabel, Daniel Keren, Assaf Schuster

Monitoring Least Squares Models of Distributed Streams

On the Formation of Circles in Co-authorship Networks

Tanmoy Chakraborty, Sikhar Patranabis, Pawan Goyal, Animesh Mukherjee

On the Formation of Circles in Co-authorship Networks

Unsupervised Feature Selection with Adaptive Structure Learning

Liang Du, Yi-Dong Shen

Unsupervised Feature Selection with Adaptive Structure Learning

• https://github.com/csliangdu/FSASL

Big Data System for Analyzing Risky Procurement Entities

Amit Dhurandhar, Bruce Graves, Rajesh Kumar Ravi, Gopikrishnan Maniachari, Markus Ettl

Big Data System for Analyzing Risky Procurement Entities

Whither Social Networks for Web Search?

Rakesh Agrawal, Behzad Golshan, Evangelos E. Papalexakis

Whither Social Networks for Web Search?

Portraying Collective Spatial Attention in Twitter

Émilien Antoine, Adam Jatowt, Shoko Wakamiya, Yukiko Kawai, Toyokazu Akiyama

Portraying Collective Spatial Attention in Twitter

• https://github.com/shu

Rubik: Knowledge Guided Tensor Factorization and Completion for Health Data Analytics

Yichen Wang, Robert Chen, Joydeep Ghosh, Joshua C. Denny, Abel N. Kho, You Chen, Bradley A. Malin, Jimeng Sun

Rubik: Knowledge Guided Tensor Factorization and Completion for Health Data Analytics

CoupledLP: Link Prediction in Coupled Networks

Yuxiao Dong, Jing Zhang, Jie Tang, Nitesh V. Chawla, Bai Wang

CoupledLP: Link Prediction in Coupled Networks

State-Driven Dynamic Sensor Selection and Prediction with State-Stacked Sparseness

Guo-Jun Qi, Charu C. Aggarwal, Deepak S. Turaga, Daby M. Sow, Phil Anno

State-Driven Dynamic Sensor Selection and Prediction with State-Stacked Sparseness

Deep Graph Kernels

Pinar Yanardag, S. V. N. Vishwanathan

Deep Graph Kernels

Dynamic Matrix Factorization with Priors on Unknown Values

Robin Devooght, Nicolas Kourtellis, Amin Mantrach

Dynamic Matrix Factorization with Priors on Unknown Values

• https://github.com/JohnLangford/vowpal_wabbit/

Clouded Intelligence

Joseph Sirosh

Clouded Intelligence

Online Influence Maximization

Siyu Lei, Silviu Maniu, Luyi Mo, Reynold Cheng, Pierre Senellart

Online Influence Maximization

Analyzing Invariants in Cyber-Physical Systems using Latent Factor Regression

Marjan Momtazpour, Jinghe Zhang, Saifur Rahman, Ratnesh K. Sharma, Naren Ramakrishnan

Analyzing Invariants in Cyber-Physical Systems using Latent Factor Regression

Predicting Serves in Tennis using Style Priors

Xinyu Wei, Patrick Lucey, Stuart Morgan, Peter Carr, Machar Reid, Sridha Sridharan

Predicting Serves in Tennis using Style Priors

Optimizing Marketing Impact through Data Driven Decisioning

Anil Kamath

Optimizing Marketing Impact through Data Driven Decisioning

Dirichlet-Hawkes Processes with Applications to Clustering Continuous-Time Document Streams

Nan Du, Mehrdad Farajtabar, Amr Ahmed, Alexander J. Smola, Le Song

Dirichlet-Hawkes Processes with Applications to Clustering Continuous-Time Document Streams

