19
April

IFMLab Tutorial Series #3

IFMLab tutorial article Derivative-Free Global Optimization Algorithms: Population based Methods and Random Search Approaches is released, which provides an introduction to the derivative-free global optimization algorithms with potential applications on training deep learning models. The covered algorithms include population based methods, e.g., GA, SCE, DE, PSO, ES, CMA-ES, and random search based approaches, e.g., hill-climbing and simulated annealing.

19
April

IFMLab Tutorial Series #2

IFMLab tutorial article Derivative-Free Global Optimization Algorithms: Bayesian Method and Lipschitzian Approaches is released, which provides a comprehensive introduction to the derivative-free global optimization algorithms with potential applications on training deep learning models. The covered algorithms include Bayesian method and Lipschitzian approaches, e.g., Shubert-Piyavskii algorithm, DIRECT, LIPO and MCS.

IJCNN Notification

One collaborated research paper Missing Entity Synergistic Completion across Multiple Isomeric Online Knowledge Libraries is accepted by IJCNN 2019.

6
Mar

IFMLab Tutorial Series #1

IFMLab tutorial article Gradient Descent based Optimization Algorithms for Deep Learning Models Training is released, which provides a comprehensive introduction to the gradient descent based learning algorithms for deep learning models. The covered algorithms include GD, SGD, Mini-batch GD, Momentum, NAG, Adagrad, RMSprop, Adadelta, Adam, Nadam, and Gadam.

ICDE Notification

One collaborated research paper from IFM Lab Meta Diagram based Active Social Networks Alignment is accepted by ICDE 2019 as a short paper.

24
Jan

Broad Learning Textbook Published

A textbook "Broad Learning Through Fusions: Applications in Machine Learning" from IFM Lab is published by Springer. This book offers a clear and comprehensive introduction to broad learning, one of the novel learning problems studied in data mining and machine learning. Pre-order is available via both Springer and Amazon.

Course Call For Enrollment

A new course entitled Advanced Data Mining will be offered to the graduate students in 2019 Spring. This course will cover some advanced topics like "network mining", "graph mining", "deep learning", "broad learning", "text mining" and "recommender system", etc. We are calling for enrollment.

15
Dec

DataLiber Platform is Online

The DataLiber open data platform has been released online. DataLiber helps you share, trade and customize data with AI experts/institutes all over the world. Once you join DataLiber, you'll be able to access the data, tasks, forum, experts, institutes, and more.

IEEE BigData Notification

One research papers Data-driven Blockbuster Planning on Online Movie Knowledge Library is accepted by IEEE BigData 2018.

21
Aug

Course Call For Enrollment

The Database course will be offered to the undergraduate students in 2018 Fall. This course will cover topics like "ER model", "relational database", "SQL", "indexing", "transaction management", etc. We are calling for enrollment.

ICDM Notification

One collaborated paper entitled " A Self-Organizing Tensor Architecture for Multi-View Clustering " is accepted by the 2018 ICDM.

Welcome New Member

Miss. Lin Meng and Mr. Jiyang Bai join IFM Lab as new PhD students starting from Fall 2018.

RecSys Notification

One collaborated paper entitled " Spectral Collaborative Filtering " is accepted by the 2018 RecSys proceedings as a Long Paper.

12
June

NSF Proposal Notification

Grateful to receive an NSF award (IIS-1763365) as the PI to support my research works on heterogeneous social network representation learning.

4
May

ICIP Notification

One collaborated paper entitled "Multi-view Fusion Through Cross-Modal Retrieval" is accepted by ICIP 2018.

ICMR Notification

One collaborated paper entitled " Multi-view Collective Tensor Decomposition for Cross-modal Hashing " is accepted by ICMR 2018.

Welcome New Member

Mr. Yuxiang Ren joins IFM Lab as a PhD student starting from Spring 2018.

16
Oct

Course Call For Enrollment

A new course entitled Social Network Mining will be offered to the graduate students in 2018 Spring. This course will cover some advanced topics like "social network mining", "graph mining", "deep learning", "broad learning", "text mining" and "recommender system", etc. We are calling for enrollment.

IFM Lab website is online.

IFM Lab is a research oriented academic laboratory directed by Prof. Jiawei Zhang, providing the latest information on fusion learning and data mining research works.