[Ml-stat-talks] FW: ICML 2016 Workshop: On-device Intelligence

Amir Ali Ahmadi a_a_a at princeton.edu
Mon May 2 21:40:46 EDT 2016


Of possible interest.
________________________________
From: Vikas Sindhwani [sindhwani at google.com]
Sent: Monday, May 02, 2016 9:36 PM
To: Amir Ali Ahmadi; anirudha at mit.edu
Subject: ICML 2016 Workshop: On-device Intelligence

Hi Amirali, Anirudha:

We are running this workshop at ICML this year. If would be great if you could circulate the CfP in the Control /Optimization/Robotics communities. The deadline is May 8th - which is short - but its a good venue for late breaking 4 page papers for all things related to real-time learning/control/optimization on emerging mobile systems.

best,
Vikas

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ICML 2016 Workshop: On-device Intelligence

New York City, June 24 2016
Website: https://sites.google.com/site/ondeviceintelligence/icml2016


Important dates:

        Submission deadline: Extended to May 8 2016
        Author Notification: May 13 2016


Submission Instructions:

        4 pages (excluding references).
        Papers must be formatted using the ICML template (bit.ly/1owUXXI<http://bit.ly/1owUXXI>)
        Submit online at: https://cmt3.research.microsoft.com/ONDI2016
        Limited Student Travel Grants will be available for selected papers.


Consumer adoption of mobile devices has created a new normal in computing: there are now more mobile devices on the planet than people, and exabytes of mobile data per month now dominates global internet traffic. As computing systems, these pocket-sized devices are more powerful in many ways than vintage supercomputers. They come packed with an ever growing array of sensors. They are “always-on”, and becoming increasingly capable of rich contextual understanding and natural interaction with their users.


This workshop will focus on research themes emerging at the intersection of machine learning and mobile systems. The topics of interest range from the design of new machine learning algorithms under storage and power constraints, new on-device learning mechanisms, the interaction between devices and cloud resources for privacy-aware distributed training, and opportunities for machine learning in the nascent area of “Internet of Things.” The scope of the workshop also extends to real-time learning and optimization in the context of novel form-factors: wearable computers, home intelligence devices, and consumer robotics systems. We are interested in hardware-software co-design for mobile machine learning applications to uncover opportunities for low-power hardware design for enabling learning in small form-factor, energy-constrained computing environments.


Topics of Interest:

        On-device learning and inference
        Real-time Optimization
        Online learning, Adaptation and Personalization
        Devices and the Cloud
        Novel device form-factors
        Novel Mobile Applications
        Hardware-Software Co-design


Workshop format:

        1-day workshop comprising of keynote presentations, invited and contributed talks, and a poster session


Invited speakers:

        Hartwig Adams.................(Google)
        Tanzeem Choudhury …….(Cornell)
        Scott Gray ………………... (Nervana systems)
        Scott Kuindersma ……….. (Harvard)
        H. Brendan McMahan…....(Google)
        Vivienne Sze …………….. (MIT)
        Ambuj Tewari …………….. (University of Michigan)
        Naveen Verma ……………(Princeton)


Workshop organizers:

        Keith Bonawitz …………… (Google)
        Suyog Gupta ……………... (IBM Research)
        Daniel Ramage …………… (Google)
        Vikas Sindhwani …………. (Google)
        Sachin Talathi …………….. (Qualcomm)
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