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Related publications (32)

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Online Distributed Learning Over Graphs With Multitask Graph-Filter Models

Ali H. Sayed, Roula Nassif

In this article, we are interested in adaptive and distributed estimation of graph filters from streaming data. We formulate this problem as a consensus estimation problem over graphs, which can be addressed with diffusion LMS strategies. Most popular grap ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Streaming From a Moving Platform with Real-Time and Playback Distortion Constraints

Laura Toni, Giuseppe Cocco

Video streaming from remotely controlled moving platforms such as drones have stringent constraints in terms of delay. In some applications such videos have to provide real-time visual feedback to the pilot with an acceptable distortion while satisfying hi ...

IEEE2019

Unexpected large evasion fluxes of carbon dioxide from turbulent streams draining the world’s mountains

Tom Ian Battin, Enrico Bertuzzo, Amber Joy Ulseth, Asa Lovisa Viktoria Horgby, Pier Luigi Segatto

Inland waters, including streams and rivers, are active components of the global carbon cycle.Despite the large areal extent of the world’s mountains, the role of mountain streams forglobal carbonfluxes remains elusive. Using recent insights from gas excha ...

Nature Research2019

Wearable System for Real-Time Sensing of Biomarkers in Human Sweat

Junrui Zhang

Wearable sweat sensing systems offer non-invasive and real-time bio-data streaming solutions. They open the possibility for continuous monitoring of biomarkers' concentrations as well as their variation in sweat, which is a complementary to current passive ...

EPFL2019

High‐resolution spatial sampling identifies groundwater as driver of CO 2 dynamics in an Alpine stream network

Tom Ian Battin, Amber Joy Ulseth, Asa Lovisa Viktoria Horgby, Marta Boix Canadell

Inland waters are major sources of CO2 to the atmosphere. The origin of this CO2 is often elusive, especially in high‐altitude streams that remain poorly studied at present. Here we study the spatial and seasonal variations in streamwater CO2, its potentia ...

2019

MAMUT: Multi-Agent Reinforcement Learning for Efficient Real-Time Multi-User Video Transcoding

David Atienza Alonso, Marina Zapater Sancho, Arman Iranfar, Luis Maria Costero Valero

Real-time video transcoding has recently raised as a valid alternative to address the ever-increasing demand for video contents in servers' infrastructures in current multi-user environments. High Efficiency Video Coding (HEVC) makes efficient online trans ...

IEEE2019

Adaptive Streaming in Interactive Multiview Video Systems

Pascal Frossard, Laura Toni, Xue Zhang

Multiview applications endow final users with the possibility to freely navigate within 3D scenes with minimum-delay. A real feeling of scene navigation is enabled by transmitting multiple high-quality camera views, which can be used to synthesize addition ...

2019

An Optimal Space Lower Bound for Approximating MAX-CUT

Mikhail Kapralov

We consider the problem of estimating the value of MAX-CUT in a graph in the streaming model of computation. At one extreme, there is a trivial 2-approximation for this problem that uses only O(log n) space, namely, count the number of edges and output hal ...

ASSOC COMPUTING MACHINERY2019

Remote Sensing meets Deep Learning: Exploiting Spatio-Temporal-Spectral Satellite Images for Early Wildfire Detection

Thành Tâm Nguyên

Wildfires are getting more severe and destructive. Due to their fast-spreading nature, wildfires are often detected when already beyond control and consequently cause billion-scale effects in a very short time. Governments are looking for remote sensing me ...

2019

From Anomaly Detection to Rumour Detection using Data Streams of Social Platforms

Quoc Viet Hung Nguyen, Thành Tâm Nguyên

Social platforms became a major source of rumours. While rumours can have severe real-world implications, their detection is notoriously hard: Content on social platforms is short and lacks semantics; it spreads quickly through a dynamically evolving netwo ...

ASSOC COMPUTING MACHINERY2019

A Regularization Framework for Learning Over Multitask Graphs

Ali H. Sayed, Stefan Vlaski, Roula Nassif

This letter proposes a general regularization framework for inference over multitask networks. The optimization approach relies on minimizing a global cost consisting of the aggregate sum of individual costs regularized by a term that allows to incorporate ...

IEEE Institute of Electrical and Electronics Engineers2019

Data stream statistics over sliding windows: How to summarize 150 Million updates per second on a single node

Grigorios Chrysos, Odysseas Papapetrou

Traditional data management systems map information using centralized and static data structures. Modern applications need to process in real time datasets much larger than system memory. To achieve this, they use dynamic entities that are updated with str ...

2019