KDD

RayS: A Ray Searching Method for Hard-label Adversarial Attack

Jinghui Chen, Quanquan Gu

Comments 9 pages, 4 figures, 9 tables. In KDD 2020

Towards Earnings Call and Stock Price Movement

Zhiqiang Ma, Grace Bang, Chong Wang, Xiaomo Liu

Comments Accepted by KDD 2020 MLF workshop

Advancing from Predictive Maintenance to Intelligent Maintenance with AI and IIoT

Haining Zheng, Antonio R. Paiva, Chris S. Gurciullo

Comments The 3rd International Workshop on Artificial Intelligence of Things (AIoT) In conjunction with the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2020)

Relation Embedding for Personalised POI Recommendation

Xianjing Wang, Flora D. Salim, Yongli Ren, Piotr Koniusz

Comments 12 pages, 3 figures, Accepted in the 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2020)

Intelligent Exploration for User Interface Modules of Mobile App with Collective Learning

Jingbo Zhou, Zhenwei Tang, Min Zhao, Xiang Ge, Fuzhen Zhuang, Meng Zhou, Liming Zou, Chenglei Yang, Hui Xiong

Comments 10 pages, accepted as a full paper in KDD 2020

Hierarchical Deep Learning Ensemble to Automate the Classification of Breast Cancer Pathology Reports by ICD-O Topography

Waheeda Saib, David Sengeh, Gcininwe Dlamini, Elvira Singh

Comments Accepted to KDD workshop on Machine Learning for Medicine and Healthcare, August 2018, London UK

BLOB : A Probabilistic Model for Recommendation that Combines Organic and Bandit Signals

Otmane Sakhi, Stephen Bonner, David Rohde, Flavian Vasile

Comments 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Aug 2020, San Diego, United States

A Fast and Robust BERT-based Dialogue State Tracker for Schema-Guided Dialogue Dataset

Vahid Noroozi, Yang Zhang, Evelina Bakhturina, Tomasz Kornuta

Comments Accepted to the Workshop on Conversational Systems Towards Mainstream Adoption at KDD 2020

Predicting conversions in display advertising based on URL embeddings

Yang Qiu, Nikolaos Tziortziotis, Martial Hue, Michalis Vazirgiannis

Comments Accepted at AdKDD 2020 workshop at KDD'20 conference, San Diego, USA

Abstractive Summarization of Spoken and Written Instructions with BERT

Alexandra Savelieva, Bryan Au-Yeung, Vasanth Ramani

Comments Accepted for KDD Converse 2020 (accepted-papers.html" target="_blank" rel="noopener">https://conversekdd20.github.io/accepted-papers.html)

Statistically Significant Pattern Mining with Ordinal Utility

Thien Q. Tran, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma

Comments Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '20), August 23--27, 2020, Virtual Event, CA, USA

MCU-Net: A framework towards uncertainty representations for decision support system patient referrals in healthcare contexts

Nabeel Seedat

Comments 4 pages, 4 figures,Spotlight Talk at KDD 2020 - Applied Data Science for Healthcare Workshop & presented at ICML 2020: Uncertainty and Robustness in Deep Learning

Seasonal-adjustment Based Feature Selection Method for Large-scale Search Engine Logs

Thien Q. Tran, Jun Sakuma

Comments The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '19)

Evolution of Credit Risk Using a Personalized Pagerank Algorithm for Multilayer Networks

Cristián Bravo, María Óskarsdóttir

Comments Conference camera-ready paper - accepted at KDD MLF 2020. 15 pages, 10 figures

Journal ref Proceedings of the Third KDD Workshop on Machine Learning in Finance, joint with 26th ACM SIGKDD Conference on Knowledge Discovery in Databases (KDD MLF 2020). ACM, New York, NY, USA, 8 pages

SentiQ: A Probabilistic Logic Approach to Enhance Sentiment Analysis Tool Quality

