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.
To explore the key building blocks of Artificial Intellgence: “Understanding”, “Learning”, “Thinking”, and “Creativity”.
Ever since the dawn of civilization humans have been trying to “extend” themselves through “machines” - tools to hunt animals stronger than us, telescopes to see farther than our eyes, cranes to lift more than our hands, cars to move faster than our legs, and computers to store and process more information than ever before. The epitome of this “extension”, the dream (or nightmare) of Artificial Intelligence, is to create a “Thinking Machine” that replicates or even surpasses our brain’s ability to:
(a) “Understand” the data it receives,
(b) “Learn” compositional and causal structures in it,
(c) “Reason” over these structures, and even
(d) “Create” new data using the “model” of the world it has learnt.
Such a machine could, for example, have a human like conversation, solve complex problems, predict the next scene in a video, find a cure for cancer, prove Fermat’s last theorem, or even create art or poetry some day. Advances made in machine learning, natural language understanding, speech recognition and synthesis, computer vision, and deep learning have brought us to the brink of such a possibility! We can already see glimpses of such “thinking machines” - the self driving cars, the jeopardy winning Watson, and the recent “paintings” created from deep vision networks (http://googleresearch.blogspot.in/2015/06/inceptionism-going-deeper-into-neural.html).
In this talk, we will explore both the philosophical and algorithmic aspects of building such a “Thinking Machine”. More specifically, we will explore some hypothese on how we:
(a) learn, represent, and disambiguate senses of words without knowing the grammar of a language?
(b) analyze knowledge from langauge and synthesize language from knowledge?
(c) reason over this knowledge to solve complex problems and innovate new ideas?
(d) can build better machine translation and conversation systems using some of these building blocks?
An Open Mind, a “healthy disregard for the impossible”, and an urge to remove the word “fiction” from “science fiction”!