A Real World Reinforcement Learning Research Program

A Real World Reinforcement Learning Research Program We are hiring for reinforcement learning related research at all levels and all MSR labs. If you are interested, apply, talk to me at COLT or ICML, or email me. More generally though, I wanted to lay out a philosophy of research which differs from (and plausibly improves on) the current prevailing mode. Deepmind and OpenAI have popularized an empirical approach where researchers modify algorithms and test them against simulated environments, including in self-play. They’ve achieved significant success in these simulated environments, greatly expanding the reportoire of ‘games solved by reinforcement learning’ which consisted of the singleton backgammon when I was a graduate student. Given the ambitious goals of these organizations, the more general plan seems to be “first solve games, then solve real problems”. There are some weaknesses to this approach, which…
Original Post: A Real World Reinforcement Learning Research Program

Announcing Microsoft Research Open Data, a cloud hosted platform for sharing datasets

[unable to retrieve full-text content]Microsoft announces Microsoft Research Open Data, datasets representing many years of data curation and research efforts by Microsoft that were published as research outcomes.
Original Post: Announcing Microsoft Research Open Data, a cloud hosted platform for sharing datasets

Monash University: Research Fellow – AI Optimisation Group

[unable to retrieve full-text content]Seeking an enthusiastic researcher with solid skills in any of the following areas: constraint programming, mixed integer programming, SAT and SAT modulo theories, modelling languages and program analysis, to work on new approaches to modelling and solving discrete optimisation problems.
Original Post: Monash University: Research Fellow – AI Optimisation Group

University of Applied Sciences of Western Switzerland: Sr Research Data Scientist (Medical Scheduling)

[unable to retrieve full-text content]Seeking a senior research data scientist to participate in the “Optimizing Operating Rooms and Care Services using Deep Reinforcement Learning” project.
Original Post: University of Applied Sciences of Western Switzerland: Sr Research Data Scientist (Medical Scheduling)

University of Applied Sciences of Western Switzerland: Sr Research Data Scientist (Fraud Detection)

[unable to retrieve full-text content]Seeking a senior research data scientist to participate to the AFFUT (Advanced Analytics for Fraud Detection) project.
Original Post: University of Applied Sciences of Western Switzerland: Sr Research Data Scientist (Fraud Detection)

University of Applied Sciences of Western Switzerland: Sr Research Data Scientist (Fraud Detection)

[unable to retrieve full-text content]Seeking a senior research data scientist to participate to the AFFUT (Advanced Analytics for Fraud Detection) project.
Original Post: University of Applied Sciences of Western Switzerland: Sr Research Data Scientist (Fraud Detection)

Google at ICLR 2018

Posted by Jeff Dean, Google Senior Fellow, Head of Google Research and Machine IntelligenceThis week, Vancouver, Canada hosts the 6th International Conference on Learning Representations (ICLR 2018), a conference focused on how one can learn meaningful and useful representations of data for machine learning. ICLR includes conference and workshop tracks, with invited talks along with oral and poster presentations of some of the latest research on deep learning, metric learning, kernel learning, compositional models, non-linear structured prediction, and issues regarding non-convex optimization.At the forefront of innovation in cutting-edge technology in neural networks and deep learning, Google focuses on both theory and application, developing learning approaches to understand and generalize. As Platinum Sponsor of ICLR 2018, Google will have a strong presence with over 130 researchers attending, contributing to and learning from the broader academic research community by presenting papers and…
Original Post: Google at ICLR 2018

How to Make AI More Accessible

[unable to retrieve full-text content]I recently was a guest speaker at the Stanford AI Salon on the topic of accessiblity in AI, which included a free-ranging discussion among assembled members of the Stanford AI Lab. There were a number of interesting questions and topics, so I thought I would share a few of my answers here.
Original Post: How to Make AI More Accessible

Announcing the Google Cloud Platform Research Credits Program

Posted by Steven Butschi, Head of Higher Education, GoogleScientists across nearly every discipline are researching ever larger and more complex data sets, using tremendous amounts of compute power to learn, make discoveries and build new tools that few could have imagined only a few years ago. Traditionally, this kind of research has been limited by the availability of resources, with only the largest universities or industry partners able to successfully pursue these endeavors. However, the power of cloud computing has been removing obstacles that many researchers used to face, enabling projects that use machine learning tools to understand and address student questions and that study robotic interactions with humans, among many more.In order to ensure that more researchers have access to powerful cloud tools, we’re launching Google Cloud Platform (GCP) research credits, a new program aimed to support faculty in…
Original Post: Announcing the Google Cloud Platform Research Credits Program

Google’s Workshop on AI/ML Research and Practice in India

Posted by Pankaj Gupta and Anand Rangarajan, Engineering Directors, Google IndiaLast month, Google Bangalore hosted the Workshop on Artificial Intelligence and Machine Learning, with the goal of fostering collaboration between the academic and industry research communities in India. This forum was designed to exchange current research and industry projects in AI & ML, and included faculty and researchers from Indian Institutes of Technology (IITs) and other leading universities in India, along with industry practitioners from Amazon, Delhivery, Flipkart, LinkedIn, Myntra, Microsoft, Ola and many more. Participants spoke on the ongoing research and work being undertaken in India in deep learning, computer vision, natural language processing, systems and generative models (you can access all the presentations from the workshop here).Google’s Jeff Dean and Prabhakar Raghavan kicked off the workshop by sharing Google’s uses of deep learning to solve challenging problems and…
Original Post: Google’s Workshop on AI/ML Research and Practice in India