KDD

Efficient Autotuning of Hyperparameters in Approximate Nearest Neighbor Search

Elias Jääsaari, Ville Hyvönen, Teemu Roos

Comments Accepted for the 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2019

Journal ref Advances in Knowledge Discovery and Data Mining. PAKDD 2019. Lecture Notes in Computer Science, vol 11440. Springer, Cham. pp. 590-602

Random Pairwise Shapelets Forest

Mohan Shi, Zhihai Wang, Jodong Yuan, Haiyang Liu

Comments There is some misunderstanding between authors when this manuscript is submitted. Some of authors disagree to submit this manuscript. So we decide to withdraw the article

Journal ref PAKDD 2018: Advances in Knowledge Discovery and Data Mining

Distributed representation of multi-sense words: A loss-driven approach

Saurav Manchanda, George Karypis

Comments PAKDD 2018 Best paper award runner-up

Journal ref Advances in Knowledge Discovery and Data Mining. PAKDD 2018. Lecture Notes in Computer Science, vol 10938. Springer, Cham

Deep Multi-Output Forecasting: Learning to Accurately Predict Blood Glucose Trajectories

Ian Fox, Lynn Ang, Mamta Jaiswal, Rodica Pop-Busui, Jenna Wiens

Comments KDD 2018

Journal ref Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Contextual Motifs: Increasing the Utility of Motifs using Contextual Data

Ian Fox, Lynn Ang, Mamta Jaiswal, Rodica Pop-Busui, Jenna Wiens

Comments 10 pages, 7 figures, accepted for oral presentation at KDD '17

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

From Dark Matter to Galaxies with Convolutional Networks

Xinyue Zhang, Yanfang Wang, Wei Zhang, Yueqiu Sun, Siyu He, Gabriella Contardo, Francisco Villaescusa-Navarro, Shirley Ho

Comments 10 pages, 11 figures, submitted for KDD 2019

Deep Hierarchical Reinforcement Learning Based Recommendations via Multi-goals Abstraction

Dongyang Zhao, Liang Zhang, Bo Zhang, Lizhou Zheng, Yongjun Bao, Weipeng Yan

Comments submitted to SIGKDD 2019

Large Scale Product Categorization using Structured and Unstructured Attributes

Abhinandan Krishnan, Abilash Amarthaluri

Comments Submitted to KDD 2019

PReP: Path-Based Relevance from a Probabilistic Perspective in Heterogeneous Information Networks

Yu Shi, Po-Wei Chan, Honglei Zhuang, Huan Gui, Jiawei Han

Comments 10 pages. In Proceedings of the 23nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, Nova Scotia, Canada, ACM, 2017

Learning Credible Models

Jiaxuan Wang, Jeeheh Oh, Haozhu Wang, Jenna Wiens

Journal ref KDD '18 Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining 2018

From Node Embedding To Community Embedding

Vincent W. Zheng, Sandro Cavallari, Hongyun Cai, Kevin Chen-Chuan Chang, Erik Cambria

Comments Code available at https://github.com/andompesta/nodeembedding-to-communityembedding

Journal ref KDD WISDOM 2016

ML Health: Fitness Tracking for Production Models

Sindhu Ghanta, Sriram Subramanian, Lior Khermosh, Swaminathan Sundararaman, Harshil Shah, Yakov Goldberg, Drew Roselli, Nisha Talagala

Comments This paper has been submitted to the Data Science track of KDD 2019

Optimized Cost per Click in Taobao Display Advertising

Han Zhu, Junqi Jin, Chang Tan, Fei Pan, Yifan Zeng, Han Li, Kun Gai

Comments Accepted by KDD 2017

Online Influence Maximization (Extended Version)

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

Comments 13 pages. To appear in KDD 2015. Extended version

Anomaly Detection with Generative Adversarial Networks for Multivariate Time Series

Dan Li, Dacheng Chen, Jonathan Goh, See-kiong Ng

Comments This paper was presented in the 7th International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications on the ACM Knowledge Discovery and Data Mining conference, August 2018, London, United Kingdom

