posted by organizer: yashoteja || 1118 views || tracked by 1 users: [display]

XC@ICML 2020 : The ICML 2020 Workshop on Extreme Classification Theory and Applications


When Jul 17, 2020 - Jul 18, 2020
Where Virtual Workshop
Submission Deadline Jun 19, 2020
Notification Due Jul 7, 2020
Categories    extreme classification   large-scale classification

Call For Papers

Call For Papers:

Extreme Classification 2020
The ICML Workshop on Extreme Classification Theory and Applications
17th/18th July 2020
Submission deadline: Friday, 19th June 2020 (23:59 Pacific Time)

Extreme classification is a rapidly growing research area focussing on multi-class and multi-label problems involving an extremely large number of labels. It brings many diverse approaches under the same umbrella including natural language processing (NLP), computer vision, information retrieval, recommendation systems, computational advertising, and embedding methods. Extreme classifiers have been deployed in many real-world applications in the industry ranging from language modelling to document tagging in NLP, face recognition to learning universal feature representations in computer vision, etc. Moreover, extreme classification finds application in recommendation, tagging, and ranking systems since these problems can be reformulated as multi-label learning tasks where each item to be ranked or recommended is treated as a separate label. Such reformulations have led to significant gains over traditional collaborative filtering and content-based recommendation techniques. Consequently, extreme classifiers have been deployed in many real-world applications in industry.

Extreme classification raises a number of interesting research questions including those related to:
* Large scale learning and distributed and parallel training
* Log-time and log-space prediction and prediction on a test-time budget
* Label embedding and tree based approaches
* Designing data structures for efficient learning such as trees, graphs or embeddings
* Crowd sourcing, preference elicitation and other data gathering techniques
* Bandits, semi-supervised learning and other approaches for dealing with training set biases and label noise
* Bandits with an extremely large number of arms
* Fine-grained classification
* Zero shot learning and extensible output spaces
* Tackling label polysemy, synonymy and correlations
* Structured output prediction and multi-task learning
* Learning from highly imbalanced data
* Dealing with tail labels and learning from very few data points per label
* PU learning and learning from missing and incorrect labels
* Feature extraction, feature sharing, lazy feature evaluation, etc.
* Performance evaluation
* Statistical analysis and generalization bounds
* Applications to new domains

The workshop aims to bring together researchers interested in these areas to encourage discussion and improve upon the state-of-the-art in extreme classification. In particular, we aim to bring together researchers from the natural language processing, computer vision and core machine learning communities to foster interaction and collaboration. Several leading researchers will present invited talks detailing the latest advances in the area. The workshop should be of interest to researchers in core supervised learning as well as application domains such as recommender systems, computer vision, computational advertising, information retrieval and natural language processing. We expect a healthy participation from both industry and academia.

* Submission instructions *

We solicit high-quality full papers that have not been published before in any other conferences or journals. The page limit for full papers is 8 pages without including references. We also allow submission of short abstracts of papers which have been published recently in case the authors seek more exposition for their work. The page limit for short abstracts is 4 pages without including references. For the short abstracts, please also provide a reference to the original full paper. All submissions will be considered for poster presentations. Some best quality submissions might also be considered for oral presentations. We will also have a best paper award.

Please submit full papers or short abstracts at
Submission deadline: Friday, 19th June 2020 (23:59 Pacific Time)
Author notification: 7th July 2020

All submissions must use the ICML template ( Submissions should be in .pdf format. The review process is both single-blind and double-blind, so feel free to anonymize your submissions if so desired.


Anna Choromanska (NYU)
John Langford (MSR)
Maryam Majzoubi (NYU)
Yashoteja Prabhu (MSR)

Related Resources

ICML 2024   International Conference on Machine Learning
ICoCTA 2024   2024 4th International Conference on Control Theory and Applications
ICoCTA 2024   2024 4th International Conference on Control Theory and Applications
NYC-2024-DS 2024   New York Annual Conference on Data Science 2024
PRICAI 2024   The 21st Pacific Rim International Conference on Artificial Intelligence
AASDS 2024   Special Issue on Applications and Analysis of Statistics and Data Science
ICONDATA 2024   6th International Conference on Data Science and Applications
IAAI 2024   Innovative Applications of Artificial Intelligence
IEEE-Ei/Scopus-SGGEA 2024   2024 Asia Conference on Smart Grid, Green Energy and Applications (SGGEA 2024) -EI Compendex
REX-IO 2024   4th Workshop on Re-envisioning Extreme-Scale I/O for Emerging Hybrid HPC Workloads @ IEEE Cluster 2024