Active Mini-Batch Sampling using Repulsive Point Processes
Jun 14, 2019
Speakers
Cheng Zhang
Speaker · 0 followers
About
We explore active mini-batch selection using repulsive point processes for stochastic gradient descent (SGD). Our approach simultaneously introduces active bias and leads to stochastic gradients with lower variance. We show theoretically and empirically that our approach improves over standard SGD both in terms of convergence speed as well as final model performance.We explore active mini-batch selection using repulsive point processes for stochastic gradient descent (SGD). Our approach simultaneously introduces active bias and leads to stochastic gradients with lower variance. We show theoretically and empirically that our approach improves over standard SGD both in terms of convergence speed as well as final model performance.…
Categories
AI & Data Science
Category · 10.8k presentations
About ICML 2019
The International Conference on Machine Learning (ICML) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence known as machine learning. ICML is globally renowned for presenting and publishing cutting-edge research on all aspects of machine learning used in closely related areas like artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, and robotics. ICML is one of the fastest growing artificial intelligence conferences in the world. Participants at ICML span a wide range of backgrounds, from academic and industrial researchers, to entrepreneurs and engineers, to graduate students and postdocs.
Like the format? Trust SlidesLive to capture your next event!
Professional recording and live streaming, delivered globally.
Sharing
Recommended Videos
Presentations on similar topic, category or speaker
Glow: Generative Flow with Invertible 1x1 Convolutions
Watch later
Graph Nets for Content Creation
Watch later
A systems security perspective on adversarial machine learning
Watch later
Advances in Climate Informatics
Watch later