Predicting Voice Elicited Emotions

Ying Li, Jose D. Contreras, Luis J. Salazar

Predicting Voice Elicited Emotions

Scalable Blocking for Privacy Preserving Record Linkage

Alexandros Karakasidis, Georgia Koloniari, Vassilios S. Verykios

Scalable Blocking for Privacy Preserving Record Linkage

Entity Matching across Heterogeneous Sources

Yang Yang, Yizhou Sun, Jie Tang, Bo Ma, Juan-Zi Li

Entity Matching across Heterogeneous Sources

SEISMIC: A Self-Exciting Point Process Model for Predicting Tweet Popularity

Qingyuan Zhao, Murat A. Erdogdu, Hera Y. He, Anand Rajaraman, Jure Leskovec

SEISMIC: A Self-Exciting Point Process Model for Predicting Tweet Popularity

A Learning-based Framework to Handle Multi-round Multi-party Influence Maximization on Social Networks

Su-Chen Lin, Shou-De Lin, Ming-Syan Chen

A Learning-based Framework to Handle Multi-round Multi-party Influence Maximization on Social Networks

Real Estate Ranking via Mixed Land-use Latent Models

Yanjie Fu, Guannan Liu, Spiros Papadimitriou, Hui Xiong, Yong Ge, Hengshu Zhu, Chen Zhu

Real Estate Ranking via Mixed Land-use Latent Models

Edge-Weighted Personalized PageRank: Breaking A Decade-Old Performance Barrier

Wenlei Xie, David Bindel, Alan J. Demers, Johannes Gehrke

Edge-Weighted Personalized PageRank: Breaking A Decade-Old Performance Barrier

An Architecture for Agile Machine Learning in Real-Time Applications

Johann Schleier-Smith

An Architecture for Agile Machine Learning in Real-Time Applications

• https://github.com/ifwe/antelope

Leveraging Social Context for Modeling Topic Evolution

Janani Kalyanam, Amin Mantrach, Diego Sáez-Trumper, Hossein Vahabi, Gert R. G. Lanckriet

Leveraging Social Context for Modeling Topic Evolution

• https://github.com/amantrac/TopicDiscoveryJPP

One-Pass Ranking Models for Low-Latency Product Recommendations

Antonino Freno, Martin Saveski, Rodolphe Jenatton, Cédric Archambeau

One-Pass Ranking Models for Low-Latency Product Recommendations

Instance Weighting for Patient-Specific Risk Stratification Models

Jen J. Gong, Thoralf M. Sundt, James D. Rawn, John V. Guttag

Instance Weighting for Patient-Specific Risk Stratification Models

Mining for Causal Relationships: A Data-Driven Study of the Islamic State

Andrew Stanton, Amanda Thart, Ashish Jain, Priyank Vyas, Arpan Chatterjee, Paulo Shakarian

Mining for Causal Relationships: A Data-Driven Study of the Islamic State

A Deep Hybrid Model for Weather Forecasting

Aditya Grover, Ashish Kapoor, Eric Horvitz

A Deep Hybrid Model for Weather Forecasting

SCRAM: A Sharing Considered Route Assignment Mechanism for Fair Taxi Route Recommendations

Shiyou Qian, Jian Cao, Frédéric Le Mouël, Issam Sahel, Minglu Li

SCRAM: A Sharing Considered Route Assignment Mechanism for Fair Taxi Route Recommendations

RSC: Mining and Modeling Temporal Activity in Social Media

Alceu Ferraz Costa, Yuto Yamaguchi, Agma Juci Machado Traina, Caetano Traina Jr., Christos Faloutsos

RSC: Mining and Modeling Temporal Activity in Social Media

• https://github.com/alceufc/rsc_model

Exploiting Relevance Feedback in Knowledge Graph Search

Yu Su, Shengqi Yang, Huan Sun, Mudhakar Srivatsa, Sue Kase, Michelle Vanni, Xifeng Yan

