Workshop on Practical Bayesian Methods for Big Data at MIT

Date:

Overview

This September, the MIT Samberg Center will host the inaugural workshop on Practical Bayesian Methods for Big Data, coinciding with IBM Research’s AI week. This event aims to explore the intersection of Bayesian methods and deep learning, addressing the challenges of scalability and uncertainty in large datasets.

Background & Relevance

Bayesian methods are essential in representing uncertainty and incorporating prior knowledge in statistical modeling. However, their application has often been limited by scalability issues when dealing with extensive data and complex models. The rise of deep learning has demonstrated the advantages of large, over-parameterized models, yet these methods frequently struggle with uncertainty calibration. The workshop seeks to bridge these two paradigms, fostering research that enhances Bayesian techniques through deep learning and vice versa.

Key Details

  • Date: September 20, 2019
  • Location: MIT Samberg Center, Cambridge, MA
  • Submission Deadline: September 6, 2019
  • Abstract Registration Deadline: August 31, 2019
  • Event Website: Deeply Bayesian
  • Submission Link: EasyChair Submission

Eligibility & Participation

The workshop invites contributions from researchers engaged in Bayesian methods, deep learning, and related fields. It targets academics and practitioners interested in advancing statistical methodologies for large-scale data applications.

Submission or Application Guidelines

Participants are encouraged to submit extended abstracts, not exceeding three pages in PDF format, following NeurIPS style guidelines. Submissions can include new ideas, recent publications, or extensions of existing work. Parallel submissions and works under review are also allowed. Accepted contributions will be presented as either 15-minute talks or poster sessions, with final versions archived on the workshop website.

Additional Context / Real-World Relevance

The integration of Bayesian methods with deep learning is increasingly vital in various domains, including healthcare, finance, and artificial intelligence. This workshop will facilitate discussions on recent advancements and practical applications, contributing to the broader understanding of statistical modeling in big data contexts.

Conclusion

Researchers and practitioners are encouraged to participate in this significant event, which promises to advance the field of Bayesian methods in the context of big data. Explore the opportunity to share your work, connect with experts, and contribute to the ongoing dialogue in this evolving area of research.


Category: Conferences & Workshops
Tags: bayesian-methods, big-data, deep-learning, neural-networks, generative-models, statistical-models, mit, ibm-research, ai-week

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