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
[unable to retrieve full-text content]Third year Ph.D student David Abel, of Brown University, was in attendance at NIP 2017, and he labouriously compiled and formatted a fantastic 43-page set of notes for the rest of us. Get them here.
Original Post: NIPS 2017 Key Points & Summary Notes
[unable to retrieve full-text content]AI NEXTCon Seattle brings together top technical engineers, practitioners, influential technologists and data scientists to share solutions and practical experiences in machine/deep learning, computer vision, speech recognition and NLP.
Original Post: 4th AI NEXTCon Conf. Seattle, Jan 17-19, Early bird (50% off) ends soon
[unable to retrieve full-text content]Here is a selection of some of the highest rated ODSC talks of 2017 as voted by our attendees. Also check out our series of bi-weekly data science and AI webinars. Attend ODSC East 2018 in person and save 70% with code KDNUGGETS!
Original Post: Watch the Best of Open Data Science Talks of 2017 for Free
Posted by Vincent Vanhoucke, Principal Scientist, Google Brain Team and Melanie Saldaña, Program Manager, University RelationsWhether in the form of autonomous vehicles, home assistants or disaster rescue units, robotic systems of the future will need to be able to operate safely and effectively in human-centric environments. In contrast to to their industrial counterparts, they will require a very high level of perceptual awareness of the world around them, and to adapt to continuous changes in both their goals and their environment. Machine learning is a natural answer to both the problems of perception and generalization to unseen environments, and with the recent rapid progress in computer vision and learning capabilities, applying these new technologies to the field of robotics is becoming a very central research question.This past November, Google helped kickstart and host the First Conference on Robot Learning (CoRL)…
Original Post: A Summary of the First Conference on Robot Learning
Posted by Christian Howard, Editor-in-Chief, Research CommunicationsThis week, Long Beach, California hosts the 31st annual Conference on Neural Information Processing Systems (NIPS 2017), a machine learning and computational neuroscience conference that includes invited talks, demonstrations and presentations of some of the latest in machine learning research. Google will have a strong presence at NIPS 2017, with over 450 Googlers attending to contribute to, and learn from, the broader academic research community via technical talks and posters, workshops, competitions and tutorials.Google is at the forefront of machine learning, actively exploring virtually all aspects of the field from classical algorithms to deep learning and more. Focusing on both theory and application, much of our work on language understanding, speech, translation, visual processing, and prediction relies on state-of-the-art techniques that push the boundaries of what is possible. In all of those tasks and…
Original Post: Google at NIPS 2017
[unable to retrieve full-text content]This year, the ODSC West was held at the Hyatt Regency San Francisco Airport, from November 2 to 4. I am, attempting here, to give you a snapshot tour of what I experienced.
Original Post: Key Takeaways from Open Data Science Conference (ODSC) West 2017
[unable to retrieve full-text content]Highlights and key takeaways from day 2 of AI Conference San Francisco 2017, including current state review, future trends, and top recommendations for AI initiatives.
Original Post: Key Takeaways from AI Conference in San Francisco 2017 – Day 2
[unable to retrieve full-text content]Highlights and key takeaways from day 1 of AI Conference San Francisco 2017, including current state review, future trends, and top recommendations for AI initiatives.
Original Post: Key Takeaways from AI Conference in San Francisco 2017 – Day 1
Posted by Bryan Perozzi, Research Scientist, NYC Algorithms and Optimization TeamThe 23rd ACM conference on Knowledge Discovery and Data Mining (KDD’17), a main venue for academic and industry research in data science, information retrieval, data mining and machine learning, was held last week in Halifax, Canada. Google has historically been an active participant in KDD, and this year was no exception, with Googlers’ contributing numerous papers and participating in workshops.In addition to our overall participation, we are happy to congratulate fellow Googler Bryan Perozzi for receiving the SIGKDD 2017 Doctoral Dissertation Award, which serves to recognize excellent research by doctoral candidates in the field of data mining and knowledge discovery. This award was given in recognition of his thesis on the topic of machine learning on graphs performed at Stony Brook University, under the advisorship of Steven Skiena. Part of…
Original Post: Google at KDD’17: Graph Mining and Beyond