Nov 2019
18 Mon
19 Tue
20 Wed
21 Thu
22 Fri
23 Sat 08:30 AM – 05:30 PM IST
24 Sun
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Accepting submissions till 01 Nov 2019, 04:20 PM
Nov 2019
18 Mon
19 Tue
20 Wed
21 Thu
22 Fri
23 Sat 08:30 AM – 05:30 PM IST
24 Sun
Accepting submissions till 01 Nov 2019, 04:20 PM
##About the 2019 edition:
The schedule for the 2019 edition is published here: https://hasgeek.com/anthillinside/2019/schedule
The conference has three tracks:
#Who should attend Anthill Inside:
Anthill Inside is a platform for:
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#Sponsors:
Sponsorship slots for Anthill Inside 2019 are open. Click here to view the sponsorship deck.
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Nishant Oli
User behaviour varies with their current location, as a consequence their engagement with online media (say Ads) varies with where they are; Knowing the type of location can help us target the user better and recommend better.
After the advent of GPS technology, it is easy and inexpensive to get location information from devices, but the data is often sparse for an ad network as they only get a partial view of user data. We present a novel algorithm to classify locations using the GPS data along with anonymous ad-request data such that it performs optimally with sparse GPS signals with no supervised data at all.
Our results show that the algorithm has a better prediction accuracy compared to existing methods and correlates well with the user behaviours.
Nishant Oli is a Data Scientist at InMobi where he works on user inferences and geo analytics. He graduated with a Master’s degree from IIIT Bangalore. Previously he worked at Siemens Corporate Research & Mazumdar Shaw Center of Translational Research in the field of Meta-Learning for computer vision and biomedical computer vision.
Nov 2019
18 Mon
19 Tue
20 Wed
21 Thu
22 Fri
23 Sat 08:30 AM – 05:30 PM IST
24 Sun
Accepting submissions till 01 Nov 2019, 04:20 PM
Hosted by
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