Exploiting Relevance Feedback in Knowledge Graph Search

• http://cs.ucsb.edu/~ysu/

On the Reliability of Profile Matching Across Large Online Social Networks

Oana Goga, Patrick Loiseau, Robin Sommer, Renata Teixeira, Krishna P. Gummadi

On the Reliability of Profile Matching Across Large Online Social Networks

Efficient Latent Link Recommendation in Signed Networks

Dongjin Song, David A. Meyer, Dacheng Tao

Efficient Latent Link Recommendation in Signed Networks

Selective Hashing: Closing the Gap between Radius Search and k-NN Search

Jinyang Gao, H. V. Jagadish, Beng Chin Ooi, Sheng Wang

Selective Hashing: Closing the Gap between Radius Search and k-NN Search

Longitudinal LASSO: Jointly Learning Features and Temporal Contingency for Outcome Prediction

Tingyang Xu, Jiangwen Sun, Jinbo Bi

Longitudinal LASSO: Jointly Learning Features and Temporal Contingency for Outcome Prediction

A PCA-Based Change Detection Framework for Multidimensional Data Streams: Change Detection in Multidimensional Data Streams

Abdulhakim Ali Qahtan, Basma Alharbi, Suojin Wang, Xiangliang Zhang

A PCA-Based Change Detection Framework for Multidimensional Data Streams: Change Detection in Multidimensional Data Streams

Dense Subgraph Discovery: KDD 2015 tutorial

Aristides Gionis, Charalampos E. Tsourakakis

Dense Subgraph Discovery: KDD 2015 tutorial

Locally Densest Subgraph Discovery

Lu Qin, Rong-Hua Li, Lijun Chang, Chengqi Zhang

Locally Densest Subgraph Discovery

Inside Jokes: Identifying Humorous Cartoon Captions

Dafna Shahaf, Eric Horvitz, Robert Mankoff

Inside Jokes: Identifying Humorous Cartoon Captions

TOPTRAC: Topical Trajectory Pattern Mining

Younghoon Kim, Jiawei Han, Cangzhou Yuan

TOPTRAC: Topical Trajectory Pattern Mining

Flexible and Robust Multi-Network Clustering

Jingchao Ni, Hanghang Tong, Wei Fan, Xiang Zhang

Flexible and Robust Multi-Network Clustering

Network Lasso: Clustering and Optimization in Large Graphs

David Hallac, Jure Leskovec, Stephen P. Boyd

Network Lasso: Clustering and Optimization in Large Graphs

Discovery of Meaningful Rules in Time Series

Mohammad Shokoohi-Yekta, Yanping Chen, Bilson J. L. Campana, Bing Hu, Jesin Zakaria, Eamonn J. Keogh

Discovery of Meaningful Rules in Time Series

• https://sites.google.com/site/rulediscovery/home
• mshok002@cs.ucr.edu

Promoting Positive Post-Click Experience for In-Stream Yahoo Gemini Users

Mounia Lalmas, Janette Lehmann, Guy Shaked, Fabrizio Silvestri, Gabriele Tolomei

Promoting Positive Post-Click Experience for In-Stream Yahoo Gemini Users

The Effectiveness of Marketing Strategies in Social Media: Evidence from Promotional Events

Panagiotis Adamopoulos, Vilma Todri

The Effectiveness of Marketing Strategies in Social Media: Evidence from Promotional Events

Set Cover at Web Scale

Stergios Stergiou, Kostas Tsioutsiouliklis

Set Cover at Web Scale

Adaptive Message Update for Fast Affinity Propagation

Yasuhiro Fujiwara, Makoto Nakatsuji, Hiroaki Shiokawa, Yasutoshi Ida, Machiko Toyoda

Adaptive Message Update for Fast Affinity Propagation

Exploiting Data Mining for Authenticity Assessment and Protection of High-Quality Italian Wines from Piedmont

Marco Arlorio, Jean Daniel Coïsson, Giorgio Leonardi, Monica Locatelli, Luigi Portinale

Exploiting Data Mining for Authenticity Assessment and Protection of High-Quality Italian Wines from Piedmont

