The Fifth Elephant 2016

India's most renowned data science conference

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:

  1. Deep Learning
  2. Text Mining
  3. Computer Vision
  4. Social Network Analysis
  5. Large-scale Machine Learning (ML)
  6. Internet of Things (IoT)
  7. Computational Biology
  8. ML in healthcare
  9. ML in education
  10. ML in energy and ecology
  11. ML in agriculrure
  12. Analytics for emerging markets
  13. ML in e-governance
  14. ML in smart cities
  15. 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 - 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

Aditya Ramana Rachakonda

@arrac

Allocation and Forecasting in Guaranteed Delivery of Advertisements

Submitted Jul 19, 2016

Guaranteed delivery (GD) of advertisements helps brands book advertisement views of niche audience segments well in advance. To enable this, we need to create an intelligent system which allows for targeting of users, forecasting supply, optimally booking campaigns, allocating campaigns to users, pricing the guarantees and penalties correctly.

Outline

In this talk, we will discuss the following:

  1. Allocation: In GD, as advertisements don’t compete on bids, we allocate advertisements to user-views such that we deliver on the guarantees, while keeping the advertiser’s interests (reaching the right set of users) intact. This problem is modelled as constrained optimization over bipartite graph of advertisements and audience segments.
  2. Forecasting: We need to know the number of views in the future that we get from different audience-segments. We model views in an audience segment, as a time series and various external inputs as exogenous variables which affect the time series. We will briefly describe the various algorithms and processes that we follow to enable forecasting.

Speaker bio

Aditya Rachakonda is a Data Scientist at Flipkart Ads. He is currently working on problems in advertisement optimization. Earlier, he was a Research Scientist at Big Data Labs in American Express. He has experience in machine learning, text mining and getting insights from short and noisy texts. Aditya is a PhD in Computer Science from IIIT Bangalore and his research interests include semantics in text and information retrieval.

Slides

https://www.dropbox.com/s/6pfs713qgfnfada/Allocation%20and%20Forecasting%20%20in%20Guaranteed%20Delivery%20%20of%20Advertisements.pdf?dl=0

Comments

{{ gettext('Login to leave a comment') }}

{{ gettext('Post a comment…') }}
{{ gettext('New comment') }}
{{ formTitle }}

{{ errorMsg }}

{{ gettext('No comments posted yet') }}

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