The Fifth Elephant 2015
A conference on data, machine learning, and distributed and parallel computing
Machine Learning, Distributed and Parallel Computing, and High-performance Computing are the themes for this year’s edition of Fifth Elephant.
The deadline for submitting a proposal is 15th June 2015
We are looking for talks and workshops from academics and practitioners who are in the business of making sense of data, big and small.
Track 1: Discovering Insights and Driving Decisions
This track is about general, novel, fundamental, and advanced techniques for making sense of data and driving decisions from data. This could encompass applications of the following ML paradigms:
- Statistical Visualizations
- Unsupervised Learning
- Supervised Learning
- Semi-Supervised Learning
- Active Learning
- Reinforcement Learning
- Monte-carlo techniques and probabilistic programming
- Deep Learning
Across various data modalities including multi-variate, text, speech, time series, images, video, transactions, etc.
Track 2: Speed at Scale
This track is about tools and processes for collecting, indexing, and processing vast amounts of data. The theme includes:
- Distributed and Parallel Computing
- Real Time Analytics and Stream Processing
- MapReduce and Graph Computing frameworks
- Kafka, Spark, Hadoop, MPI
- Stories of parallelizing sequential programs
- Cost/Security/Disaster Management of Data
Commitment to Open Source
HasGeek believes in open source as the binding force of our community. If you are describing a codebase for developers to work with, we’d like it to be available under a permissive open source license. If your software is commercially licensed or available under a combination of commercial and restrictive open source licenses (such as the various forms of the GPL), please consider picking up a sponsorship. We recognize that there are valid reasons for commercial licensing, but ask that you support us in return for giving you an audience. Your session will be marked on the schedule as a sponsored session.
Workshops
If you are interested in conducting a hands-on session on any of the topics falling under the themes of the two tracks described above, please submit a proposal under the workshops section. We also need you to tell us about your past experience in teaching and/or conducting workshops.
Hosted by
The Fifth Elephant - known as one of the best data science and Machine Learning conference in Asia - has transitioned into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more
AC
Anand Chandrasekaran
@madstreetden
Keeping Moore's law alive: Neuromorphic computing
Submitted Jun 15, 2015
Section:
Full Talk
Technical level:
Beginner
This talk explores the implications of Neuromorphic Engineering, or ‘building brains in silicon’, on the development of extremely parallel compute techniques such as deep learning.
Outline
Moore’s law is a term coined by Carver Mead, a Caltech professor who is also the father of Neuromorphic Engineering. It refers to the observation, now more hope than reality, that advances in technology will allow a doubling of compute capability in silicon every 18 months. Recent advances in the use of highly parallel compute methods, that are loosely based on neural systems in our brain, are changing how compute is accomplished. These techniques, collectively termed deep learning networks, burst onto to the world because of one reason: the ability to perform lots of parallel computations on graphics cards. However, it is in truly custom hardware, such as that pioneered by the Neuromorphic community that we will find the salvation of Moore’s law. When we blend powerful compute techniques with custom silicon architectures, we can keep the hope alive of continuing to double the compute capability of the world.
If you are in the space of deep learning or have heard about how GPUs have revolutionalized high performance computing, this talk will take you to the extreme bleeding edge of that world.
Requirements
None, I will keep transistor physics out of this.
Speaker bio
The speaker was one of the creators of Neurogrid, a system built in Stanford that until recently was the largest Neuromorphic system in the world. He is also the CTO and Founder of Mad Street Den, a computer vision and AI startup based out of Chennai.
Links
- https://in.linkedin.com/in/anandchandrasekaran
- www.madstreetden.com
Comments
Hosted by
The Fifth Elephant - known as one of the best data science and Machine Learning conference in Asia - has transitioned into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more
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