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.
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.
Designing distributed components in a multi tenant architecture
The objective of this talk is to go over design of distributed search components in a Multi-tenant architecture spanning across geographies and deals with challenges around custom ranking, tenant specific configurations and dynamic ranking elements.
A global search infrastructure that serves millions of queries with SLA’s of the order of milliseconds is non-trivial to build. Throw in multiple tenants with diverse requirements and we have a huge complex system that needs to handle myriad configurations, ranking components, dynamic elements and what not. At stake of this complex system are stability, real time latencies, configurability, customization and scalability.
This talk will go over Bloomreach’s innovative search solution that addresses these seemingly impossible but utterly real requirements and the challenges involved in developing distributed search applications in a multi tenant scenario.
Some understanding of a search subsystem and how ranking works
Suchi and Ronak have been working on Search platform scaling for Bloomreach’s big data. Relevant experience includes distributed computing, data modelling, statistical machine learning, data ingestion, user data and personalization.
Ronak has an M.Tech, Computer Science from IIT, Bombay and BE from GCET. He worked at Adobe as a computer scientist for 7 years before joining Bloomreach.
Prior to Bloomreach, Suchi was a founding member of the Android framework team and has made extensive contributions to the Android framework.Suchi has an MS from University of Cincinnati and BE from BITS, Pilani. Her prior work experience includes working in companies like Google, Motorola and IBM Almaden.