Online Outlier Exploration Over Large Datasets

Lei Cao, Mingrui Wei, Di Yang, Elke A. Rundensteiner

Online Outlier Exploration Over Large Datasets

Estimating Local Intrinsic Dimensionality

Laurent Amsaleg, Oussama Chelly, Teddy Furon, Stéphane Girard, Michael E. Houle, Ken-ichi Kawarabayashi, Michael Nett

Estimating Local Intrinsic Dimensionality

Visual Search at Pinterest

Yushi Jing, David C. Liu, Dmitry Kislyuk, Andrew Zhai, Jiajing Xu, Jeff Donahue, Sarah Tavel

Visual Search at Pinterest

Probabilistic Community and Role Model for Social Networks

Yu Han, Jie Tang

Probabilistic Community and Role Model for Social Networks

Subspace Clustering Using Log-determinant Rank Approximation

Chong Peng, Zhao Kang, Huiqing Li, Qiang Cheng

Subspace Clustering Using Log-determinant Rank Approximation

0-Bit Consistent Weighted Sampling

Ping Li

0-Bit Consistent Weighted Sampling

Multi-View Incident Ticket Clustering for Optimal Ticket Dispatching

Mirela Madalina Botezatu, Jasmina Bogojeska, Ioana Giurgiu, Hagen Völzer, Dorothea Wiesmann

Multi-View Incident Ticket Clustering for Optimal Ticket Dispatching

Virus Propagation in Multiple Profile Networks

Angeliki Rapti, Spyros Sioutas, Kostas Tsichlas, Giannis Tzimas

Virus Propagation in Multiple Profile Networks

• http://alkistis.ceid.upatras.gr/research/kdd15/

Temporal Phenotyping from Longitudinal Electronic Health Records: A Graph Based Framework

Chuanren Liu, Fei Wang, Jianying Hu, Hui Xiong

Temporal Phenotyping from Longitudinal Electronic Health Records: A Graph Based Framework

Influence at Scale: Distributed Computation of Complex Contagion in Networks

Brendan Lucier, Joel Oren, Yaron Singer

Influence at Scale: Distributed Computation of Complex Contagion in Networks

COSNET: Connecting Heterogeneous Social Networks with Local and Global Consistency

Yutao Zhang, Jie Tang, Zhilin Yang, Jian Pei, Philip S. Yu

COSNET: Connecting Heterogeneous Social Networks with Local and Global Consistency

Discovering Collective Narratives of Theme Parks from Large Collections of Visitors' Photo Streams

Gunhee Kim, Leonid Sigal

Discovering Collective Narratives of Theme Parks from Large Collections of Visitors' Photo Streams

Statistical Arbitrage Mining for Display Advertising

Weinan Zhang, Jun Wang

Statistical Arbitrage Mining for Display Advertising

Modeling Truth Existence in Truth Discovery

Shi Zhi, Bo Zhao, Wenzhu Tong, Jing Gao, Dian Yu, Heng Ji, Jiawei Han

Modeling Truth Existence in Truth Discovery

Data Science at Visa

Waqar Hasan, Min Wang

Data Science at Visa

Towards Decision Support and Goal Achievement: Identifying Action-Outcome Relationships From Social Media

Emre KicKiman, Matthew Richardson

Towards Decision Support and Goal Achievement: Identifying Action-Outcome Relationships From Social Media

Client Clustering for Hiring Modeling in Work Marketplaces

Vasilis Verroios, Panagiotis Papadimitriou, Ramesh Johari, Hector Garcia-Molina

Client Clustering for Hiring Modeling in Work Marketplaces

Optimal Action Extraction for Random Forests and Boosted Trees

Zhicheng Cui, Wenlin Chen, Yujie He, Yixin Chen

Optimal Action Extraction for Random Forests and Boosted Trees

• https://cse.wustl.edu/~z.cui/projects/ILP.tar.gz
• z.cui@wustl.edu

Discovering Valuable items from Massive Data

Hastagiri P. Vanchinathan, Andreas Marfurt, Charles-Antoine Robelin, Donald Kossmann, Andreas Krause