Wissam Maamar Kouadri, Salima Benbernou, Mourad Ouziri, Themis Palpanas, Iheb Ben Amor

Comments In Proceedings of the 9th KDD Workshop on Issues of Sentiment Discovery and Opinion Mining (WISDOM 20). San Diego, CA, USA, 8 pages

Hop Sampling: A Simple Regularized Graph Learning for Non-Stationary Environments

Young-Jin Park, Kyuyong Shin, Kyung-Min Kim

Comments presented in KDD 2020 Workshop on Mining and Learning with Graphs (MLG)

Mining Large Quasi-cliques with Quality Guarantees from Vertex Neighborhoods

Aritra Konar, Nicholas D. Sidiropoulos

Comments Accepted for publication at KDD 2020 (Research Track), 12 pages

A Formally Robust Time Series Distance Metric

Maximilian Toller, Bernhard C. Geiger, Roman Kern

Comments MileTS Workshop at KDD'19

Usable Security for ML Systems in Mental Health: A Framework

Helen Jiang, Erwen Senge

Comments Accepted to Designing AI in Support of Good Mental Health (GOOD) Workshop at KDD 2020

An Enhanced Text Classification to Explore Health based Indian Government Policy Tweets

Aarzoo Dhiman, Durga Toshniwal

Comments Accepted to KDD 2020: Applied Data Science for Healthcare Workshop (4 pages, 2 figures, 2 tables)

Predicting Individual Treatment Effects of Large-scale Team Competitions in a Ride-sharing Economy

Teng Ye, Wei Ai, Lingyu Zhang, Ning Luo, Lulu Zhang, Jieping Ye, Qiaozhu Mei

Comments Accepted to KDD 2020

DeepSampling: Selectivity Estimation with Predicted Error and Response Time

Tin Vu, Ahmed Eldawy

Comments 9 pages, published in DeepSpatial 2020

Journal ref ACM SIGKDD Workshop on Deep Learning for Spatiotemporal Data, Applications, and Systems, 2020

COLD: Towards the Next Generation of Pre-Ranking System

Zhe Wang, Liqin Zhao, Biye Jiang, Guorui Zhou, Xiaoqiang Zhu, Kun Gai

Comments accepted by DLP-KDD 2020

Statistical Evaluation of Anomaly Detectors for Sequences

Erik Scharwächter, Emmanuel Müller

Comments 5 pages, 6 figures, accepted at the 6th KDD Workshop on Mining and Learning from Time Series (KDD MiLeTS 2020), source code available at https://github.com/diozaka/anomaly-eval

A Deep Learning Approach for COVID-19 Trend Prediction

Tong Yang, Long Sha, Justin Li, Pengyu Hong

Comments 7 pages, 11 figures, accepted by KDD 2020 epiDAMIK workshop

Treatment Policy Learning in Multiobjective Settings with Fully Observed Outcomes

Soorajnath Boominathan, Michael Oberst, Helen Zhou, Sanjat Kanjilal, David Sontag

Comments To appear at KDD'20

Predictive and Causal Implications of using Shapley Value for Model Interpretation

Sisi Ma, Roshan Tourani

Comments Accepted by KDD CD workshop 2020

An Empirical Analysis of Backward Compatibility in Machine Learning Systems

Megha Srivastava, Besmira Nushi, Ece Kamar, Shital Shah, Eric Horvitz

Comments KDD 2020, 9 pages, 7 figures

LRSpeech: Extremely Low-Resource Speech Synthesis and Recognition

Jin Xu, Xu Tan, Yi Ren, Tao Qin, Jian Li, Sheng Zhao, Tie-Yan Liu

Journal ref KDD 2020

Multi-stream RNN for Merchant Transaction Prediction

Zhongfang Zhuang, Chin-Chia Michael Yeh, Liang Wang, Wei Zhang, Junpeng Wang

Comments Accepted by KDD 2020 Workshop on Machine Learning in Finance