Seminars

A Simple Exploration of Sora, by Guangqing Fu. [PDF][Video]
2024.04.23
Online Deep Anomaly Detection for Evolving Data Stream, by Lei Liu. [PDF][Video]
2024.04.23
Policy Optimization in Reinforcement Learning, by Wei Han. [PDF][Video]
2024.04.23
Efficient and Robust Deep Feature Matching, by Yang Duan. [PDF][Video]
2024.04.16
TimeMixer Decomposable Multiscale Mixing For Time Series Forecasting, by Lei Zhang. [PDF][Video]
2024.04.16
Using LoRA makes LLM smaller and faster, by Deshuai Zhang. [PDF][Video]
2024.04.16
Motion model-based Multi-Object Tracking, by Chen Liao. [PDF][Video]
2024.04.09
Gaussian Receptive Field based Label Assignment for Tiny Object Detection, by Jingyi Zhou. [PDF][Video]
2024.04.02
Empowering transformers for timeseries with patch, by Liangsen Wang. [PDF][Video]
2024.04.02
Advances in Cross-Domain Graph Few-Shot Learning, by Jinkang He. [PDF][Video]
2024.03.26
Sun_Multi-scale and patche Transformers, by Wenping Sun. [PDF][Video]
2024.03.26
Multi-periodicity Time Series Forecasting, by Zhipeng Jian. [PDF][Video]
2024.03.19
The More You Know About Time Series The Better You Do Time Series Forecasting, by Yulin Tao. [PDF][Video]
2024.03.19
Online Learning with Incremental and Decremental Features, by Haifeng Peng. [PDF][Video]
2024.03.19
Foundation model for long sequence modeling density and discrete modality, by Jinxia Guo. [PDF][Video]
2024.03.12
How the Extra modality Benefits a Classification Task, by Yuxiao Liu. [PDF][Video]
2024.03.12
Unreliable Partial Label Learning-submit, by Hongliang Wang. [PDF][Video]
2024.03.05
Open Temporal Graph, by Shuojin Huang. [PDF][Video]
2024.03.05
Prompt Learning A New Paradigm for Continual Learning, by Jiaming Liu. [PDF][Video]
2024.02.27
Node mixup tackle under-reaching, by Zhenqiang Wang. [PDF][Video]
2024.02.27
Simple Tricks on Dynamic Graph Model, by Zhenqiang Wang. [PDF][Video]
2024.01.02
Text Information in Graph, by Shuojin Huang. [PDF][Video]
2024.01.02
Replay-Free Continual Learning based on revived prototypes, by Lei Liu. [PDF][Video]
2024.01.02
SAD Semi-Supervised Anomaly Detection on Dynamic Graphs, by Quan Wu. [PDF][Video]
2023.12.26
Consistency is All You Need, by Rui Zhang. [PDF][Video]
2023.12.19
New Approaches in Attribute Graph Representation learning, by Jiahua Kang. [PDF][Video]
2023.12.19
Innovation in utilizing unlabeled datas based on GCD model, by Deshuai Zhang. [PDF][Video]
2023.12.19
Key-Event Feature-wise transformation–Poor guys’ CLIP, by Zhili Qin. [PDF][Video]
2023.12.12
Learn to Categorize or Categorize to Learn Self-Coding for Generalized Category Discovery, by Junjiang Li. [PDF][Video]
2023.12.12
New Approaches in Dynamic Graph Representation learning, by Xin Liu. [PDF][Video]
2023.12.05
Key-Event Detection or Sub-Event Detection, by Xiaoxiao Wang. [PDF][Video]
2023.12.05
Time series anomaly detection by contrastive learning, by Zhengming Luo. [PDF][Video]
2023.12.05
Rough Roadmap to LLM-based Researches, by Wei Han. [PDF][Video]
2023.11.28
Self Augmentation: Sequential Masking and Channel Masking, by Puzhen Wang. [PDF][Video]
2023.11.28
iTransformer for time series forecasting, by Zhipeng Jian. [PDF][Video]
2023.11.28
Leben in München, by Jiaming Liu. [PDF][Video]
2023.11.21
Federated Learning for Multimodal Data, by Yuxiao Liu. [PDF][Video]
2023.11.21
LLMs for Recommendation System-A Survey and Directions, by Yangqiming Wang. [PDF][Video]
2023.11.14
Visual Grounding and Tracking with Natural Language, by Chen Liao. [PDF][Video]
2023.11.14
Large Language Models for Time Series, by Enhui Wang. [PDF][Video]
2023.11.07
A Brief Introduction to Partial Label Learning, by Hongliang Wang. [PDF][Video]
2023.11.07
An Investigation of the Practicality of Supervised Knowledge, by Tongze Zhang. [PDF][Video]
2023.10.31
OneNet Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling, by Feichi Hu. [PDF][Video]
2023.10.31
End-to-end Object Detection with Transformer, by Jingyi Zhou. [PDF][Video]
2023.10.24
Dynamic Graph Representation Learning, by Qirui Hao. [PDF][Video]
2023.10.24
Anomaly Detection on Dynamic Graph, by Hongbin Zheng. [PDF][Video]
2023.10.17
Large scale data compression, by Wenpin Sun. [PDF][Video]
2023.10.10
Beyond Efficient Transformer for Long Sequence Tasks, by Liangsen Wang. [PDF][Video]
2023.10.10
Hypergraph for Whole-Slide Images, by Wei Wu. [PDF][Video]
2023.10.10
Can RetNet really inherit transformer?, by Jinxia Guo. [PDF][Video]
2023.09.26
Graph-based Methods for Long-tail Problem, by Xinyu Liu. [PDF][Video]
2023.09.26
GNN Imbalance and an innovative methods for efficient feature extraction, by Yang Duan. [PDF][Video]
2023.09.26
Online Learning with Mix-Typed Streaming Features, by Haifeng Peng. [PDF][Video]
2023.09.19
Two different perspectives improve transfer learning, by Xin Li. [PDF][Video]
2023.09.19
Ensemble learning for Imbalanced Data Streams With Concept Drift, by Zhonglin Wu. [PDF][Video]
2023.09.12
Feature or Label?: The Usage of Unlabeled Sample in SSFSL, by Guangqing Fu. [PDF][Video]
2023.09.12
The bridge of Knowledge and Latent Space, by Shilong Kang. [PDF][Video]
2023.09.12
Tool Learning with Foundation Models, by Hongyuan Liu. [PDF][Video]
2023.09.05
