ParLearning2019: 8th International Workshop on Parallel and Distributed Computing for Large-Scale Machine Learning and Big Data Analytics Dena’ina Convention Center and William Egan Convention Center Anchorage, AK, United States, August 5-8, 2019 |
Conference website | https://parlearning.github.io/ |
Submission link | https://easychair.org/conferences/?conf=parlearning2019 |
Submission deadline | May 5, 2019 |
Scaling up machine-learning (ML), data mining (DM) and reasoning algorithms from Artificial Intelligence (AI) for massive datasets is a major technical challenge in the time of "Big Data". The past ten years have seen the rise of multi-core and GPU based computing. In parallel and distributed computing, several frameworks such as OpenMP, OpenCL, and Spark continue to facilitate scaling up ML/DM/AI algorithms using higher levels of abstraction. We invite novel works that advance the trio-fields of ML/DM/AI through development of scalable algorithms or computing frameworks. Ideal submissions should describe methods for scaling up X using Y on Z, where potential choices for X, Y and Z are provided below.
Scaling up
- Recommender systems
- Optimization algorithms (gradient descent, Newton methods)
- Deep learning
- Sampling/sketching techniques
- Clustering (agglomerative techniques, graph clustering, clustering heterogeneous data)
- Classification (SVM and other classifiers)
- SVD and other matrix computations
- Probabilistic inference (Bayesian networks)
- Logical reasoning
- Graph algorithms/graph mining and knowledge graphs
- Semi-supervised learning
- Online/streaming learning
- Generative adversarial networks
Using
- Parallel architectures/frameworks (OpenMP, OpenCL, OpenACC, Intel TBB)
- Distributed systems/frameworks (GraphLab, Hadoop, MPI, Spark)
- Machine learning frameworks (TensorFlow, PyTorch, Theano, Caffe)
On
- Clusters of conventional CPUs
- Many-core CPU (e.g. Xeon Phi)
- FPGA
- Specialized ML accelerators (e.g. GPU and TPU)
Important Dates
- Paper submission: May 5, 2019 (Anywhere on Earth)
- Author notification: June 1, 2019
- Camera-ready version: Jun 8, 2019
Paper Guidelines
Submissions are limited to a total of 10 pages, including all content and references, and must be in PDF format and formatted according to the new Standard ACM Conference Proceedings Template. Additional information about formatting and style files is available online at: https://www.acm.org/publications/proceedings-template. Papers that do not meet the formatting requirements will be rejected without review.
Venue
The conference will be held in conjunction with the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
August 4-8, 2019
Dena’ina Convention Center and William Egan Convention Center
Anchorage, Alaska, USA
Contact
All questions about submissions should be emailed to Arindam Pal <arindamp@gmail.com>