by The Fifth Elephant

Deep Learning Conf 2016

A conference on deep learning.

Deep Learning Conf 2016

A conference on deep learning.

by The Fifth Elephant
date_range

Date

01 Jul 2016, Bangalore

place

Venue

CMRIT College

About

Deep Learning is a new area of research that is getting us closer in achieving one of the primary objectives of Machine Learning – Artificial Intelligence.
It is used widely in the fields of Image Recognition, Natural Language Processing (NLP) and Video Classification.

Format

Deep Learning Conf is a single day conference followed by workshops on the second day. The conference will have full, crisp and lightning talks from morning to evening. The workshops on the next day will introduce participants to neural networks followed by two tracks of three-hour workshops on NLP and Computer Vision / AI. Participants can join either one of the two workshop tracks.

Tracks

We are looking for talks and workshops from academics and practitioners of Deep Learning on the following topics:

  • Applications of Deep Learning in software.
  • Applications of Deep Learning in hardware.
  • Conceptual talks and cutting edge research on Deep Learning.
  • Building businesses with Deep Learning at the core.

We are inviting proposals for:

  • Full-length 40 minute talks.
  • Crisp 15-minute talks.
  • Lightning talks of 5 mins duration.

Selection process

Proposals will be filtered and shortlisted by an Editorial Panel. Along with your proposal, you must share the following details:

  • Links to videos / slide decks when submitting proposals. This will help us understand your past speaking experience.
  • Blog posts you may have written related to your proposal.
  • Outline of your proposed talk – either in the form of a mind map or a text document or draft slides.

If your proposal involves speaking about a library / tool / software that you intend to open source in future, the proposal will be considered only when the library / tool / software in question is made open source.

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

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

  • Proposal submission deadline: 31 May 2016
  • Schedule announcement: 15 June 2016
  • Conference dates: 1 July 2016

Venue

CMR Institute of Technology, Bangalore

Contact

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

Venue



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All proposals

Confirmed sessions

Expresso - A user-friendly tool for Deep Learning

Jaley Dholakiya (@jaleydholakiya)

  • Crisp talk
  • Beginner
  • 1 upvotes
  • 0 comments
  • Sat, 11 Jun
  • play_arrow
  • slideshow

Deep Learning for Computer Vision

Anand Chandrasekaran (@anandchandrasekaran)

  • Workshop
  • Intermediate
  • 4 upvotes
  • 0 comments
  • Wed, 8 Jun

Deep learning for computational pathology

Neeraj Kumar (@neerajkumar89)

  • Full talk
  • Intermediate
  • 2 upvotes
  • 0 comments
  • Mon, 6 Jun

Recent advancements in Deep Learning techniques using GPUs.

Sundara R Nagalingam (@nsundarrl)

  • Sponsored talk
  • Intermediate
  • 0 upvotes
  • 0 comments
  • Tue, 31 May

Slot-Filling in Conversations with Deep Learning

Nishant Sinha (@ekshaks)

  • Crisp talk
  • Intermediate
  • 5 upvotes
  • 0 comments
  • Tue, 31 May

Making Deep Neural Networks smaller and faster

Suraj Srinivas (@surajsrinivas)

  • Crisp talk
  • Intermediate
  • 5 upvotes
  • 0 comments
  • Tue, 31 May

Applied Deep Learning

Abhishek Thakur (@abhishekthakur)

  • Full talk
  • Intermediate
  • 16 upvotes
  • 2 comments
  • Sun, 29 May

Challenges & Implications of Deep Learning in Healthcare

Suthirth Vaidya (@suthirth)

  • Full talk
  • Intermediate
  • 5 upvotes
  • 0 comments
  • Tue, 24 May

Deep Dive Into Building Chat-bots Using Deep Learning

Vijay Gabale (@vijaygabale)

  • Full talk
  • Intermediate
  • 12 upvotes
  • 0 comments
  • Mon, 23 May

Deep learning: A convoluted overview with recurrent themes and beliefs.

Anand Chandrasekaran (@anandchandrasekaran)

  • Full talk
  • Intermediate
  • 2 upvotes
  • 0 comments
  • Fri, 20 May

Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimation

Arjun Jain (@stencilman)

  • Crisp talk
  • Advanced
  • 7 upvotes
  • 1 comments
  • Wed, 11 May

Residual Learning and Stochastic Depth in Deep Neural Networks

pradyumna reddy (@pradyu1993)

  • Crisp talk
  • Intermediate
  • 12 upvotes
  • 0 comments
  • Fri, 6 May

Introduction to Deep Learning for Natural Language Processing

Nischal HP (@nischalhp)

  • Workshop
  • Intermediate
  • 13 upvotes
  • 0 comments
  • Fri, 29 Apr
  • slideshow

Unconfirmed proposals

Object Detection using deep convolutional network

Koustubh Sinhal (@koustubh)

  • Crisp talk
  • Advanced
  • 2 upvotes
  • 1 comments
  • Tue, 31 May

Text made Understandable by Machines

Ashish Kumar (@ashish122)

  • Full talk
  • Intermediate
  • 28 upvotes
  • 2 comments
  • Mon, 30 May

Deep learning for Image and Feature recognition

Hemant Jain (@jainhemant)

  • Full talk
  • Intermediate
  • 31 upvotes
  • 2 comments
  • Mon, 30 May

Debugging deep nets

Vivek Gandhi (@vivgandhi)

  • Full talk
  • Intermediate
  • 12 upvotes
  • 1 comments
  • Sun, 29 May

Sequence learning

Rajarshee Mitra (@rajarsheem)

  • Full talk
  • Intermediate
  • 15 upvotes
  • 0 comments
  • Sat, 28 May

Deep Learning with MATLAB : Real-time Object Recognition and Transfer Learning

Sunita John (@sunjoh)

  • Crisp talk
  • Intermediate
  • 7 upvotes
  • 0 comments
  • Thu, 26 May

Learning to play games / Deep Reinforcement Learning

Utkarsh Sinha (@liquidmetal)

  • Full talk
  • Intermediate
  • 12 upvotes
  • 0 comments
  • Wed, 25 May

Building DeepNets using Keras

Anuj Gupta (@anuj-gupta)

  • Workshop
  • Intermediate
  • 11 upvotes
  • 0 comments
  • Tue, 24 May

Activations, Objectives and Optimisers - Nuts & Bolts of a DeepNet

Anuj Gupta (@anuj-gupta)

  • Full talk
  • Intermediate
  • 12 upvotes
  • 0 comments
  • Tue, 24 May

Events Build Build 2016 Microsoft Cognitive Services: Build smarter and more engaging experiences

Abhishek Narain (@narainabhishek)

  • Full talk
  • Beginner
  • 1 upvotes
  • 0 comments
  • Mon, 23 May

Automated Interior Designing using Bayesian networks

Aakanksha Bapna (@aakankshabapna)

  • Crisp talk
  • Intermediate
  • 5 upvotes
  • 0 comments
  • Mon, 16 May
  • play_arrow

Debugging DeepNets - practitioners black book

Anuj Gupta (@anuj-gupta) (proposing)

  • Full talk
  • Advanced
  • 4 upvotes
  • 0 comments
  • Fri, 13 May

Practical Deep Learning

Arthi Venkataraman (@arthi)

  • Full talk
  • Intermediate
  • 3 upvotes
  • 0 comments
  • Fri, 15 Apr
  • slideshow