Robust GNN by Contrastive Learning, by Jinkang He. [PDF][Video]
2023.09.05
Crossformer: Transformer Utilizing Crossdimension Dependency For Multivariate Time Series Forecasting, by Lei Zhang. [PDF][Video]
2023.08.29
Applying Prompt in Continual Learning, by lei Liu. [PDF][Video]
2023.08.29
Attention Mechanism in Graph Neural Networks, by Hongbin Zheng. [PDF][Video]
2023.07.25
Hard example mining for Contrastive Representation Learning, by Hongqing Xi. [PDF][Video]
2023.07.25
Domain generalization on time series: A new research topic, by Enhui Wang. [PDF][Video]
2023.07.18
Online active learning for drifting data stream, by Zhonglin Wu. [PDF][Video]
2023.07.18
Robust Learning in the Presence of Data Distribution Shift, by Hongliang Wang. [PDF][Video]
2023.07.11
The ODE Form of the Generate Diffudion Model, by Rui Zhang. [PDF][Video]
2023.07.11
Improved Fine-Tuning by Better Leveraging Pre-Training Data, by Xin Li. [PDF][Video]
2023.07.04
Generalization and enhancement representation of GNN, by Yang Duan. [PDF][Video]
2023.07.04
Kernel Density Estimation over Data Streams, by Pingfu He. [PDF][Video]
2023.07.04
Exploring the Stationarity in Time Series Forecasting, by Feichi Hu. [PDF][Video]
2023.06.27
Mask for graph autoencoders, by Jiahua Kang. [PDF][Video]
2023.06.27
Conformal prediction on data streams and its new approximation method, by Haifeng Peng. [PDF][Video]
2023.06.13
Locating and Editing Knowledge in GPT, by Wei Han. [PDF][Video]
2023.06.13
How does Transformer apply to graph structures, by Lidan Zhang. [PDF][Video]
2023.06.06
Temporal relation is essential in time series forecasting, by Liangsen Wang. [PDF][Video]
2023.05.30
A Brief Introduction to Backdoor Attack, by Shangxuan Fu. [PDF][Video]
2023.05.30
Graph Contrastive Learning with Augmentation, by Xin Liu. [PDF][Video]
2023.05.30
A Brief Introduction to Quantization Method in Deep Learning, by Han Wang. [PDF][Video]
2023.05.23
Adversarial Examples and Data Attribution, by Shilong Kang. [PDF][Video]
2023.05.23
Are Transformers Effective for Time Series Forecasting?, by Ziling Deng. [PDF][Video]
2023.05.16
A Brief INtro to Graph Transformer, by Xinyu Liu. [PDF][Video]
2023.05.16
Novel methods of continuous learning based on transferable representation, by Lei Liu. [PDF][Video]
2023.05.09
Time Series Anomaly Detection using Graph-based Adversarial Network, by Tadiyos. [PDF][Video]
2023.05.09
Suffering in implementing generative replay method, by Zhiqi Qin. [PDF][Video]
2023.04.25
Domain Adaptation Regression, by Zhaoyu Liu. [PDF][Video]
2023.04.25
Correlation between time series, by Baoying Li. [PDF][Video]
2023.04.18
Handling FL Label Distribution Heterogeneity , by Cobbinah Bernard. [PDF][Video]
2023.04.18
Semi-supervised Drifted Stream Learning, by Liangxu Pan. [PDF][Video]
2023.04.11
Say goodbye to machine learning handiwork and embrace MLOps, by Kai Qin. [PDF][Video]
2023.04.11
Insights About The Benefits of Auxiliary Datasets, by Tongze Zhang. [PDF][Video]
2023.04.04
How to accelerate Hierarchical Clustering algorithms? A graph approximation perspective, by Jinxia Guo. [PDF][Video]
2023.04.04
The Renaissance of MLP and the Rethink of Vision models, by Hongyuan Liu. [PDF][Video]
2023.03.28
Mining Statistically Significant Paths in Time Series Data, by Chang Yang. [PDF][Video]
2023.03.28
A Brief Survey on Imbalanced Learning, by Jiaming Liu. [PDF][Video]
2023.03.21
Boosting Few-Shot Learning from Embedding, by Puzhen Wang. [PDF][Video]
2023.03.21
Adaptive Hypergraph Learning, by Wei Wu. [PDF][Video]
2023.03.14
Streaming graph neural network, by Yangqiming Wang. [PDF][Video]
2023.03.14
Classify time series data with deep metric learning, by Zhengming Luo. [PDF][Video]
2023.03.07
Graph Contrastive Learning with Mathematical Skills, by Qirui Hao. [PDF][Video]
2023.03.07
Learning Federated Models Efficiently in the Presence of Heterogeneous Data and Devices, by Eben. [PDF][Video]
2023.02.28
Streaming Hierarchical Clustering, by Xiaoxiao Wang. [PDF][Video]
2023.02.28
Contrastive Pre-Training of GNNs, by Jinkang He. [PDF][Video]
2023.02.21
Une année à Montréal, by Zhong Zhang. [PDF][Video]
2023.02.21
Advanced Methods of Unsupervised Instance Segmentation, by Guangqing Fu. [PDF][Video]
2023.02.14
Applications of attention mechanism in time series forecasting, by Junran Yang. [PDF][Video]
2023.02.14
Efficient utilization and representation of Graph data, by Yang Duan. [PDF][Video]
2023.01.10
Active Learning with Drifting Streaming Data, by Zhonglin Wu. [PDF][Video]
2023.01.03
Approaches to Alleviate Catastrophic Forgetting in Streaming learning, by Lei Liu. [PDF][Video]
2023.01.03
A Brief Survey on Deep Clustering, by Jiaming Liu. [PDF][Video]
2022.12.20
Some Self-supervised Learning Methods on Graphs, by Qirui Hao. [PDF][Video]
2022.12.20
Adaptive learning on weakly labeled stream, by Liangxu Pan. [PDF][Video]
2022.12.13
A series of scalable hierarchical clustering algorithms, by Jinxia Guo. [PDF][Video]
2022.12.06
A brief introduction of domain generalization, by Zhaoyu Liu. [PDF][Video]
2022.12.06
Random Walk Aggregations based Graph Neural Network, by Chang Yang. [PDF][Video]
2022.11.29
Graph, Dynamic and Robustness, by Han Wang. [PDF][Video]
