Manuela M. Veloso, Carnegie Mellon University Time series arising for studies of physical, biological, economic and sociological systems are an important data class. This year’s conference will feature three panels: “Fighting a pandemic: convergence of expertise, data science and policy,” a panel of experts from around the globe, will address the challenges and opportunities of using data science to fight a pandemic. However, this intuition is at odds with common machine learning approaches to ranking which directly optimize the relevance of each individual item without a holistic view of the result set. ACM strengthens the computing profession's collective voice through strong leadership, promotion of the highest standards, and recognition of technical excellence. From a product perspective, showing diverse results provides the user with more choice and should lead to an improved experience. Klicken Sie auf "einverstanden", verlassen Sie unserer Seite und werden auf eine externe Seite weitergeleitet. She holds a Ph.D. in computer science from the University of Rochester. Lon.TV. Accepted papers will be presented as posters during the workshop and list on the website. This workshop is a half day workshop taking place on , Aug 24, 2020 in conjunction with KDD 2020, Virtual Conference. Existing methods are capable of managing databases with thousands or tens of thousands of graphs. He has co-edited three books on Supertagging, Natural Language Generation, and Language Translation, has authored over a 100 research publications and holds over 100 patents in these areas. We invite quality research contributions, position and opinion papers addressing relevant challenges in the domain Topics of interest include, but are not limited to: All submitted papers and posters will be single-blind and will be peer reviewed by an international program Read More. Panelists will cite real-world cases where using data science helped the fight against the pandemic and cautionary tales of when it hindered that fight. Emery Brown Massachusetts Institute of Technology. of conversational systems. A real-world system often exhibits complex dynamics arising from interaction among its subunits. We invite quality research contributions, position and opinion papers addressing relevant challenges in the domain The ACM SIGKDD Service Award is the highest recognition of service awarded in the field. RecSys, 2014. KDD Converse is a half day workshop taking place on Monday, August 24, 2020 in conjunction with KDD 2020 in San Diego, CA. Best Paper Awards “BusTr: Predicting Bus Travel Times from Real-Time Traffic” Dr. Bangalore has been an adjunct associate professor at Columbia University (2005), a visiting professor at Princeton University (2008-present) and Otto Monstead Professor at Copenhagen Business School (2013). WWW, 2020. Review based RS. [Learn More about ACM's Public Policy Work...]. Facebook research being presented at KDD 2020. The proposed method overcomes data insufficiency problem of existing work and does not necessarily rely on user demographic information. Skip to content. Anyone, from any background, should feel encouraged to participate and contribute to ACM. Gabriel Blanco Saldana, Saurabh Deshpande, Xin Luna Dong, Xiang He, Andrey Kan, Xian Li, Yan Liang, Jun Ma, Alexandre Michetti Manduca, Jay Ren, Surender Pal Singh, Fan Xiao, Yifan Ethan Xu, Chenwei Zhang, Tong Zhao, Amazon; Haw-Shiuan Chang, University of Massachusetts Amherst; Giannis Karamanolakis, Columbia University; Yuning Mao, University of Illinois at Urbana Champaign, Yaqing Wang, State University of New York at Buffalo, Christos Faloutsos, Carnegie Mellon University; Andrew McCallum, University of Massachusetts Amherst; Jiawei Han, University of Illinois at Urbana Champaign Mengdi Huai, Jianhui Sun, Renqin Cai, Aidong Zhang, University of Virginia; Liuyi Yao, State University of New York at Buffalo 2020 Ford Ranger Review; 2020 Ford Ranger Review. The ACM TechTalk series brings leading computing luminaries and visionaries to your screen. an enterprise-grade conversational system, and the need for a unified success metric. requires a judicious balance of several metrics, often along competing These objectives are parameterized by one or more resolution parameters in order to enable diverse knowledge discovery in complex data. Important Dates. Panelists include Danielle Gewurz, Deloitte Consulting; Shubha Nabar, Faras AI; Monica Rogati, Data Science and AI Advisor; Horst Samulowitz, IBM Watson Research Center. Collaborative Multi-Level Embedding Learning from Reviews for … 2020 ACM SIGKDD Service Award Danai Koutra, Morris Wellman assistant professor of Computer Science and Engineering at University of Michigan, and Jiliang Tang, assistant professor of Computer Science and Engineering at Michigan State University, both received the first annual ACM SIGKDD Rising Star Award. Advances in conversational technologies including speech recognition, The data science revolution is finally enabling the development of large-scale data-driven models that provide scenarios, forecasts and risk analysis for infectious disease threats. “Managing Diversity in Airbnb Search” RecSys, 2013. Learn more. Lon.TV. All talk videos including Keynote, Contributed, and Spotlight will be uploaded to our Youtube DLG Channel after the KDD conference. AutoCTR: Towards automated neural architecture discovering for click-through rate prediction Qingquan Song, Dehua Cheng, Eric Zhou, Jiyan Yang, Yuandong Tian, Xia Hu. "As a longtime member