Jul 2016

25 Mon

26 Tue

27 Wed

28 Thu 08:30 AM – 06:25 PM IST

29 Fri 08:30 AM – 06:15 PM IST

30 Sat 08:45 AM – 05:00 PM IST

31 Sun 08:15 AM – 06:00 PM IST

Make a submission

NIMHANS Convention Centre

The Fifth Elephant is India’s most renowned data science conference. It is a space for discussing some of the most cutting edge developments in the fields of machine learning, data science and technology that powers data collection and analysis.

Machine Learning, Distributed and Parallel Computing, and High-performance Computing continue to be the themes for this year’s edition of Fifth Elephant.

We are now accepting submissions for our next edition which will take place in Bangalore 28-29 July 2016.

Tracks

We are looking for application level and tool-centric talks and tutorials on the following topics:

Deep Learning
Text Mining
Computer Vision
Social Network Analysis
Large-scale Machine Learning (ML)
Internet of Things (IoT)
Computational Biology
ML in healthcare
ML in education
ML in energy and ecology
ML in agriculrure
Analytics for emerging markets
ML in e-governance
ML in smart cities
ML in defense

The deadline for submitting proposals is 30th April 2016

Format

This year’s edition spans two days of hands-on workshops and conference. We are inviting proposals for:

Full-length 40 minute talks.
Crisp 15-minute talks.
Sponsored sessions, 15 minute duration (limited slots available; subject to editorial scrutiny and approval).
Hands-on Workshop sessions, 3 and 6 hour duration.

Selection process

Proposals will be filtered and shortlisted by an Editorial Panel. We urge you to add links to videos / slide decks when submitting proposals. This will help us understand your past speaking experience. Blurbs or blog posts covering the relevance of a particular problem statement and how it is tackled will help the Editorial Panel better judge your proposals.

We expect you to submit an outline of your proposed talk – either in the form of a mind map or a text document or draft slides within two weeks of submitting your proposal.

We will notify you about the status of your proposal within three weeks of submission.

Selected speakers must participate in one-two rounds of rehearsals before the conference. This is mandatory and helps you to prepare well for the conference.

There is only one speaker per session. Entry is free for selected speakers. As our budget is limited, we will prefer speakers from locations closer home, but will do our best to cover for anyone exceptional. HasGeek will provide a grant to cover part of your travel and accommodation in Bangalore. Grants are limited and made available to speakers delivering full sessions (40 minutes or longer).

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 licence. If your software is commercially licensed or available under a combination of commercial and restrictive open source licences (such as the various forms of the GPL), please consider picking up a sponsorship. We recognise 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.

Key dates and deadlines

Revised paper submission deadline: 17 June 2016
Confirmed talks announcement (in batches): 13 June 2016
Schedule announcement: 30 June 2016
Conference dates: 28-29 July 2016

Venue

The Fifth Elephant will be held at the NIMHANS Convention Centre, Dairy Circle, Bangalore.

Contact

For more information about speaking proposals, tickets and sponsorships, contact info@hasgeek.com or call +91-7676332020.

Hosted by

The Fifth Elephant

The Fifth Elephant - known as one the best #datascience and #machinelearning conference in Asia - is transitioning into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more

All submissions

Previous Next

This submission has been added to the schedule

Convolutional Neural Networks from the Other Side

Submitted Jul 9, 2016

Section: Full talk Technical level: Advanced

Deep Learning has made lot of progress in the last four years:

Newer ideas in architectures (module like architectures of NiN, GoogLenet, VGG Net etc),
Adverserial examples and its aftereffects in certain networks (impercetible but intentional changes to inputs causing highly confident wrong results),
Newer results with theoretical narratives (from invariant scattering transforms, group theoretic perspective, probablistic perpective, theoretical proofs on learnability of some of these models and many more).

among other things.

This talk is a roundup of some of the interesting ideas published at top tier academic conferences and Arxiv from last two years covering above themes. The main idea is to collate the various narratives to help create a story of why some of these models work.

Given the current rate of publications and the large areas of Computer Science, Electrical Engineering and Mathematics (and even Physics) that it covers; the attempt is to create a map of coherent ideas so that a practitioner can get a holistic picture of current results and directions and use them to debug/develop their models. Due to the broad nature of the topic and even broader selection of papers/topics available and limited time, only a representative portion will be covered.

Outline

What is new about CNN and what are some of the ingredients of the current revolution
Interesting results in CNN Architectures: NiN, GoogLeNet, VGG Net, Residual Nets, Spatial Transformer Networks
Why Theory ? Can’t we just take the hacker approach ?
Why Hierarchy ?
What is being learned ?
Why non-linearity ?
Can we make networks more interpretable ?

Speaker bio

Sumod Mohan holds an M.S degree and was purusing his Ph.D in Electrical Engineering from Clemson University with his broad interest in application of Graph Algorithms and Probablistic Graphical Models in Computer Vision. He decided to dropout and join HighlightCam (in California) where he led Computer Vision Algorithm Development. He currently leads the Computer Vision and Machine Learning Business Division (CVD) at Soliton Technologies. His experience spans Computer Vision, Machine Learning, 3D Vision, Deep Learning, Graph Algorithms, Probabilistic Graphical Models, Code Optimization and Parallelization and has worked in the Computer Vision and Machine Learning for past 10 years.