MLconf gathers machine learning & AI enthusiasts from a broad range of industries and academic backgrounds to share new tools, tricks, platforms, algorithms and methods with a broad audience of practitioners. Each presentation offers an educational component to be shared with the community, in which specific algorithms and techniques can be shared and new applications of such are inspired.
- Algorithms that have graduated from an academic/theory state and have proven to be effective, robust and scalable in production within industry application
- Machine Learning/AI examples of specific challenges faced within current industry and how teams have found success by applying new algorithms & techniques or by applying tweaks to existing practices for optimal outcomes
- New platforms, tools for machine learning. Emphasis should be given on the technical challenges, benchmarks and motivation for the development, not a product pitch.
- 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
Submit your abstract here.
Topics we are looking for:
- Natural Language Processing
- Deep Learning
- Reinforcement Learning
- Word Embeddings
- Generative Adversarial Networks
- Transfer Learning
- Adversarial Machine Learning
- IoT and edge computing applications
- Evolution Strategies / Genetic Algorithms
- Probabilistic Programming and Logic
- Chatbots / Bots
- Bayesian Methods
- Markov Logic Networks
- Synthetic Art, Biology
- Ethics in Machine Learning
- Data / Algorithm Ethics
- Sketching Randomized Algorithms
- Game Theory
- Community Detection
- Large-Scale Clustering
- Time Series
- Image Analysis
- Structured Learning using Neural Networks
- Data Science for Social Good
Abstract Submission Deadline: 06/30/2018. Submit your abstract here.