2022.11.29
Can Interpretability Help?, by Wei Han. [PDF][Video]
2022.11.22
Introduction and application of TCN, by Baoying Li. [PDF][Video]
2022.11.22
Time series discord is still competitive, by Zhengming Luo. [PDF][Video]
2022.11.15
Time Series Anomaly Detection, by Tadiyos. [PDF][Video]
2022.11.15
GNN Based Recommendation System and An Improvement, by Xin Liu. [PDF][Video]
2022.11.08
Deep Embedded Clustering Method for Short Texts, by Xiaoxiao Wang. [PDF][Video]
2022.11.08
Novel Approaches for Graph Embedding Learning, by Xinyu Liu. [PDF][Video]
2022.11.01
Encoding nodes position info to enhance GNN representation, by Kai Qing. [PDF][Video]
2022.11.01
Make VAE Great Again, by Zhili Qin. [PDF][Video]
2022.10.25
Better Graph Structure for Better Performance over Node Classification, by Yangqiming Wang. [PDF][Video]
2022.10.25
Time Series: Explaining More Than Predicting, by Ziling Deng. [PDF][Video]
2022.10.18
Communication-Efficient Federated Learning Frameworks, by Ebenezer Nanor. [PDF][Video]
2022.10.18
Safe Deep Semi-Supervised Learning with Unseen-Class Unlabeled Data, by Hongliang Wang. [PDF][Video]
2022.10.11
DeepExtrema: A Deep Learning Approach for Forecasting Block Maximain Time Series Data, by Feichi Hu. [PDF][Video]
2022.10.11
Graph Self-Supervised Learning, by Pingfu He. [PDF][Video]
2022.09.27
Balance the optimization of different modalities, by Hongyuan Liu. [PDF][Video]
2022.09.27
How to improve the performance of embedding for few-shot learning, by Puzhen Wang. [PDF][Video]
2022.09.20
Dynamic network embedding, by Jiahua Kang. [PDF][Video]
2022.09.20
Spatio-temporal fusion in time series graph data, by Wenping Sun. [PDF][Video]
2022.09.13
Handling FL Statistical Heterogeneity Through Personalized Learning, by Cobbinah Bernard. [PDF][Video]
2022.09.13
Hyper-parameter Optimization, by Hongqing Xi. [PDF][Video]
2022.09.06
Uncover the Veil of the Diffusion Model, by Rui Zhang. [PDF][Video]
2022.09.06
Dynamic Neural Networks, by Wei Han. [PDF][Video]
2022.08.30
Multiplex Heterogeneous Graph Neural Network, by Xinyu Liu. [PDF][Video]
2022.08.23
Cluster better with better ‘data’, by Jinxia Guo. [PDF][Video]
2022.08.23
Clustering with Number of Clusters Estimation, by Jiaming Liu. [PDF][Video]
2022.07.19
Detecting and Adapting to Irregular Distribution Shifts in Bayesian Online Learning, by Feichi Hu. [PDF][Video]
2022.07.12
Meta-Seminar: A Seminar about Seminar, by Han Wang. [PDF][Video]
2022.07.12
Use reinforced learning to select high-quality source domain instances, by Junran Yang. [PDF][Video]
2022.07.05
Deep Neural Network Compression: Low Rank Matrix & Tensor Decompositions, by Hongliang Wang. [PDF][Video]
2022.07.05
Attribute Network Embedding, by Jiahua Kang. [PDF][Video]
2022.06.28
Deep Learning Approaches for Data Stream Classification, by Yangqiming Wang. [PDF][Video]
2022.06.28
Learning with not Enough Data: Active Learning, by Puzhen Wang. [PDF][Video]
2022.06.21
Improving the Assortativity of Graphs with Local Mixing Patterns, by Chang Yang. [PDF][Video]
2022.06.21
Restrict Information flow in network: Bottleneck Strategy, by Hongyuan Liu. [PDF][Video]
2022.06.14
Active Learning for Drifting and Predictable Concept Drift, by Zhonglin Wu. [PDF][Video]
2022.06.14
Federated Learning on Data Streams, by Eben. [PDF][Video]
2022.06.07
Revisiting Transformers From The Perspective of Memorization, by Zhong Zhang. [PDF][Video]
2022.06.07
Personalized Federated Learning, by Cobbinah Bernard. [PDF][Video]
2022.05.31
Graph neural networks for Kriging interpolation in time series, by Wenping Sun. [PDF][Video]
2022.05.31
Time Series Anomaly Detection With Association Discrepancy, by Xiaoshun Yao. [PDF][Video]
2022.05.24
Directed Graph Neural Network, by Yuanyuan Man. [PDF][Video]
2022.05.24
Interpretability on Time Series, by Ziling Deng. [PDF][Video]
2022.05.17
Neural Networks Motivated by Partial Differential Equations, by Qirui Hao. [PDF][Video]
2022.05.17
How to use less memory to train models, by Kai Qin. [PDF][Video]
2022.05.10
Robust semi-supervised learning (SSL), by Liangxv Pan. [PDF][Video]
2022.05.10
Some recent research on Multi-instance Learning, by Wenli Jia. [PDF][Video]
2022.04.26
Graph Learning in 2022, by Wujun Tao. [PDF][Video]
2022.04.26
Dynamic Network Embedding Based on Snapshots, by Lin Li. [PDF][Video]
2022.04.19
Knowledge Distillation A Survey, by Xvsong Ning. [PDF][Video]
2022.04.12
Negative transfer based on adversarial network, by Zhaoyu Liu. [PDF][Video]
2022.04.12
The latest research on data poisoning attacks, by Shangxuan Fu. [PDF][Video]
2022.03.29
A Research from Scratch, by Xiaoxiao Wang. [PDF][Video]
2022.03.29
An Overview of Few-shot Class Incremental Learning, by Zhili Qin. [PDF][Video]
2022.03.22
Multi-Label Learning with Limited Supervision, by Hongqing Xi. [PDF][Video]
2022.03.22
Recent Advance in Topic Modeling, by Lidan Zhang. [PDF][Video]
2022.03.15
Anomalous Edge Detection on Dynamic Graphs, by Pingfu He. [PDF][Video]
2022.03.15
How to Write a “Good” Paper, by Junming Shao. [PDF]
2022.03.08
Deepwalk and Matrix Factorization, by Jianyun Lu. [PDF][Video]
2022.03.08
Several methods of pre-training model compression, by Xin Liu. [PDF][Video]