Unlearn What You Have Learned: Adaptive Crowd Teaching with Exponentially Decayed Memory Learners

Yao Zhou, Arun Reddy Nelakurthi, Jingrui He

Comments 10 pages, KDD 18

Not Just Privacy: Improving Performance of Private Deep Learning in Mobile Cloud

Ji Wang, Jianguo Zhang, Weidong Bao, Xiaomin Zhu, Bokai Cao, Philip S. Yu

Comments Conference version accepted by KDD'18

Learning Tree-based Deep Model for Recommender Systems

Han Zhu, Xiang Li, Pengye Zhang, Guozheng Li, Jie He, Han Li, Kun Gai

Comments Accepted by KDD 2018

Exploring Student Check-In Behavior for Improved Point-of-Interest Prediction

Mengyue Hang, Ian Pytlarz, Jennifer Neville

Comments published in KDD'18

SGR: Self-Supervised Spectral Graph Representation Learning

Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Alex Bronstein, Emmanuel Müller

Comments As appeared in KDD Deep Learning Day workshop

Count-Min: Optimal Estimation and Tight Error Bounds using Empirical Error Distributions

Daniel Ting

Comments Long version of a KDD 2018 paper of the same name

Identifying Sources and Sinks in the Presence of Multiple Agents with Gaussian Process Vector Calculus

Adam D. Cobb, Richard Everett, Andrew Markham, Stephen J. Roberts

Comments KDD '18 Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, Pages 1254-1262, 9 pages, 5 figures, conference submission, University of Oxford. arXiv admin note: text overlap with arXiv:1709.02357

Infrastructure Quality Assessment in Africa using Satellite Imagery and Deep Learning

Barak Oshri, Annie Hu, Peter Adelson, Xiao Chen, Pascaline Dupas, Jeremy Weinstein, Marshall Burke, David Lobell, Stefano Ermon

Journal ref KDD 2018 Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Quantum Statistics-Inspired Neural Attention

Aristotelis Charalampous, Sotirios Chatzis

Comments Submitted to The 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2019)

Cost-Sensitive Reference Pair Encoding for Multi-Label Learning

Yao-Yuan Yang, Kuan-Hao Huang, Chih-Wei Chang, Hsuan-Tien Lin

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

Biomedical Document Clustering and Visualization based on the Concepts of Diseases

Setu Shah, Xiao Luo

Comments KDD 2017's Data Driven Discovery Workshop

An Efficient Bandit Algorithm for Realtime Multivariate Optimization

Daniel N Hill, Houssam Nassif, Yi Liu, Anand Iyer, S V N Vishwanathan

Comments KDD'17 Audience Appreciation Award

Journal ref Daniel N. Hill, Houssam Nassif, Yi Liu, Anand Iyer, and S. V. N. Vishwanathan. 2017. An Efficient Bandit Algorithm for Realtime Multivariate Optimization. In Proceedings of KDD'17, Halifax, NS, Canada, pp. 1813-1821, 2017

Outfit Generation and Style Extraction via Bidirectional LSTM and Autoencoder

Takuma Nakamura, Ryosuke Goto

Comments 9 pages, 5 figures, KDD Workshop AI for fashion

Fairness of Exposure in Rankings

Ashudeep Singh, Thorsten Joachims

Comments In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, London, UK, 2018

Predicting Infant Motor Development Status using Day Long Movement Data from Wearable Sensors

David Goodfellow, Ruoyu Zhi, Rebecca Funke, Jose Carlos Pulido, Maja Mataric, Beth A. Smith

Comments 4 pages, KDD Machine Learning and Healthcare Workshop August 2018. This work was funded in part by the American Physical Therapy Association Academy of Pediatric Physical Therapy Research Grant 1 and 2 Awards (PI: Smith) and in part by NSF award 1706964 (PI: Smith, Co-PI: Matarić)