Publications by Tian Guo | EPFL Graph Search

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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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

Tian Guo

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

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

Distributed Time Series Analytics

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

Model-View Sensor Data Management in the Cloud

Efficient Distributed Decision Trees for Robust Regression

Model-View Sensor Data Management in the Cloud

Data Summarization with Social Contexts

Robust Online Time Series Prediction with Recurrent Neural Networks

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

Fast Distributed Correlation Discovery Over Streaming Time-Series Data