2022.03.01
Toward Fair Outlier Detection, by Yu Ye. [PDF][Video]
2022.03.01
Unsupervised concept drift detection, by Zhengming Luo. [PDF][Video]
2022.02.22
A new direction for generative models Denoising Diffusion Probabilistic Models (DDPM), by Rui Zhang. [PDF][Video]
2022.02.22
Data Stream Regression, by Feichi Hu. [PDF][Video]
2022.01.21
Semi-supervised Learning on Data Streams, by Hongliang Wang. [PDF][Video]
2022.01.11
Localality similarity supervised feature distribution and clustering, by Jinxia Guo. [PDF][Video]
2022.01.11
Online Continual Learning, by Liangxv Pan. [PDF][Video]
2022.01.04
Detecting concept drift by information theory, by Zhonglin Wu. [PDF][Video]
2022.01.04
Novel Approaches in Multivariate Time Series and Graph, by Chang Yang. [PDF][Video]
2021.12.21
Self-supervised Graph Denoising——My previous & current works, by Han Wang. [PDF][Video]
2021.12.21
Semi-supervised methods for novel class detection, by Yangqiming Wang. [PDF]
2021.12.14
Federated Graph Learning, by Wenli Jia. [PDF]
2021.12.14
Some work on spatiotemporal predictive networks, by Zhaoyu Liu. [PDF][Video]
2021.12.07
A New Meta-Baseline For Few-Shot Learning, by Puzhen Wang. [PDF][Video]
2021.12.07
News Recommendation System, by Jay Kumar. [PDF][Video]
2021.11.23
Attributed Network Embedding, by Jiahua Kang. [PDF][Video]
2021.11.23
Memory-Based Architectures, by Baoyin Li. [PDF][Video]
2021.11.02
Open-set Semi-supervised Learning, by Jiaming Liu. [PDF][Video]
2021.11.02
Residual Network Research, by Xusong Ning. [PDF][Video]
2021.10.26
Multivariate Time Series Forecasting(MTSF) With Dynamic Graph, by Wenping Sun. [PDF][Video]
2021.10.26
Discriminative Shapelets for Time Series Classification, by Yuanyuan Man. [PDF][Video]
2021.10.19
GNN Based Dynamic Network Embedding, by Lin Li. [PDF][Video]
2021.10.19
Applications of “Isolation”-from Tree to Kernel, by Yu Ye. [PDF][Video]
2021.10.12
Anomaly Explanation in Deep Detectors, by Bolin Feng. [PDF][Video]
2021.10.12
From multi-thread to distributed system, A unified model, by Kai Qin. [PDF][Video]
2021.09.14
More Expressive Graph Neural Networks, by Wujun Tao. [PDF][Video]
2021.09.14
Graph in Multivariate Time, by Xiaoshun Yao. [PDF][Video]
2021.09.07
Current Approaches in Handling Heterogeneous Federated Learning, by Cobbinah Bernard Mawuli. [PDF][Video]
2021.09.07
Methods for Efficient Federated Learning, by Eben. [PDF][Video]
2021.08.27
Data Poisoning Attack and Defense, by Shangxuan Fu. [PDF][Video]
2021.08.27
Higher result password – some attention methods in computer vision, by Zhili Qin. [PDF]
2021.08.20
Deep Temporal Point Process, by Minghong Yang. [PDF]
2021.08.20
Pay Attention to MLPs-An Overview of Recent Trends, by Zhong Zhang. [PDF][Video]
2021.07.30
View optimization algorithm from perspective of dynamics and introduce to R-Dropout, by Rui Zhang. [PDF][Video]
2021.07.30
Incentive Mechanism for Federated Learning, by Wenli Jia. [PDF][Video]
2021.07.09
New publish password-CV transformer, by Zhili Qin. [PDF][Video]
2021.07.09
AUC Maximization, by Bailin Feng. [PDF]
2021.07.02
Clustering with Instance Discrimination wised Self-Supervised Learning, by Jinxia Guo. [PDF]
2021.07.02
Temporal analysis for Event Detection, by Xiaoxiao Wang. [PDF][Video]
2021.06.25
Few shot learning based on Prototype Learning, by Yue Cao. [PDF][Video]
2021.06.25
Urban-Flow Prediction, by Baoying Li. [PDF][Video]
2021.06.18
Step into Multivariate Time Series Classification, by Xiaoshun Yao. [PDF][Video]
2021.06.18
Introduction to Frequency Principles and Wasserstein Distance, by Rui Zhang. [PDF][Video]
2021.06.04
Deep Learning from the First Principle, by Yu Ye. [PDF][Video]
2021.06.04
Robust Graph Embedding-From Robustness Extension to Graph Denoising, by Han Wang. [PDF]
2021.05.28
Influence Maximization (IM) on Social Networks: An Introduction, by Honglian Wang. [PDF][Video]
2021.05.28
Recent Algorithms for Heterogenous Clients in FL, by Ebenezer Nanor. [PDF][Video]
2021.05.21
Applications of GNN in event detection, by Kai Qin. [PDF][Video]
2021.05.21
Handed datastream in engineering tasks, by Yifan Zhuo. [PDF][Video]
2021.05.14
Federated Learning with Non-IID Data, by Minghong Yang. [PDF][Video]
2021.05.14
Graph Contrastive Learning, by Wujun Tao. [PDF][Video]
2021.05.07
Inductive Learning On Graph, by Lin Li. [PDF][Video]
2021.05.07
Text classification improvement using external knowledge and auxiliary tasks, by Lidan Zhang. [PDF][Video]
2021.04.30
Domain Adaption based Adversarial, by Zhaoyu Liu. [PDF][Video]
2021.04.23
Text Embeddings for Topic Modeling, by Jay Kumar. [PDF][Video]
2021.04.23
Koopman Operator in Deep Learning, by Yuanyuan Man. [PDF][Video]
2021.04.16
Handling Domain Shift in Federated Learning, by Bernard Mawuli Cobbinah. [PDF][Video]
2021.04.16
Hypergraph Learning, by Xusong Ning. [PDF][Video]
2021.04.09
Vision-Language Pre-training With Transformers(An Overview), by Zhong Zhang. [PDF][Video]
2021.04.09
Life Long Learning, by Hongliang Wang. [PDF][Video]
2021.04.02
Some Recent Works on Class Incremental Learning, by Jiaming Liu. [PDF][Video]
2021.04.02
An Introduction to Keyphrase Extraction, by Cong Xu. [PDF][Video]
2021.03.26
