KDD

Fast and Scalable Distributed Deep Convolutional Autoencoder for fMRI Big Data Analytics

Milad Makkie, Heng Huang, Yu Zhao, Athanasios V. Vasilakos, Tianming Liu

Comments This work is submitted to SIGKDD 2018

DeepProbe: Information Directed Sequence Understanding and Chatbot Design via Recurrent Neural Networks

Zi Yin, Keng-hao Chang, Ruofei Zhang

Comments Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2017

Extremely Fast Decision Tree

Chaitanya Manapragada, Geoff Webb, Mahsa Salehi

Comments Submitted to KDD'2018

Shield: Fast, Practical Defense and Vaccination for Deep Learning using JPEG Compression

Nilaksh Das, Madhuri Shanbhogue, Shang-Tse Chen, Fred Hohman, Siwei Li, Li Chen, Michael E. Kounavis, Duen Horng Chau

Comments under review at KDD'18

MIDA: Multiple Imputation using Denoising Autoencoders

Lovedeep Gondara, Ke Wang

Comments To appear in the proceedings of the 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2018)

Measuring Human-perceived Similarity in Heterogeneous Collections

Jesse Anderton, Pavel Metrikov, Virgil Pavlu, Javed Aslam

Comments Reviewed but not accepted for KDD 2014; not resubmitted elsewhere

DyPerm: Maximizing Permanence for Dynamic Community Detection

Prerna Agarwal, Richa Verma, Ayush Agarwal, Tanmoy Chakraborty

Comments 4 tables, 3 figures, Accepted in n 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2018

Neural Tensor Factorization

Xian Wu, Baoxu Shi, Yuxiao Dong, Chao Huang, Nitesh Chawla

Comments 9 pages. Submitted to KDD

Fast Interactive Image Retrieval using large-scale unlabeled data

Akshay Mehra, Jihun Hamm, Mikhail Belkin

Comments 15 Pages, Submitted to KDD 2018

Learning multifractal structure in large networks

Austin R. Benson, Carlos Riquelme, Sven Schmit

Journal ref Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD), 2014

Approximate Personalized PageRank on Dynamic Graphs

Hongyang Zhang, Peter Lofgren, Ashish Goel

Comments KDD'16

Recruitment Market Trend Analysis with Sequential Latent Variable Models

Chen Zhu, Hengshu Zhu, Hui Xiong, Pengliang Ding, Fang Xie

Comments 11 pages, 30 figure, SIGKDD 2016

Towards Data Quality Assessment in Online Advertising

Sahin Cem Geyik, Jianqiang Shen, Shahriar Shariat, Ali Dasdan, Santanu Kolay

Comments 10 pages, 7 Figures. This work has been presented in the KDD 2016 Workshop on Enterprise Intelligence

Journal ref KDD 2016 Workshop on Enterprise Intelligence

Luck is Hard to Beat: The Difficulty of Sports Prediction

Raquel YS Aoki, Renato M Assuncao, Pedro OS Vaz de Melo

Comments 10 pages, KDD2017, Applied Data Science track

Journal ref Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2017

When is a Network a Network? Multi-Order Graphical Model Selection in Pathways and Temporal Networks

Ingo Scholtes

Comments 10 pages, 4 figures, 1 table, companion python package pathpy available on gitHub

Journal ref In KDD'17 - Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, Nova Scotia, Canada, August 13-17, 2017

Algorithmic clothing: hybrid recommendation, from street-style-to-shop

Y Qian, P Giaccone, M Sasdelli, E Vasquez, B Sengupta

Comments KDD 2017 Workshop on ML meets Fashion

Deep Tensor Encoding

B Sengupta, E Vasquez, Y Qian

Comments KDD Workshop on ML meets Fashion 2017

Crowdsourcing Cybersecurity: Cyber Attack Detection using Social Media

Rupinder Paul Khandpur, Taoran Ji, Steve Jan, Gang Wang, Chang-Tien Lu, Naren Ramakrishnan

Comments 13 single column pages, 5 figures, submitted to KDD 2017

Soft Methodology for Cost-and-error Sensitive Classification

Te-Kang Jan, Da-Wei Wang, Chi-Hung Lin, Hsuan-Tien Lin

Comments A shorter version appeared in KDD '12

Uncertainty in Online Experiments with Dependent Data: An Evaluation of Bootstrap Methods

Eytan Bakshy, Dean Eckles

Comments 9 pages, 5 figures. This version corrects an error in one set of simulations in Section 3.4 / Figure 4. All other results are unaffected

Journal ref In Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD '13). 2013. ACM, New York, NY, USA, 1303-1311

Measurement Context Extraction from Text: Discovering Opportunities and Gaps in Earth Science

Kyle Hundman, Chris A. Mattmann

Journal ref 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Data-Driven Discovery Workshop, Halifax, Canada, August 2017

EmbedJoin: Efficient Edit Similarity Joins via Embeddings

Haoyu Zhang, Qin Zhang

Comments A preliminary version of this paper has been published in KDD 2017. In this version we have extended the basic EmbedJoin algorithm to EmbedJoin+ which has better accuracy on some tested datasets. 30 pages

Clustrophile: A Tool for Visual Clustering Analysis

Çağatay Demiralp

Comments KDD IDEA'16

Predicting Remaining Useful Life using Time Series Embeddings based on Recurrent Neural Networks

Narendhar Gugulothu, Vishnu TV, Pankaj Malhotra, Lovekesh Vig, Puneet Agarwal, Gautam Shroff

Comments Presented at 2nd ML for PHM Workshop at SIGKDD 2017, Halifax, Canada

A Century of Science: Globalization of Scientific Collaborations, Citations, and Innovations

Yuxiao Dong, Hao Ma, Zhihong Shen, Kuansan Wang

Comments KDD'17: The 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Structural Diversity and Homophily: A Study Across More than One Hundred Big Networks

Yuxiao Dong, Reid A. Johnson, Jian Xu, Nitesh V. Chawla

Comments KDD'17: The 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

"Let me convince you to buy my product ... ": A Case Study of an Automated Persuasive System for Fashion Products

Vitobha Munigala, Srikanth Tamilselvam, Anush Sankaran

Comments ML4Creativity workshop at SIGKDD 2017

Customer Lifetime Value Prediction Using Embeddings

Benjamin Paul Chamberlain, Angelo Cardoso, C. H. Bryan Liu, Roberto Pagliari, Marc Peter Deisenroth

Comments 10 pages, 11 figures

Journal ref Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining Pages 1753-1762, 2017

"Breaking" Disasters: Predicting and Characterizing the Global News Value of Natural and Man-made Disasters

Armineh Nourbakhsh, Quanzhi Li, Xiaomo Liu, Sameena Shah

Comments Accepted by KDD 2017 Data Science + Journalism workshop

Intelligent Disaster Response via Social Media Analysis - A Survey

Tahora H. Nazer, Guoliang Xue, Yusheng Ji, Huan Liu

Comments 14 pages, 3 figures, 104 references, accepted in SIGKDD Explorations