Discovering Valuable items from Massive Data

Matrix Completion with Queries

Natali Ruchansky, Mark Crovella, Evimaria Terzi

Matrix Completion with Queries

Co-Clustering based Dual Prediction for Cargo Pricing Optimization

Yada Zhu, Hongxia Yang, Jingrui He

Co-Clustering based Dual Prediction for Cargo Pricing Optimization

Personalizing LinkedIn Feed

Deepak Agarwal, Bee-Chung Chen, Qi He, Zhenhao Hua, Guy Lebanon, Yiming Ma, Pannagadatta Shivaswamy, Hsiao-Ping Tseng, Jaewon Yang, Liang Zhang

Personalizing LinkedIn Feed

On Estimating the Swapping Rate for Categorical Data

Daniel Kifer

On Estimating the Swapping Rate for Categorical Data

Incorporating World Knowledge to Document Clustering via Heterogeneous Information Networks

Chenguang Wang, Yangqiu Song, Ahmed El-Kishky, Dan Roth, Ming Zhang, Jiawei Han

Incorporating World Knowledge to Document Clustering via Heterogeneous Information Networks

Utilizing Text Mining on Online Medical Forums to Predict Label Change due to Adverse Drug Reactions

Ronen Feldman, Oded Netzer, Aviv Peretz, Binyamin Rosenfeld

Utilizing Text Mining on Online Medical Forums to Predict Label Change due to Adverse Drug Reactions

Regularity and Conformity: Location Prediction Using Heterogeneous Mobility Data

Yingzi Wang, Nicholas Jing Yuan, Defu Lian, Linli Xu, Xing Xie, Enhong Chen, Yong Rui

Regularity and Conformity: Location Prediction Using Heterogeneous Mobility Data

Non-exhaustive, Overlapping Clustering via Low-Rank Semidefinite Programming

Yangyang Hou, Joyce Jiyoung Whang, David F. Gleich, Inderjit S. Dhillon

Non-exhaustive, Overlapping Clustering via Low-Rank Semidefinite Programming

Building Discriminative User Profiles for Large-scale Content Recommendation

Erheng Zhong, Nathan Liu, Yue Shi, Suju Rajan

Building Discriminative User Profiles for Large-scale Content Recommendation

Large-Scale Distributed Bayesian Matrix Factorization using Stochastic Gradient MCMC

Sungjin Ahn, Anoop Korattikara, Nathan Liu, Suju Rajan, Max Welling

Large-Scale Distributed Bayesian Matrix Factorization using Stochastic Gradient MCMC

MOOCS: What Have We Learned?

Daphne Koller

MOOCS: What Have We Learned?

Predicting Future Scientific Discoveries Based on a Networked Analysis of the Past Literature

Meenakshi Nagarajan, Angela D. Wilkins, Benjamin J. Bachman, Ilya B. Novikov, Shenghua Bao, Peter J. Haas, María E. Terrón-Díaz, Sumit Bhatia, Anbu K. Adikesavan, Jacques J. Labrie, Sam Regenbogen, Christie M. Buchovecky, Curtis R. Pickering, Linda Kato, Andreas Martin Lisewski, Ana Lelescu, Houyin Zhang, Stephen Boyer, Griff Weber, Ying Chen, Lawrence A. Donehower, W. Scott Spangler, Olivier Lichtarge

Predicting Future Scientific Discoveries Based on a Networked Analysis of the Past Literature

Why It Happened: Identifying and Modeling the Reasons of the Happening of Social Events

Yu Rong, Hong Cheng, Zhiyu Mo

Why It Happened: Identifying and Modeling the Reasons of the Happening of Social Events

More Constraints, Smaller Coresets: Constrained Matrix Approximation of Sparse Big Data

Dan Feldman, Tamir Tassa

More Constraints, Smaller Coresets: Constrained Matrix Approximation of Sparse Big Data