Time Series Chains From TSC17 to TSC20, by Chang Yang. [PDF][Video]
2021.03.26
Black-box Attack on Graphs, by Zhongjing Yu. [PDF][Video]
2021.03.19
Extensions on Deep Metric Learning, by Liangxu Pan. [PDF][Video]
2021.03.19
Hidden Markov Model of Dynamic Reverse k Nearest Neighbor, by Jianyun Lu. [PDF][Video]
2021.03.12
Novel Class Detection on Data Streams, by Shangxuan Fu. [PDF][Video]
2021.03.12
Multi-View Representation with Graph Neural Network, by Xusong Ning. [PDF][Video]
2021.02.02
A Brief Introduction of Federated Transfer Learning, by Baoying Li. [PDF][Video]
2021.02.02
An Introduction to Normalizing Flow, by Honglian Wang. [PDF][Video]
2021.01.26
Time Series Forecasting with Spatial Temporal Graphs, by Chang Yang. [PDF][Video]
2021.01.26
Deep Metric Learning, by Liangxu Pan. [PDF][Video]
2021.01.26
Few shot learning based on Data Augmentation, by Yue Cao. [PDF][Video]
2021.01.19
A Brief Introduction of Transfer Learning, by Zhaoyu Liu. [PDF][Video]
2021.01.19
Concept Drift Detection, by Shangxuan Fu. [PDF][Video]
2021.01.19
Fairness Research of Federated Learning, by Wenli Jia. [PDF][Video]
2021.01.12
An Introduction to Event Detection Methods, by Xiaoxiao Wang. [PDF][Video]
2021.01.12
Improvement and Application of Adversarial Example, by Rui Zhang. [PDF][Video]
2021.01.05
Semi-supervised Learning on Data Streams, by Hongliang Wang. [PDF][Video]
2021.01.05
Fake News Detection A Brief Survey, by Zijiao Wang. [PDF]
2021.01.05
Anomaly Detection on Dynamic Graphs, by Kai Qin. [PDF][Video]
2020.12.29
An Introduction to Weakly Supervised Anomaly Detection, by Yu Ye. [PDF][Video]
2020.12.29
Representation and Organization of Events Based Graph, by Lidan Zhang. [PDF][Video]
2020.12.29
Self-supervised Learning by Contrastive Methods, by Jinxia Guo. [PDF][Video]
2020.12.22
Improving Communication Efficiency in Federated Learning, by Ebenezer Nanor. [PDF][Video]
2020.12.22
How to Deal with Multivariate Time Series with Missing Values, by Yifan Zhuo. [PDF][Video]
2020.12.15
Trafficflow prediction based GNN, by Yuanyuan Man. [PDF][Video]
2020.12.15
Preserving Privacy in Federated Learning, by Bernard Mawuli Cobbinah. [PDF][Video]
2020.12.08
On The Security Issues of Pre-trained Models, by Zhong Zhang. [PDF][Video]
2020.12.08
Apply Graph Convolutional Network to Knowledge Graph, by Han Wang. [PDF][Video]
2020.12.01
Informtion Theory in Deep Neural Networks, by Wei Han. [PDF][Video]
2020.12.01
Cross-Lingual Multi-Label Classification of Text Data, by Jay Kumar. [PDF][Video]
2020.11.24
Bias and Debias in RecSys, by Bailin Feng. [PDF][Video]
2020.11.24
An Introduction to Few-shot Time Series Prediction, by Minghong Yang. [PDF]
2020.11.17
Overview Of Dynamic Graph Embedding, by Lin Li. [PDF]
2020.11.17
Recommendation Systems in Production, by Yang Liu. [PDF]
2020.11.10
Robust Graph Convolutional Networks, by Wujun Tao. [PDF][Video]
2020.11.10
An Introduction to Chinese Spelling Check, by Cong Xu. [PDF][Video]
2020.11.03
Attention Mechanics for Multivariate Time Series, by Xiaoshun Yao. [PDF][Video]
2020.11.03
Natural Language Processing: Interpretability of Attention, by Jierui Li. [PDF][Video]
2020.10.27
From Softmax to Prototype Learning, by Jiaming Liu. [PDF]
2020.10.27
Reports about co-training in Munich, by Zhongjing Yu. [PDF]
2020.10.15
AutoEncoder – From initiation to burial, by Zhili Qin. [PDF]
2020.10.15
Some Recent Research on Graph Neural Networks, by Wujun Tao. [PDF]
2020.09.29
SingleLabel and Multi-Label Classification of Text Data in Stream Environment, by Jay Kumar. [PDF]
2020.09.29
HBase: The Hadoop database, a distributed, scalable, big data store, by Yifan Zhuo. [PDF]
2020.09.14
Some Recent Research Based on Self-supervised Learning, by Yue Cao. [PDF]
2020.09.14
Limitations of Graph Neural Networks, by Honglian Wang. [PDF]
2020.09.01
Showcase for Transformers, by Zhong Zhang. [PDF]
2020.08.18
Recent Session-based and Sequential Recommeder System, by Bolin Feng. [PDF]
2020.08.18
Learning Semantic Information in the Sample Self-supervised Learning, by Zhili Qin. [PDF]
2020.08.04
Some Recent Researc of Adversarial Defense, by Rui Zhang. [PDF]
2020.08.04
An Efficient Network Architecture: Before and After Training, by Wei Han. [PDF]
2020.07.21
Graph Embedding, by Lin Li. [PDF]
2020.07.21
The Non IID Data Challenge in Federated Learning(FL), by Bernard Mawuli Cobbinah. [PDF]
2020.07.07
Some methods for MTS classification, by Xiaoshun Yao. [PDF]
2020.07.07
Next Poi Recommendation, by Yang Liu. [PDF]
2020.06.23
Some Works about Extreme Values in Time Series, by Yuanyuan Man. [PDF]
2020.06.23
Open-set Recognition and Learning, by Jiaming Liu. [PDF]
2020.06.09
Research and Job Search Experience Sharing, by Yao Yang. [PDF]
2020.06.09
Deep Embedding Clustering, by Han Wang. [PDF]
2020.05.26
Recent Advances on Graph Neural Network, by Di Wu. [PDF]
2020.05.26
Time Series Prediction Based on Attention Mechanism, by Hongcai Wu. [PDF]
2020.05.10
Dynamic Graph Representation Learning, by Kai Qin. [PDF]
2020.05.10
Chinese Named Entity Recognition with Lexical Information, by Cong Xu. [PDF]
2020.04.28
Some Advances about Few Learning, by Minghong Yang. [PDF]
2020.04.28
