Call For Speakers- 2017 Events

MLconf is calling for speakers for 2017 events!

  • Algorithms that have graduated academic conferences such as NIPS, ICML, etc and have proven to be effective, robust and scalable in production
  • Novel data science practices, such as data transformations, new data sources, novel representations, etc
  • Machine Learning/AI case studies (Lessons learned), demonstrating challenges in the wild and how to handle them in a new way
  • New platforms, tools for machine learning. Emphasis should be given on the technical challenges, benchmarks and motivation for the development
  • New business practices, for managing, growing data science teams and expanding machine learning to new domains
  • Tutorials and novel ways of presenting and simplifying machine learning domains, including: deep learning, kernel methods, bayesian nonparametrics, tensor algebra, etc
  • Up and coming areas of machine learning that you think will dominate the industry in the future, such as probabilistic programming etc.

Topics we’re looking for:

  • Natural Language Processing
  • Deep Learning
  • Reinforcement Learning
  • Neural Turing Machines/Neural Theorem Provers
  • Generative Models
  • Probabilistic Programming
  • Probabilistic Logic and Reasoning
  • Chatbots/ ALL Bots
  • Bayesian Inference
  • One Shot Learning
  • Markov Logic Networks
  • Structure Learning
  • Synthetic Art, Biology
  • Ethics in Machine Learning
  • Sketching Randomized Algorithms
  • Game Theory
  • Community Detection
  • Large-Scale Clustering
  • Time Series
  • Image Analysis
  • Bayesian Non-Parametrics
  • Topic Models

Submit Abstract – The deadline schedule is as follows:

  • MLconf NYC  – 01/31/2017 Submission Deadline
  • MLconf SEA  – 03/01/2017 Submission Deadline
  • MLconf ATL   – 06/01/2017 Submission Deadline
  • MLconf SF    – 07/01/2017 Submission Deadline

The selection of the presentation will be based on:

  1. Clarity and novelty of the presentation
  2. Diversity of the topics for the conference
  3. Speaker’s experience in the industry