Towards Better Reinforcement Learning for High Stakes Domains
Speaker: Dr. Saleh Soltan, Princeton University
Speaker: Professor Hagit Messer, School of Electrical Engineering, Tel Aviv University, Israel
Charles Menguy, Senior Computer Scientist
As people now engage with digital properties using a myriad of devices such as laptops, smart phones, tablets, connected TVs and gaming consoles, the traditional cookie-based or device-level views of online user interaction are too narrow. Even when using a single device, a person may be assigned multiple IDs due to cookie churn or the use of different browsers. Marketers are looking through a fragmented lens and are spending their marketing dollars without understanding more than a fractional part of consumer interactions.
Amel Lageat, Senior Director, Consumer Business
Abstract: In a world of Infobesity, analysts, engineers, professionals, executive leaders, and people now have access to more data and analytics opportunities that we can ever make sense of. However, a genuine people centric approach can provide the sharpest guidance in designing relevant strategies and solutions: it makes data, models, and analytics more meaningful and purposeful, and also leads to marketing and commercial impact in global organizations.
Dr. Paul Ardis, Research Mission Leader at GE Global Research
Analytics are opening up new possibilities in the aviation sector as we think beyond the airplane during flight. Putting together GE’s expertise in AI for manufacturing and service with airline passenger analytics and intelligent supply chains, we are working towards a future where efficiency and agility is realized to maximize efficiency and minimize disruption.
Ron Daniel, Jessica Cox, Corey Harper
Most of the experimental results reported in scientific articles, and recorded in databases or in supplements to the article, are provided in tables. Unfortunately, the amazing recent progress in natural language understanding is of little help if we want to automatically understand those tables. Tables are, after all, not your grandmother’s natural language. Despite this, we believe significant progress can be made towards the goal of combining tables of related information into larger sets that can be analyzed, visualized, understood, and used as the basis for decisions. Elsevier Labs is prototyping tools to help guide people in the exploration of tables from many articles and the extraction and merging of the data they contain. This talk will show examples of what has been accomplished by manually merging such data. With those as examples of the desired outcomes, we will describe our experiments to duplicate such examples, the work flow in which they operate, and our most recent results.
Speaker: Dr. Martha Symko-Davies, Laboratory Program Manager, Energy Systems Integration (ESI), National Renewable Energy Laboratory (NREL)
Jeannette M. Wing
Avanessians Director of the Data Science Institute Professor of Computer Science Columbia University
Data for Good
Bloomberg Center, Cornell Tech
2 West Loop Road
New York, NY 10044