Contextualized Word Representations, by Cong Xu. [PDF]
2020.01.07
Data Stream Learning under Infinite Label Delay, by SALAH UD DIN. [PDF]
2020.01.07
Introduction to Adversarial Example, by Rui Zhang. [PDF]
2019.12.24
Anomaly Detection for Time Series, by Xiaoshun Yao. [PDF]
2019.12.24
Model-based Approaches for Short Text Stream Clustering, by Jay Kumar. [PDF]
2019.12.10
Matrix Completion and Hawkes Process in Recsys, by Bailin Feng. [PDF]
2019.12.10
Federated Learning in the Era of Privacy Concerns, by Bernard Mawuli Cobbinah. [PDF]
2019.11.26
Some Advance of Attributed Network Embedding, by Wujun Tao. [PDF]
2019.11.26
Continual Learning, by Jiaming Liu. [PDF]
2019.11.12
Dynamic Network Embedding, by Honglian Wang. [PDF]
2019.10.29
Gradient Descent based Optimization Algorithms for Deep Learning, by Hongcai Wu. [PDF]
2019.10.29
Some Recent Advances about Few Shot Learning, by Yue Cao. [PDF]
2019.10.22
Reinforcement Learning for Recommender Systems, by Yang Liu. [PDF]
2019.10.22
Adversarial Training-based Domain Adaptation, by Yu Ye. [PDF]
2019.10.15
Another Way to Optimized Objective Function-Evolution Strategy, by Zhili Qin. [PDF]
2019.10.15
Interpret the Generalization Ability of Deep Learning From the Perspective of Fourier Analysis, by Wei Han. [PDF]
2019.09.24
Some Advances of Neural Network Architecture in Image Classification, by Yifan Zhuo. [PDF]
2019.09.24
Conditional Random Field for Sequence Labeling, by Zhong Zhang. [PDF]
2019.09.10
Graph Based Approaches for Recommendation, by Haoran Chen. [PDF]
2019.09.10
Session-based Recommender Systems, by Yang Liu. [PDF]
2019.07.23
Feature-Evolving Data Stream Mining, by Jiaqi Peng. [PDF]
2019.07.23
Deep Models for Text Semantic Match, by Di Wu. [PDF]
2019.07.09
A Survey of CTR Prediction Evolution Process, by Didi Kang. [PDF]
2019.07.09
Recent Advances in Semi-supervised Data Streams, by Yu Ye. [PDF]
2019.06.11
Modular Neural Network, by Wei Han. [PDF]
2019.06.11
Distributed Deep Learning Framework: A Brief Introduction, by Haoran Chen. [PDF]
2019.05.21
Some Challenges of Graph Convolution Networks, by Zhongjing Yu. [PDF]
2019.05.21
Learning Concept Drifting Data Stream with Limited Labels, by SALAH UD DIN. [PDF]
2019.05.07
Temporal Sequences Modeling with Neural Networks, by Hongcai Wu. [PDF]
2019.05.07
Methods and Possibilities to Utilize Complex Numbers, Start from Knowledge Graph Embedding, by Yao Yang. [PDF]
2019.04.16
A Brief Introduction of Automatic Machine Learning, by Dongzi Chen. [PDF]
2019.04.16
Semi-supervised GANs, by Jiaming Liu. [PDF]
2019.04.02
Introduction of GAN(Generative Adversarial Networks), by Yifan Zhuo. [PDF]
2019.04.02
When Multi-label Learning Meets Deep Neural Networks, by Peiyan Li. [PDF]
2019.03.19
Few-shot and Zero-shot Learning, by Zhili Qin. [PDF]
2019.03.19
Attention is All You Need, by Honglian Wang. [PDF]
2019.03.05
The Softmax Bottleneck for RNN-based Language Model, by Zhong Zhang. [PDF]
2019.03.05
Introduction of DQN, by Yang Liu. [PDF]
2019.01.22
High-order Structure in Networks, by Haoran Chen. [PDF]
2019.01.22
Recommendation in Industry, by Didi Kang. [PDF]
2019.01.08
Regression on Data Stream with Incremental Trees, by Dongzi Chen. [PDF]
2019.01.08
An Introduction to GBDT Zoo and Some Feature Engineering Tricks, by Cong Xu. [PDF]
2018.12.18
Capsule Neural Network and Discussion on Synchronization Neural Network, by Wei Han. [PDF]
2018.12.18
Deep Learning Based Recommender System, by Yi Zhao. [PDF]
2018.12.04
Classification with Novel Class Detection in Data Streams, by Salah Ud din. [PDF]
2018.12.04
Mathematical Derivation of SVM and Top-k Multi-Class SVM, by Yifan Zhuo. [PDF]
2018.11.20
Introduction of Graph Convolutional Neural Networks, by Zhongjing Yu. [PDF]
2018.11.20
Language Model and Attention Mechanism, by Zhong Zhang. [PDF]
2018.11.06
Keras: The Python Deep Learning library, by Hongcai Wu. [PDF]
2018.11.06
Dirichlet Process: Theoretic Introduction, Extensions and Applications, by Di Wu. [PDF]
2018.10.23
Max-margin DeepWalk and Hierarchical Representation Learning for Networks, by Yao Yang. [PDF]
2018.10.23
From Riemann Hypothesis to Block Chain, by Jiaming Liu. [PDF]
2018.10.09
Some Methods to Solve L1 Norm Objective Function, by Zhili Qin. [PDF]
2018.10.09
Heterogeneous Information Learning and Representation, by Honglian Wang. [PDF]
2018.09.25
Density-based Local Outlier Detection in Data Stream, by Jiaqi Peng. [PDF]
2018.09.25
On the Stability of the Dynamic System, by Zhong Zhang. [PDF]
2018.09.11
Fast Cross-layer Dependency Network Inference on Multi-layered Networks, by Yao Yang. [PDF]
2018.08.28
Visualizing Convolutional Networks, by Jiaming Liu. [PDF]
2018.08.28
Scalable Methods for Network Embedding, by Haoran Chen. [PDF]
2018.08.14
What Makes Spark Faster than MapReduce, by Yi Zhao. [PDF]
2018.07.31
Tutorial on tensorflow usage, by Wei Han. [PDF]
2018.07.31
Instance Selection for Regression, by Dongzi Chen. [PDF]
2018.07.17
Matrix Factorization Technique in Recommender Systems, by Didi Kang. [PDF]
2018.07.17
Recurrent Neural Networks and Network Variants, by Hongcai Wu. [PDF]
2018.07.03
Adaptive Sliding Window in Data Stream, by Jiaqi Peng. [PDF]
2018.07.03
It is All Starting From the Kernel K-means, by Zhong Zhang. [PDF]
