KDD

Missing Value Imputation for Mixed Data via Gaussian Copula

Yuxuan Zhao, Madeleine Udell

Comments Accepted by KDD 2020

AutoGrow: Automatic Layer Growing in Deep Convolutional Networks

Wei Wen, Feng Yan, Yiran Chen, Hai Li

Comments KDD 2020

Deep Exogenous and Endogenous Influence Combination for Social Chatter Intensity Prediction

Subhabrata Dutta, Sarah Masud, Soumen Chakrabarti, Tanmoy Chakraborty

Comments 6 figures, 7 tables, Accepted in SIGKDD 2020

Towards Knowledge Discovery from the Vatican Secret Archives. In Codice Ratio -- Episode 1: Machine Transcription of the Manuscripts

Donatella Firmani, Marco Maiorino, Paolo Merialdo, Elena Nieddu

Comments Donatella Firmani, Marco Maiorino, Paolo Merialdo, and Elena Nieddu. 2018. Towards Knowledge Discovery from the Vatican Secret Archives. In Codice Ratio - Episode 1: Machine Transcription of the Manuscripts. In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD '18). ACM, New York, NY, USA, 263-272

Real-Time Optimization Of Web Publisher RTB Revenues

Pedro Chahuara, Nicolas Grislain, Grégoire Jauvion, Jean-Michel Renders

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

Optimal Allocation of Real-Time-Bidding and Direct Campaigns

Grégoire Jauvion, Nicolas Grislain

Journal ref Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, July 2018, Pages 416-424

Structural Patterns and Generative Models of Real-world Hypergraphs

Manh Tuan Do, Se-eun Yoon, Bryan Hooi, Kijung Shin

Comments to be published in the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '20)

Recurrent Neural Networks for Stochastic Control in Real-Time Bidding

Nicolas Grislain, Nicolas Perrin, Antoine Thabault

Journal ref 2019. Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. Association for Computing Machinery, New York, NY, USA

Improving Movement Predictions of Traffic Actors in Bird's-Eye View Models using GANs and Differentiable Trajectory Rasterization

Eason Wang, Henggang Cui, Sai Yalamanchi, Mohana Moorthy, Fang-Chieh Chou, Nemanja Djuric

Comments Accepted for publication at ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2020

Interpretable Deep Graph Generation with Node-Edge Co-Disentanglement

Xiaojie Guo, Liang Zhao, Zhao Qin, Lingfei Wu, Amarda Shehu, Yanfang Ye

Comments This paper has been accepted by KDD 2020

Explainable Classification of Brain Networks via Contrast Subgraphs

Tommaso Lanciano, Francesco Bonchi, Aristides Gionis

Comments To be published at KDD 2020

Efficient AutoML Pipeline Search with Matrix and Tensor Factorization

Chengrun Yang, Jicong Fan, Ziyang Wu, Madeleine Udell

Comments This is an extended version of AutoML Pipeline Selection: Efficiently Navigating the Combinatorial Space (DOI: 10.1145/3394486.3403197) at KDD 2020

Average Sensitivity of Spectral Clustering

Pan Peng, Yuichi Yoshida

Comments KDD 2020

Seeker: Real-Time Interactive Search

Ari Biswas, Thai T Pham, Michael Vogelsong, Benjamin Snyder, Houssam Nassif

Comments This paper will appear in KDD 2019

Journal ref Knowledge Discovery in Databases Conference (KDD'19), Anchorage, Alaska, pp. 2867-2875, 2019

Multi-level Graph Convolutional Networks for Cross-platform Anchor Link Prediction

Hongxu Chen, Hongzhi Yin, Xiangguo Sun, Tong Chen, Bogdan Gabrys, Katarzyna Musial

Comments To appear in KDD'20

Learning Opinion Dynamics From Social Traces

Corrado Monti, Gianmarco De Francisci Morales, Francesco Bonchi

Comments Published at KDD2020

Journal ref Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD2020)