On the Discovery of Evolving Truth

Yaliang Li, Qi Li, Jing Gao, Lu Su, Bo Zhao, Wei Fan, Jiawei Han

On the Discovery of Evolving Truth

User Conditional Hashtag Prediction for Images

Emily Denton, Jason Weston, Manohar Paluri, Lubomir D. Bourdev, Rob Fergus

User Conditional Hashtag Prediction for Images

Predictive Modeling for Public Health: Preventing Childhood Lead Poisoning

Eric Potash, Joe Brew, Alexander Loewi, Subhabrata Majumdar, Andrew Reece, Joe Walsh, Eric Rozier, Emile Jorgenson, Raed Mansour, Rayid Ghani

Predictive Modeling for Public Health: Preventing Childhood Lead Poisoning

• https://github.com/dssg/lead-public

Forecasting Fine-Grained Air Quality Based on Big Data

Yu Zheng, Xiuwen Yi, Ming Li, Ruiyuan Li, Zhangqing Shan, Eric Chang, Tianrui Li

Forecasting Fine-Grained Air Quality Based on Big Data

User Modeling in Telecommunications and Internet Industry

Qiang Yang

User Modeling in Telecommunications and Internet Industry

Generic and Scalable Framework for Automated Time-series Anomaly Detection

Nikolay Laptev, Saeed Amizadeh, Ian Flint

Generic and Scalable Framework for Automated Time-series Anomaly Detection

• https://github.com/yahoo/egads

Medical Mining: KDD 2015 Tutorial

Myra Spiliopoulou, Pedro Pereira Rodrigues, Ernestina Menasalvas Ruiz

Medical Mining: KDD 2015 Tutorial

Efficient Algorithms for Public-Private Social Networks

Flavio Chierichetti, Alessandro Epasto, Ravi Kumar, Silvio Lattanzi, Vahab S. Mirrokni

Efficient Algorithms for Public-Private Social Networks

Discovering and Exploiting Deterministic Label Relationships in Multi-Label Learning

Christina Papagiannopoulou, Grigorios Tsoumakas, Ioannis Tsamardinos

Discovering and Exploiting Deterministic Label Relationships in Multi-Label Learning

Powering Real-time Decision Engines in Finance and Healthcare using Open Source Software

Bassel Ojjeh

Powering Real-time Decision Engines in Finance and Healthcare using Open Source Software

Beyond Triangles: A Distributed Framework for Estimating 3-profiles of Large Graphs

Ethan R. Elenberg, Karthikeyan Shanmugam, Michael Borokhovich, Alexandros G. Dimakis

Beyond Triangles: A Distributed Framework for Estimating 3-profiles of Large Graphs

VC-Dimension and Rademacher Averages: From Statistical Learning Theory to Sampling Algorithms

Matteo Riondato, Eli Upfal

VC-Dimension and Rademacher Averages: From Statistical Learning Theory to Sampling Algorithms

Unified and Contrasting Cuts in Multiple Graphs: Application to Medical Imaging Segmentation

Chia-Tung Kuo, Xiang Wang, Peter B. Walker, Owen T. Carmichael, Jieping Ye, Ian Davidson

Unified and Contrasting Cuts in Multiple Graphs: Application to Medical Imaging Segmentation

Mining Administrative Data to Spur Urban Revitalization

Ben Green, Alejandra Caro, Matthew Conway, Robert Manduca, Tom Plagge, Abby Miller

Mining Administrative Data to Spur Urban Revitalization

• https://github.com/dssg/memphis-public

FrauDetector: A Graph-Mining-based Framework for Fraudulent Phone Call Detection

Vincent S. Tseng, Jia-Ching Ying, Che-Wei Huang, Yimin Kao, Kuan-Ta Chen

FrauDetector: A Graph-Mining-based Framework for Fraudulent Phone Call Detection

• https://github.com/yahoo/egads

Spoken English Grading: Machine Learning with Crowd Intelligence

Vinay Shashidhar, Nishant Pandey, Varun Aggarwal

Spoken English Grading: Machine Learning with Crowd Intelligence