2018.06.19
Correlation Information in Multi-label Classification, by Zhili Qin. [PDF]
2018.06.19
Point-of-interest Recommendation in Location-based Social Networks, by Yi Zhao. [PDF]
2018.06.05
Rule Learning, by Heng Zhang. [PDF]
2018.06.05
Relation Extraction, Embedding and Inference for Knowledge Graph, by Di Wu. [PDF]
2018.05.22
Data Mining for Urban Planning, by Songling Liu. [PDF]
2018.05.22
hdoop and Other Stuff, by Chen Huang. [PDF]
2018.04.17
Recommendation Systems with Diversity, by Chongming Gao. [PDF]
2018.04.03
Introduction to Subspace Clustering, by Cong Xu. [PDF]
2018.04.03
The Inconsistency in Multi-label Learning-Inspiration and Discussion, by Peiyan Li. [PDF]
2018.03.20
Attributed Network Embedding, by Zhongjing Yu. [PDF]
2018.03.20
Local Event Detection in Geo-Tagged Tweet Streams, by Honglian Wang. [PDF]
2018.03.10
Gaussian Processes Regression, by Jiaming Liu. [PDF]
2018.03.10
RNN and LSTM, by Ruizhi Wu. [PDF]
2018.01.17
Community Detection and Feature Selection in Attributed Networks, by Haoran Chen. [PDF]
2018.01.03
Temporal Recommendation, by Didi Kang. [PDF]
2017.12.20
Learning in the Presence of Class Imbalance and Concept Drift, by Dongzi Chen. [PDF]
2017.12.20
Optimization in ML- chap 1, by Chen Huang. [PDF]
2017.12.07
Two Ways to Solve Extreme Multi-label Learning Task, by Zhili Qin. [PDF]
2017.12.07
ICDM SHARE, by Junming Shao. [PDF]
2017.12.01
Trajectory Indexing and Retrieval, by Yi Zhao. [PDF]
2017.11.27
Introduction to Link Prediction, by Xiaolin Yang. [PDF]
2017.11.27
Inverse Variance-Based Network Inference and Clustering, by Yao Yang. [PDF]
2017.11.08
Neural Variational Inference, by Di Wu. [PDF]
2017.11.08
Distributed ML, by Chen Huang. [PDF]
2017.10.25
Introduction to Subspace Clustering, by Zhong Zhang. [PDF]
2017.10.25
Paper Sharing: Clustering and Embedding, by Peiyan Li. [PDF]
2017.10.11
Paper Sharing: L-EnsNMF , by Chongming Gao. [PDF]
2017.10.11
Watermarking in High Efficiency Video Coding , by Salahuddin. [PDF]
2017.10.11
Graph Mining KDD’17 , by Zhongjing Yu. [PDF]
2017.09.20
Knowledge Graph , by Songling Liu. [PDF]
2017.09.06
Reinforcement Learning , by Heng Zhang. [PDF]
2017.09.06
The Models for Modeling Dependencies in Document Streams , by Dongzi Chen. [RAR]
2017.08.09
Iterative Re-weighted Method , by Zhong Zhang. [PDF]
2017.08.09
Representation-based Transfer Learning and Some Advances, by Wei Han. [PDF]
2017.07.26
A Fun Tutorial of Deep Learning, by Junhua Chen. [PDF]
2017.07.26
Game Theoretic Modeling of Network Formation, by Xiaolin Yang. [PDF]
2017.06.28
Poisson distribution Poisson factorization Poisson process, by Ruizhi Wu. [PDF]
2017.06.14
Bayesian Machine Learning Some Basics, by Chen Huang. [PDF]
2017.06.14
Poisson Factorization, by Yi Zhao. [ZIP]
2017.05.31
Some Variants of Topic Models Based on LDA, by Di Wu. [ZIP]
2017.05.31
Graphical Models: From Theory to Programing, by Junhua Chen. [Code]
2017.05.17
Label Distribution Learning, by Wei Han. [PDF]
2017.05.03
Ensemble Learning and Two Popular Papers, by Chongming Gao [PDF]
2017.05.03
Power Iteration Based Clustering, by Zhen Wang. [PDF]
2017.04.19
SNE, t-SNE, LargeVis, Word2Vec and Node2Vec, by Peiyan Li. [PDF]
2017.04.14
Road Network Trajectory, by Songling Liu. [PDF]
2017.04.14
Graph Stream Mining: Clustering On Dynamic Networks, by Zhongjing Yu. [PDF]
2017.04.07
Introduction to Network Embedding, by Wenbao Li. [PDF]
2017.04.07
Hash Learnig, by Feng Huang. [PDF]
2017.03.31
Learning to Rank, by Ruizhi Wu. [PDF]
2017.03.22
XGBoost, by Heng Zhang. [PDF]
2017.03.22
Online Learning, by Chen Huang. [PDF]
2017.03.17
Research Issues in Data Stream Association Rule Mining, by Shasha Luo. [PDF]
2017.03.17
Multi-View Learning: NMF Based Method, by Zhong Zhang. [PDF]
2017.03.08
Can people cooperate in prisoners dilemma , by Xiaolin Yang. [PDF]
2017.03.08
The Instance Selection For Active Learning , by Dongzi Chen. [PDF]
2017.03.01
Generalized Linear Model , by Jiaming Liu. [PDF]
2017.03.01
Correlation-Based Methods in Multi-label Learning , by Peiyan Li. [PDF]
2017.01.11
Representative Selection: See All By Looking at A Few , by Di Wu. [PDF]
2017.01.11
Discussion on Spatial-temporal Learning: Similarity and Outlier , by Ruizhi Wu. [PDF]
2016.12.28
Moving Together Pattern , by Yi Zhao. [PDF]
2016.12.14
Distributed Processing , by Feng Huang. [PDF]
2016.12.14
Discussion on Feature Engineering: Learning Representation , by Chen Huang. [PDF]
2016.12.07
Start From Star: Deep Learning and Neuroscience , by Wei, Han. [PDF]
2016.11.30
Discussion on Complex Network: From Ranking to Application , by Zhongjing Yu. [PDF]
2016.11.23
Auto-Encoding Variational Bayes , by Qiyu Liu. [PDF]
2016.11.16
Heterogeneous network related Recommendation , by Wenbao Li. [PDF]
2016.11.16
Discussion on Data Stream , by Feng Huang. [PDF]
2016.11.09
Two States of Compressed Sensing, by Chongming Gao. [PDF]
2016.10.26
Survival and Hazard Models, by Junhua Chen. [PDF]
2016.10.19
Metric Learnig, by Songling Liu. [PDF]
2016.10.12
Computational Advertising, by Feng Huang. [PDF]
2016.10.12
nOSTP, by Joshua. [PDF]
2016.09.21
Strategic Network Formation, by Zhongjing Yu. [PDF]
2016.09.21
