People


Sarah Wassermann

Sarah Wassermann
Institution office homepage group
 Inria 43 None Former PhD students

Articles

ADAM & RAL: Adaptive Memory Learning and Reinforcement Active Learning for Network Monitoring,
Sarah Wassermann , Thibaut Cuvelier, Pavol Mulinka, Pedro Casas,
15th International Conference on Network and Service Management (CNSM) 2019, Halifax, Canada
I See What you See - Real Time Prediction of Video Quality from Encrypted Streaming Traffic,
Sarah Wassermann , Michael Seufert, Pedro Casas, Li Gang, Kuang Li,
Internet-QoE@MOBICOM 2019, Los Cabos, Mexico
RAL - Improving Stream-Based Active Learning by Reinforcement Learning,
Sarah Wassermann , Thibaut Cuvelier, Pedro Casas,
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) Workshop on Interactive Adaptive Learning (IAL) 2019, Würzburg, Germany
On the Analysis of YouTube QoE in Cellular Networks through in-Smartphone Measurements,
Sarah Wassermann , Pedro Casas, Michael Seufert, Florian Wamser,
WMNC 2019, Paris, France
Let me Decrypt your Beauty - Real-time Prediction of Video Resolution and Bitrate for Encrypted Video Streaming,
Sarah Wassermann , Michael Seufert, Pedro Casas, Li Gang, Kuang Li,
TMA 2019, Paris, France
ADAM & RAL - Adaptive Memory Learning and Reinforcement Active Learning for Network Monitoring,
Sarah Wassermann , Thibaut Cuvelier, Pavol Mulinka, Pedro Casas,
CNSM 2019
Remember the Good, Forget the Bad, do it Fast - Continuous Learning over Streaming Data,
Pavol Mulinka, Sarah Wassermann , Gonzalo Marín, Pedro Casas,
Continual Learning Workshop at NeurIPS 2018 2018, Montréal, Canada
Beauty is in the Eye of the Smartphone Holder A Data Driven Analysis of YouTube Mobile QoE,
Nikolas Wehner, Sarah Wassermann , Pedro Casas, Michael Seufert, Florian Wamser,
CNSM 2018, Rome, Italy
Distributed Internet Paths Performance Analysis Through Machine Learning,
Sarah Wassermann , Pedro Casas,
TMA 2018, Vienne, Austria
BIGMOMAL — Big Data Analytics for Mobile Malware Detection,
Sarah Wassermann , Pedro Casas,
ACM SIGCOMM 2018 Workshop on Traffic Measurements for Cybersecurity (WTMC 2018) 2018, Budapest, Hungary
Anycaston the Move - A Look at Mobile Anycast Performance,
Sarah Wassermann , John Rula, Fabian Bustamante, Pedro Casas,
TMA 2018, Vienne, Austria
BIGMOMAL - Big Data Analytics for Mobile Malware Detection,
Sarah Wassermann , Pedro Casas,
WTMC@SIGCOMM 2018
Improving QoE prediction in mobile video through machine learning,
Pedro Casas, Sarah Wassermann ,
NOF 2017
NETPerfTrace - Predicting Internet Path Dynamics and Performance with Machine Learning,
Sarah Wassermann , Pedro Casas, Thibaut Cuvelier, Benoit Donnet,
Big-DAMA@SIGCOMM 2017
On the Analysis of Internet Paths with DisNETPerf, a Distributed Paths Performance Analyzer,
Sarah Wassermann, Pedro Casas, Benoit Donnet, Guy Leduc, Marco Mellia,
LCN Workshops 2016

Journal articles

Considering User Behavior in the Quality of Experience Cycle - Towards Proactive QoE-Aware Traffic Management,
Michael Seufert, Sarah Wassermann , Pedro Casas,
IEEE Communications Letters 2019
Machine Learning Models for YouTube QoE and User Engagement Prediction in Smartphones,
Sarah Wassermann , Nikolas Wehner, Pedro Casas,
SIGMETRICS Perform. Evaluation Rev. 2018, Toulouse, France
Unveiling network and service performance degradation in the wild with mplane,
Pedro Casas, Pierdomenico Fiadino, Sarah Wassermann, Stefano Traverso, Alessandro Dalconzo, Edion Tego, Francesco Matera, Marco Mellia,
IEEE Commun. Mag. 2016

Report

Lightweight, General Inference of Streaming Video Quality from Encrypted Traffic,
Francesco Bronzino , Paul Schmitt, Sara Ayoubi , Nick Feamster, Renata Teixeira , Sarah Wassermann , Srikanth Sundaresan,
CoRR 2019

Posters

RAL - Reinforcement Active Learning for Network Traffic Monitoring and Analysis,
Sarah Wassermann , Thibaut Cuvelier, Pedro Casas,
ACM SIGCOMM 2020 Posters, Demos, and Student Research Competition 2020, New York / Virtual, United States
How Good is your Mobile (Web) Surfing? Speed Index Inference from Encrypted Traffic,
Sarah Wassermann , Pedro Casas, Michael Seufert, Nikolas Wehner, Joshua Schuler, Tobias Hossfeld,
ACM SIGCOMM 2020 Posters, Demos, and Student Research Competition 2020, New York, United States
Improving Stream-Based Active Learning with Reinforcement Learning,
Sarah Wassermann , Thibaut Cuvelier, Pedro Casas,
Women in Machine Learning (WiML) Workshop 2019 2019, Vancouver, Canada
Decrypting Video Quality from Encrypted Streaming Traffic,
Sarah Wassermann , Pedro Casas,
Women in Machine Learning (WiML) Workshop 2019 2019, Vancouver, Canada
ViCrypt: Real-time, Fine-grained Prediction of Video Quality from Encrypted Streaming Traffic,
Sarah Wassermann , Michael Seufert, Pedro Casas, Li Gang, Kuang Li,
ACM Internet Measurement Conference (IMC) 2019 2019, Amsterdam, Netherlands