of ACM SIGKDD, I am always incredibly impressed by the contributions of our volunteers," said Zeller. The authors aim to fill this gap by making the following three contributions: (i) they use a real-world dataset collected from 1,400 homeless youth (across six American states) to build accurate Machine Learning (ML) models for predicting the susceptibility of homeless youth to SUD; (ii) they find a representative set of factors associated with SUD among this population by analyzing feature importance values associated with their ML models; and (iii) they investigate the effect of geographical heterogeneity on the factors associated with SUD. Zeller has served on the executive board for eight years, playing an instrumental role in planning multiple KDD conferences. Our new deadline for submission will be June 5th, 2020. Research Track Papers Applied Data Science Track Papers. This workshop aims to bring researchers and practitioners together to discuss issues, learnings, challenges and Although there is a lot of reserach done in developing conversational systems spanning areas such as dialogue systems, NLP, NLU, HCI, search and recommender systems; there are additional challenges when a product is created based on conversational systems and deployed to real world users. areas come together when conversational systems are put in practice along with unique and additional challenges. It also names as Fellows and Distinguished Members those members who, in addition to professional accomplishments, have made significant contributions to ACM's mission. Call For Papers KDD Converse is a half day workshop taking place on Monday, August 24, 2020 in conjunction with KDD 2020 in San Diego, CA. They demonstrate that their neural sequence model improves over DeepTTE, the state-of-the-art baseline, both in performance (-30% MAPE) and training stability. Traditionally NED uses hand-tuned patterns to capture rare, but reliable, signals. 8Bitdo N30 Arcade Stick Review for Nintendo Switch, PC, Mac & Android . Important Dates. The authors present BusTr, a machine-learned model for translating road traffic forecasts into predictions of bus delays, used by Google Maps to serve the majority of the world's public transit systems where no official real-time bus tracking is provided. A partial listing of highlights follows. Exploiting the powerful learning ability of deep neural networks and the efficiency of hashing methods for approximate nearest neighbor, GHashing demonstrates significantly better performance compared to state-of-the-art methods. “Explanations that Matter through Meta-Provenance” KDD-2020-Tutorial: Automated Recommender System. Graph similarity search is an important data mining problem. We have a fantastic lineup lecture-style tutorials to be held in conjunction with KDD 2020. In machine learning and data mining these interactions are usually formulated as dependency and correlation among system variables. We invite submission of papers and posters of two to ten pages (including references), Big and small stories surrounding a police station in Berlin-Kreuzberg. Toggle navigation KDD 2020. Click to play video . “Parameterized Correlation Clustering in Hypergraphs and Bipartite Graphs” Specifically, the first study of the adversarial attacks against DRL interpretations was introduced. Jingbo Shang, assistant professor of Computer Science at University of California at San Diego, earned runner-up for his thesis, "Constructing and Mining Heterogeneous Information Networks from Massive Text." Sign up Why GitHub? Papers will be judged by their relevance to the workshop, especially to the main themes identified above, and their potential to generate discussion. "Without their dedication and belief in our mission, we would never have been able to create such a vibrant data science community, let alone organize a conference of this magnitude and quality year after year.". Abstract: Kate Davies Designs (KDD) was established by Kate Davies in 2010, when a stroke at the age of 36 ended her career as a literary academic. To join the workshop click on this zoom meeting link Dr. Amanda Stent works on text analytics and discourse processing as NLP architect at Bloomberg LP. KDD 2020 will feature four keynote talks, 18 applied data science invited talks, 217 accepted research papers grouped into 43 sessions for oral presentations, workshops and tutorials. KDD is the premier international conference that brings together researchers and practitioners from both academia and industry to deep-dive into novel ideas, latest research results and share in-the-trenches experiences and innovations. KDD 2020 is looking to be an amazing year. MLG 2020, 16th International Workshop on Mining and Learning with Graphs, co-located with KDD 2020, San Diego, CA, USA Submissions Due - June 15, 2020 (11: 59 P.M. AoE) Notification - June 30, 2020 Camera Ready Version of Papers Due - July 10, 2020 KDD Converse half day Workshop - August 24, 2020 We invite quality research contributions, position and opinion papers addressing relevant challenges in the domain of conversational systems. Nintendo Switch Pro Controller Review - More comfortable vs. Joycons . KDD, 2011. Research from different Conversational systems have improved dramatically recently and are gaining adoption in industries such as e-commerce, banking, finance and real estate to name a few. ACM provides the computing field's premier Digital Library and serves its members and the computing profession with leading-edge publications, conferences, and