On the Art and Science of Machine Learning Explanations

Patrick Hall

Comments This manuscript is a preprint of the text for an invited talk at the 2019 KDD XAI workshop. A previous version has also appeared in the proceedings of the Joint Statistical Meetings. Errata and updates available here: https://github.com/jphall663/kdd_2019. Version 2 incorporated reviewer feedback. Version 3 includes a minor adjustment to Figure 1. Version 4 corrects a minor typo

Assessing Centrality Without Knowing Connections

Leyla Roohi, Benjamin I. P. Rubinstein, Vanessa Teague

Comments Full report of paper appearing in PAKDD2020

Journal ref In: Advances in Knowledge Discovery and Data Mining. PAKDD 2020. Lecture Notes in Computer Science, vol 12085. Springer, Cham, pages 152-163 (2020)

Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks

Zonghan Wu, Shirui Pan, Guodong Long, Jing Jiang, Xiaojun Chang, Chengqi Zhang

Comments Accepted by KDD 2020

Multi-Source Deep Domain Adaptation with Weak Supervision for Time-Series Sensor Data

Garrett Wilson, Janardhan Rao Doppa, Diane J. Cook

Comments Accepted at KDD 2020

Map Generation from Large Scale Incomplete and Inaccurate Data Labels

Rui Zhang, Conrad Albrecht, Wei Zhang, Xiaodong Cui, Ulrich Finkler, David Kung, Siyuan Lu

Comments This paper is accepted by KDD 2020

Molecular Inverse-Design Platform for Material Industries

Seiji Takeda, Toshiyuki Hama, Hsiang-Han Hsu, Victoria A. Piunova, Dmitry Zubarev, Daniel P. Sanders, Jed W. Pitera, Makoto Kogoh, Takumi Hongo, Yenwei Cheng, Wolf Bocanett, Hideaki Nakashika, Akihiro Fujita, Yuta Tsuchiya, Katsuhiko Hino, Kentaro Yano, Shuichi Hirose, Hiroki Toda, Yasumitsu Orii, Daiju Nakano

Comments 9 pages, 7 figures, Accepted to KDD 2020

A Pipeline for Integrated Theory and Data-Driven Modeling of Genomic and Clinical Data

Vineet K Raghu, Xiaoyu Ge, Arun Balajee, Daniel J. Shirer, Isha Das, Panayiotis V. Benos, Panos K. Chrysanthis

Comments 16 pages, 8 figures, Presented at the ACM SIGKDD Workshop on Data Mining in Bioinformatics (BioKDD, 2019)

Sequential Anomaly Detection using Inverse Reinforcement Learning

Min-hwan Oh, Garud Iyengar

Comments Published in KDD 2019 (Oral in Research Paper Track)

Estimating Graphlet Statistics via Lifting

Kirill Paramonov, Dmitry Shemetov, James Sharpnack

Journal ref KDD '19 Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, July 2019, Pages 587-595

NLPMM: a Next Location Predictor with Markov Modeling

Meng Chen, Yang Liu, Xiaohui Yu

Journal ref Pacific-Asia Conference on Knowledge Discovery and Data Mining, 186-197, 2014

Precipitation Nowcasting with Satellite Imagery

Vadim Lebedev, Vladimir Ivashkin, Irina Rudenko, Alexander Ganshin, Alexander Molchanov, Sergey Ovcharenko, Ruslan Grokhovetskiy, Ivan Bushmarinov, Dmitry Solomentsev

Comments Final KDD 2019 version

Journal ref in Proceedings of The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2019

Learning with Sets in Multiple Instance Regression Applied to Remote Sensing

Thomas Uriot

Comments KDD 2019, FEED Workshop

SAFE: Similarity-Aware Multi-Modal Fake News Detection

Xinyi Zhou, Jindi Wu, Reza Zafarani

Comments To be published in The 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2020)

Predicting Different Types of Conversions with Multi-Task Learning in Online Advertising

Junwei Pan, Yizhi Mao, Alfonso Lobos Ruiz, Yu Sun, Aaron Flores

Comments SIGKDD

Journal ref SIGKDD 2019