Learning Model Trees From Evolving Data Streams, by Heng Zhang. [PDF]
2016.09.14
A Brief View of Robust Semi-supervised Classification, by Chen Huang. [PDF]
2016.09.07
Subspace Clustering, by Zhong Zhang. [PDF]
2016.08.31
An Introduction to Game Theory, by Xiaolin Yang. [PDF]
2016.08.31
Structure Aware Sampling in Data Streams, by Yue Tan. [PDF]
2016.08.24
Regularity and Conformity Location Prediction Using Heterogeneous Mobility Data, by Ruizhi Wu. [PDF]
2016.08.24
From Sparse Representation to Low Rank Representation, by Peiyan Li. [RAR]
2016.07.27
How To Define Outlier, by Feng Huang. [RAR]
2016.07.27
Information Diffusion and External Influence in Networkss, by Zhongjing Yu. [PDF]
2016.06.29
A Matrix Factorization Method for Clustering in Heterogeneous Information Networks, by Wenbao Li. [PDF]
2016.06.29
Summarization of PGM, by Feng Huang. [PDF]
2016.06.15
Structure Learning, by Zhongjing Yu. [PDF]
2016.06.01
Graph Model Chap 17, by Junhua Chen. [PDF]
2016.06.01
Graph Model Chap 16, by Junhua Chen. [PDF]
2016.06.01
Kalman Filtering, by Heng Zhang. [PDF]
2016.06.01
MAP Inference, by Qinyuan Liu. [PDF]
2016.05.25
Graph Model Chap 12, by Xiaolin Yang. [PDF]
2016.05.25
Graph Model Chap 11, by Wenbao Li. [PDF]
2016.05.25
Graph Model Chap 9 and Chap 10, by Zhong Zhang. [PDF]
2016.05.11
Graph Model Chap 7 and Chap 8, by Xinzuo Wang. [PDF]
2016.05.06
Graph Model Chap 5 and Chap 6, by Ruizhi Wu. [PDF]
2016.05.06
Graph Model Chap 4, by Chen Huang. [PDF]
2016.04.27
Graph Model Chap 3, by Feng Huang. [PDF]
2016.04.20
Graph Model Chap 1 and Chap 2, by Xinwu Chen. [PDF]
2016.04.20
RankClus, by Xiaolin Yang. [RAR]
2016.04.06
Variational Inference, by Junhua Chen. [RAR]
2016.04.06
Edit distance and SOM, by Songling Liu. [RAR]
2016.03.30
Incremental SVM, by Heng Zhang. [PDF]
2016.03.30
FengFeng-KNN, by Feng Huang. [PDF]
2016.03.23
Graphical Model, by Chen Huang. [PDF]
2016.03.16
A Bayesian View to LDA and Dirichlet, by Chongming Gao. [PDF]
2016.03.16
Multiple Kernel Learning, by Zhong Zhang. [PDF]
2016.03.09
Graph Similarity Measures, by Xinzuo Wang. [PDF]
2016.03.09
Dirichlet Process, by Zhongjing Yu. [PDF]
2016.03.03
Criteria for model selection, by Wenbao Li. [PDF]
2016.03.03
Cost and Preference in Recommender System, by Junhua Chen. [PDF]
2016.01.20
Quantifying long-term Scientific Impact, by Ruiqi Yang. [PDF]
2016.01.20
Supervised Metric Learning, by Songling Liu. [PDF]
2016.01.13
Co-clustering, by Qinyuan Liu. [PDF]
2016.01.13
Trajectory Similarity Measurements, by Wei Wang. [PDF]
2016.01.06
Lifelong Learnig, by Huaxiu Yao. [PDF]
2016.01.06
Ensemble Learning, by Fangfang Chen. [PDF]
2015.12.30
Symbolic Aggregate ApproXimation, by Zhong Zhang. [PDF]
2015.12.23
Dimensional Reduction, by Feng Huang. [PDF]
2015.12.16
PageRank, by Xiaolin Yang. [PDF]
2015.12.09
A SURVEY OF SYNOPSIS CONSTRUCTION IN DATA STREAMS, by Yue Tan. [PDF]
2015.12.09
HMM, by Chongming Gao. [PDF]
2016.12.02
Outlier Detection of Trajectory, by Yuanliang Zhang. [PDF]
2015.11.25
Concept Drift, by Ke Yan. [PDF]
2015.11.25
A Self-Exciting Point Process Model, by Ruiqi Yang. [PDF]
2015.11.16
Online Learning, by Jiatu Shi. [PDF]
2015.11.16
Functional Connectome Fingerprinting, by Zhang Zhong. [PDF]
2015.11.11
Trajectory Clustering, by Ruizhi Wu. [PDF]
2015.11.04
Popularity versus Similarity in Growing Network, by Zhongjing Yu. [PDF]
2015.10.28
Community Detection Method in HetNet_VEPathClus, by Wenbao Li. [PDF]
2015.10.28
Recommendation based on personal personality, by Junhua Chen. [PDF]
2015.10.21
Unsupervised Feature Selection, by Songling Liu. [PDF]
2015.10.21
Network Reconstruction , by Xinzuo Wang. [PDF]
2015.10.14
Data Stream Learning, by Feng Huang. [PDF]
2015.10.14
Big Data Analysis Tool, by Ruizhi Wu. [PDF]
2015.09.23
LDA, by Chen Huang. [PDF]
2015.09.16
Time Series Analysis, by Heng Zhang. [PDF]
2015.09.16
Community and Role Model, by Zhongjing Yu. [PDF]
2015.09.02
Hierarchical Data Stream Compression, by Yue Tan. [PDF]
2015.07.23
Clustering in Heterogeneous Information Network, by Wenbao Li. [PDF]
2015.07.09
Learning and VC dimension, by Chen Huang. [PDF]
2015.05.21
Graph Summarization with bounded error, by Yue Tan. [PDF]
2015.05.07
Auxiliary Domain Selection in Cross-Domain Collaborative Filtering, by Chang Yi. [PDF]
2015.04.23
Mining Heterogeneous Network, by Jiatu Shi. [PDF]
2015.04.09
Deep Learning, by Nan Meng. [PDF]
2015.03.13
Class Posterior Probability, by Kai Wang. [PDF]
2015.03.13
Regularization, by Wenbao Li. [PDF]
2015.01.20
Tensor and Its Decomposition, by Zhichao Han. [PDF]
2015.01.08
Mean Field Theoryh, by Jiatu Shi. [PDF]
2014.12.11
Ranking with multiple hyperplanes, by Tao Qin. [PDF]
2014.11.21
Bayes Learning, by Kai Wang. [PDF]
2014.11.13
Networks & Economic Development , by Jinhu Liu. [PDF]
2014.11.06
Recommendation algorithms in the macro-evolving network, by Xiao Hu. [PDF]
2014.11.06
Sampling for Big Data , by Yue Tan. [PDF]
2014.10.30
Multiple Kernel Learning, by Hao Pan. [PDF]
2014.10.30
Tansfer Learning, by Wenbao Li. [PDF]
2014.10.23
Trajectory Data Mining, by Zhichao Han. [PDF]
2014.10.23
Sync Data Stream Classification, by Yi Liu. [PDF]
2014.10.17
Local Sensitive Hash, by Xinzuo Wang. [PDF]
2014.10.17