career resources. Jie Tang, Jing Zhang, Limin Yao, Juanzi Li, Li Zhang and Zhong Su received the inaugural Test of Time Award for Applied Science in recognition of their study of mining academic social networks published in the 2008 peer-reviewed paper, "ArnetMiner: Extraction and Mining of Academic Social Networks." Click to play video . ACM is committed to creating an environment that welcomes new ideas and perspectives, and where hostility or other antisocial behaviors are not tolerated. In this talk, I will highlight the complexity of building Aug 24, 2020. Advances in Recommender Systems: From Multi-stakeholder Marketplaces to Automated RecSys. More recently, he cofounded SambaNova systems based, in part, on his work on accelerating machine learning. Motivated by this experience, we built Bootleg, a clean-slate, open-source, self-supervised system to improve tail performance using a simple transformer-based architecture. “A Look at State-Space Multi-Taper Time-Frequency Analysis” Can one build a knowledge graph (KG) for all products in the world? Christopher (Chris) Ré is an associate professor in the Department of Computer Science at Stanford University. Ang Li , Huanrui Yang, Yiran Chen, Duke University; Yixiao Duan, Jianlei Yang, Beihang University The Google research team investigates sampled metrics in more detail and shows that they are inconsistent with their exact version, in the sense that they do not persist relative statements, e.g., recommender A is better than B, not even in expectation. The new model can solve both supervised and unsupervised learning problems. Although graphs have been ubiquitous in AI and knowledge discovery … and text-to-speech synthesis have accelerated the adoption of ACM, the world's largest educational and scientific computing society, delivers resources that advance computing as a science and a profession. Hidden Factors and Hidden Topics: Understanding Rating Dimensions with Review Text. XKDD 2020 considers the author list submitted with the paper as final. However, existing methods either heavily rely on high-quality user generated content (including user profiles) or suffer from data insufficiency problem if only focusing on network topology, which brings researchers into an insoluble dilemma of model selection. Item recommendation algorithms are evaluated using ranking metrics that depend on the positions of relevant items. KDD’s Applied Data Science Invited Talks feature highly influential speakers who have directly contributed to successful data mining applications in finance, healthcare, bioinformatics, public policy, infrastructure, telecommunications, social media and computational advertising. SIGs offer a wealth of conferences, publications and activities focused on specific computing sub-disciplines. Unfortunately, there is no definitive data-driven study on analyzing factors associated with SUD among homeless youth. KDD 2020 will feature four keynote talks, 18 applied data science invited talks, 217 accepted research papers grouped into 43 sessions for oral presentations, workshops and tutorials. Vespignani will review and discuss recent results and challenges in the area and focus on ongoing work aimed at responding to the COVID-19 pandemic. These explanations convey the details of analytic steps and the original data used in an analysis. Then, we discuss some complexities of modeling trading conversations, as well as our work on entity recognition and slot filling, intent recognition and conversation disentanglement. Compared to a regular neural network of the same size, CRBM-DNN has fewer parameters so they require fewer training samples. The research group from Duke University presents TIPRDC, a task-independent privacy-respecting data crowdsourcing framework with anonymized intermediate representation. Check back as we get closer to the conference for more detailed program information. In this talk, Gil will discuss the need for explanations that provide the context and rationale for how the data analysis process was designed. Lon.TV . Richard Barnes, UC Berkeley; Senaka Buthpitiya, James Cook, Alex Fabrikant, Andrew Tomkins, Fangzhou Xu, Google Research Code review → Project ... KDD Cup 2020 Challenges for Modern E-Commerce Platform: Multimodalities Recall first place 135 stars 46 forks Star Watch Code; Issues 0; Pull requests 0; Actions; Projects 0; Security; Insights master. ACM, the Association for Computing Machinery, is the world's largest educational and scientific computing society, uniting educators, researchers and professionals to inspire dialogue, share resources and address the field's challenges. enterprise-grade conversational system to deliver an effective and August 2020. 1 branch 0 tags. Virtual Conference. designing an efficient dialog management for those use cases, New this year, the Rising Star Award celebrates individual work done in the first five years after earning a PhD. Even so, architecting and engineering a complex “A Novel Deep Learning Model by Stacking Conditional Restricted Boltzmann Machine and Deep Neural Network” She will also illustrate with examples from several domains the kinds of explanations that can be generated from meta-provenance and discuss important areas of future work. Motivated by applications in community detection and dense subgraph discovery, this paper considers new clustering objectives in hypergraphs and bipartite graphs. Members enjoy exclusive offers and discounts on IT industry certifications and vendor-specific training.