posted by user: apparikh || 1738 views || tracked by 3 users: [display]

NIPS Spectral Learning 2012 : Workshop on Spectral Algorithms for Latent Variable Models (at NIPS 2012)


When Dec 7, 2012 - Dec 8, 2012
Where Lake Tahoe, Nevada, USA
Submission Deadline Sep 28, 2012
Notification Due Oct 14, 2012

Call For Papers

Recently, linear algebra techniques have given a fundamentally different perspective for learning and inference in latent variable models. Exploiting the underlying spectral properties of the model parameters has led to fast, provably consistent methods for structure and parameter learning that stand in contrast to previous approaches, such as Expectation Maximization, which suffer from local optima and
slow convergence. Furthermore, these techniques have given insight into the nature of latent variable models.

In this workshop, via a mix of contributed/invited talks, posters, and discussion, we seek to explore the theoretical and applied aspects of spectral methods including the following major themes:

(1) How can spectral techniques help us develop fast and local minima free solutions to real world problems involving latent variables in natural language processing, dynamical systems, computer vision etc. where existing methods such as Expectation Maximization are unsatisfactory?

(2) How can these approaches lead to a deeper understanding and interpretation of the complexity of latent variable models?

We welcome the submission of papers related to the intersection of spectral/linear algebra methods and probabilistic modeling. Possible topics could include (but are not limited to) spectral algorithms for learning and inference in probabilistic models, tensor decomposition methods, theoretical results, and applications of these approaches.
The goal of the workshop is to bring together a wide variety of researchers from both theoretical and applied areas, and thus is open to a wide range of papers.

Submitted papers should be in NIPS 2012 format with a maximum of 4 pages (not including references). Please email your submission to

Sept 23, 2012 - Deadline for submission
Oct 7, 2012 - Notification of acceptance

If you have any questions, feel free to contact us at

Ankur Parikh (Carnegie Mellon)
Le Song (Georgia Tech)
Eric Xing (Carnegie Mellon)

Related Resources

ICMLA 2021   20th IEEE International Conference on Machine Learning and Applications
IARCE 2021-Ei Compendex & Scopus 2021   2021 5th International Conference on Industrial Automation, Robotics and Control Engineering (IARCE 2021)
ICONIP 2021   The 28th International Conference on Neural Information Processing (ICONIP2021)
ML_BDA 2021   Special Issue on Machine Learning Technologies for Big Data Analytics
FAIML 2021   2021 International Conference on Frontiers of Artificial Intelligence and Machine Learning (FAIML 2021)
17th ICTEL Rome 2021   17th ICTEL 2021 – International Conference on Teaching, Education & Learning, 06-07 September, Rome
TERA - Eurasia Research 2021   19th ICTEL 2021 – International Conference on Teaching, Education & Learning, 11-12 October, Lisbon
20th ICTEL October, Dubai 2021   20th ICTEL 2021 – International Conference on Teaching, Education & Learning, 23-24 October, Dubai
SPAA 2021   33th ACM Symposium on Parallelism in Algorithms and Architectures
blockchain_ml_iot 2021   Special Issue - Blockchain and Machine Learning for IoT: Security and Privacy Challenges