Personne

Tian Guo

Cette personne n’est plus à l’EPFL

Publications associées (12)

Hybrid Neural Networks for Learning the Trend in Time Series

The trend of time series characterizes the intermediate upward and downward behaviour of time series. Learning and forecasting the trend in time series data play an important role in many real applications, ranging from resource allocation in data centers, ...

2017

Distributed Time Series Analytics

Tian Guo

In recent years time series data has become ubiquitous thanks to affordable sensors and advances in embedded technology. Large amount of time-series data are continuously produced in a wide spectrum of applications, such as sensor networks, medical monitor ...

EPFL2017

Robust Online Time Series Prediction with Recurrent Neural Networks

Karl Aberer, Tian Guo

Time series forecasting for streaming data plays an important role in many real applications, ranging from IoT systems, cyber-networks, to industrial systems and healthcare. However the real data is often complicated with anomalies and change points, which ...

Ieee2016

Efficient Distributed Decision Trees for Robust Regression

Karl Aberer, Jean Paul Calbimonte Perez, Tian Guo

The availability of massive volumes of data and recent advances in data collection and processing platforms have motivated the development of distributed machine learning algorithms. In numerous real-world applications large datasets are inevitably noisy a ...

2016

Data Summarization with Social Contexts

Karl Aberer, Xia Hu, Tian Guo, Hao Zhuang, Rameez Rahman

While social data is being widely used in various applications such as sentiment analysis and trend prediction, its sheer size also presents great challenges for storing, sharing and processing such data. These challenges can be addressed by data summariza ...

Assoc Computing Machinery2016

Fast Distributed Correlation Discovery Over Streaming Time-Series Data

Karl Aberer, Saket Sathe, Tian Guo

The dramatic rise of time-series data in a variety of contexts, such as social networks, mobile sensing, data centre monitoring, etc., has fuelled interest in obtaining real-time insights from such data using distributed stream processing systems. One such ...

2015

SigCO: Mining Significant Correlations via a Distributed Real-time Computation Engine

Karl Aberer, Jean Paul Calbimonte Perez, Tian Guo, Hao Zhuang

The dramatic rise of time-series data produced in a variety of contexts, such as stock markets, mobile sensing, sensor networks, data centre monitoring, etc., has fuelled the development of large-scale distributed real-time computation systems (e.g., Apach ...

2015

Efficient Indexing and Query Processing of Model-View Sensor Data in the Cloud

Karl Aberer, Tian Guo

As the number of sensors that pervade our lives increases (e.g., environmental sensors, phone sensors, etc.), the eﬃcient management of massive amount of sensor data is becoming increasingly important. The inﬁnite nature of sensor data poses a serious chal ...

2014

Online indexing and distributed querying model-view sensor data in the cloud

Karl Aberer, Tian Guo, Hao Zhuang

As various kinds of sensors penetrate our daily life (e.g., sensor networks for environmental monitoring, GPS for localization and navigation), the efficient management of massive amount of sensor data becomes increasingly important at present. Many sensor ...

Springer-Verlag Berlin2014

Model-View Sensor Data Management in the Cloud

Karl Aberer, Tian Guo

Infinite nature of sensor data poses a serious challenge for query processing even in a cloud infrastructure. Model-based sensor data approximation reduces the amount of data for query processing, but all modeled segments need to be scanned, in the worst c ...

2013

Model-View Sensor Data Management in the Cloud

Karl Aberer, Tian Guo

IEEE2013

An Adaptive Approach for Online Segmentation of Multi-Dimensional Mobile Data

Karl Aberer, Zhixian Yan, Tian Guo

With increasing availability of mobile sensing devices including smartphones, online mobile data segmentation becomes an important topic in reconstructing and understanding mobile data. Traditional approaches like online time series segmentation either use ...

2012