15
July

Relocation to Davis, CA

Our research team has been relocated to Davis at California, and will be hosted at the Computer Science department at UC Davis.

15
Jan

DASFAA Notification

One research paper from IFM Lab entitled Label Contrastive Coding based Graph Neural Network for Graph Classification is accepted by DASFAA.

3
Jan

Course Call For Enrollment

The Advanced Database course will be offered to the graduate students in 2021 Spring. This course will cover advanced topics about database systems. We are calling for enrollment.

2
Dec

AAAI Notification

One collaborated research paper entitled Hyperbolic Variational Graph Neural Network for Modeling Dynamic Graphs is accepted by AAAI.

30
Oct

BIBM Notification

One collaborated research paper entitled Few-shot Radiology Report Generation for Rare Diseases is accepted by BIBM.

23
Oct

ASONAM Notification

One research paper from IFM Lab entitled DEAM: Adaptive Momentum with Discriminative Weight for Stochastic Optimization is accepted by ASONAM.

16
Oct

WSDM Notification

One collaborated research paper entitled AutoCite: Multi-Modal Representation Fusion for Contextual Citation Generation is accepted by WSDM.

16
Sept

EMNLP Notification

One research paper from IFM Lab entitled Text Graph Transformer for Document Classification is accepted by EMNLP as a short paper.

24
Aug

Course Call For Enrollment

The Database course will be offered to the undergraduate students in 2020 Fall. This course will cover topics like "ER model", "relational database", "SQL", "indexing", "transaction management", etc. We are calling for enrollment.

12
Aug

ICDE Notification

One research paper from IFM Lab EnsemFDet: An Ensemble Approach to Fraud Detection based on Bipartite Graph is accepted by the ICDE.

17
July

CIKM Notification

One collaborated research paper CommDGI: Community Detection Oriented Deep Graph Infomax is accepted by CIKM.

21
June

ICML Notification

One research paper from IFM Lab Get Rid of Suspended Animation: Deep Diffusive Neural Network for Graph Representation Learning is accepted by the ICML workshop on Graph Representation Learning and Beyond (GRL+).

HT Notification

One research paper from IFM Lab Scalable Heterogeneous Social Network Alignment through Synergistic Graph Partition is accepted by HT 2020.

20
Jan

Preprints

One research preprint paper from IFM Lab GRAPH-BERT: Only Attention is Needed for Learning Graph Representations is released. The corresponding model Source code of Graph-Bert is also released at github.

Course Call For Enrollment

A new course entitled Deep Learning and Applications will be offered to the graduate students in 2020 Spring. This course will cover some advanced topics like "deep learning & optimization", "graph mining", "natural language processing" and "recommender system", etc. We are calling for enrollment.

10
Nov

AAAI Notification

One collaborated research paper Learning Signed Network Embedding via Graph Attention is accepted by AAAI 2020 as a full paper. One paper from IFM Lab entitled Heterogeneous Deep Graph Infomax is accepted by the Deep Learning on Graphs: Methodologies and Applications workshop co-located with AAAI.

1
Oct

NIPS Notification

One research paper IsoNN: Isomorphic Neural Network for Graph Representation Learning and Classification from IFM Lab is accepted by NIPS 2019 Graph Representation Learning Workshop.

Welcome New Member

Yixin Chen and Haopeng Zhang join IFM Lab as PhD students starting from Fall 2019. Chenlu Wang and Haoran Yang join IFM Lab as visiting students since the summer of 2019.

18
Aug

Course Call For Enrollment

The Database course will be offered to the undergraduate students in 2019 Fall. This course will cover topics like "ER model", "relational database", "SQL", "indexing", "transaction management", etc. We are calling for enrollment.

10
Aug

ICDE Notification (1st Round)

One research paper FAKEDETECTOR: Effective Fake News Detection with Deep Diffusive Neural Network from IFM Lab is accepted by ICDE 2020 in the 1st Round.

31
July

IFM Lab Tutorial Series #7

IFM Lab tutorial article Graph Neural Networks for Small Graph and Giant Network Representation Learning: An Overview is released, which provides an introduction to the latest graph neural networks, including IsoNN, SDBN, LF&ER, GCN, GAT, DifNN, GNL, GraphSage and seGEN. Latest preprints of IsoNN and GNL first-authored by Lin Meng and Yixin Chen from IFM Lab are also released.

30
May

IFM Lab Tutorial Series #6

IFM Lab tutorial article Cognitive Functions of the Brain: Perception, Attention and Memory is released, which provides an introduction to the brain cognitive functions, including perception, attention and memory.

20
May

IFM Lab Tutorial Series #5

IFM Lab tutorial article Basic Neural Units of the Brain: Neurons, Synapses and Action Potential is released, which provides an introduction to the brain basic neural units, including neurons, synapses, and action potential.

9
May

IJCAI Notification

One collaborated paper "Learning Network Embedding with Community Structural Information" is accepted by IJCAI 2019.

30
April

IFM Lab Tutorial Series #4

IFM Lab tutorial article Secrets of the Brain: An Introduction to the Brain Anatomical Structure and Biological Function is released, which provides an introduction to the brain anatomical structure and function, as well as its surrounding sensory systems.

19
April

IFM Lab Tutorial Series #3

IFM Lab 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

IFM Lab Tutorial Series #2

IFM Lab tutorial article Derivative-Free Global Optimization Algorithms: Bayesian Method and Lipschitzian 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 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

IFM Lab Tutorial Series #1

IFM Lab 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 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: An Application on Social Networks" 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. IFM Lab will be hosted at the Computer Science department at Florida State University.