
Actions Panel
MLconf NYC 2016
When and where
Date and time
Location
New York 230 5th Ave New York, NY
Map and directions
How to get there
Refund Policy
Description
MLconf was created to host the thought leaders in Machine Learning and Data Science to discuss their most recent experience with applying techniques, tools, algorithms and methodologies to the seemingly impossible problems that occur when dealing with massive and noisy data. MLconf is independent of any outside company or university – it’s simply a conference organized to gather the Machine Learning communities in various cities to share knowledge and create an environment for the community to coalesce.
Event Speakers:
Kaheer Suleman, CTO, Maluuba
Abstract: Conversational Language Understanding
Jennifer Marsman, Principal Developer Evangelist, Microsoft
Abstract: Using EEG and Azure Machine Learning to Perform Lie Detection
Soumith Chintala, Artificial Intelligence Research Engineer, Facebook
Abstract: Predicting the Future Using Deep Adversarial Networks: Learning With No Labeled Data
Erich Elsen, Research Scientist, Baidu
Abstract: Training Recurrent Neural Networks at Scale
Sergei Vassilvitskii, Research Scientist, Google
Abstract: Teaching K-Means New Tricks
Braxton McKee, CEO & Founder, Ufora
Abstract: Say What You Mean: Scaling Machine Learning Algorithms Directly from Source Code
Geetu Ambwani, Principal Data Scientist, Huffington Post
Abstract: Data Science in the Newsroom
Edo Liberty, Research Director, Yahoo
Abstract: Online Data Mining: PCA and K-Means
Lei Yang, Senior Engineering Manager, Quora
Abstract: Sharing and Growing the World's Knowledge with Machine Learning
Samantha Kleinberg, Assistant Professor of Computer Science, Stevens Institute of Technology
Abstract: Casual Inference and Explanation to Improve Human Health
Mathias Brandewinder, Software Engineer & Data Scientist, Clear Lines Consulting
Abstract: Scripts that Scale with F# and mbrace.io
Damien Lefortier, Senior Machine Learning Engineer and Tech Lead in the Prediction Machine Learning team, Criteo
Abstract: Machine Learning for Display Advertising @ Scale
Yael Elmatad, Senior Data Scientist, Tapad
Abstract: Beyond the Classifier, Inspiration from Engineering Algorithms
Furong Huang, Ph.D. Canidate, UC Irvine
Abstract: Discovery of Latent Factors in High-dimensional Data Using Tensor Methods
Ike Nassi, Founder, TidalScale
Abstract: Scaling Spark - Vertically
Michael Galvin, Sr. Data Scientist, Metis
Abstract: An Introduction to Word2vec and Working With Text Data
Welch Labs, Short Tutorial Videos on Mutual Information & Decision Trees
Sponsors:
Gold: Metis, Cloudera, Dato, Meetup.com, Quora, SAS Inc, Cubist Systematic Strategies
Silver: Google, Baidu Research, h2o.ai, HiringSolved
Bronze: Maluuba, Facebook Research
Media: O'Reilly, CRC Press, MIT Press, Now Publishers, Cambridge University Press, Galvanize, Springer