Active learning from streams of graph, language & time series signals

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Active learning from streams of graph, language & time series signals David Talby SVP Engineering Atigeo Claudiu Branzan Senior Engineering Lead Atigeo

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Transcript of Active learning from streams of graph, language & time series signals

Page 1: Active learning from streams of graph, language & time series signals

Active learning from streams of graph, language & time series

signals

David Talby

SVP EngineeringAtigeo

Claudiu Branzan

Senior Engineering LeadAtigeo

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Why Active Learning & Feedback? 50+Schemes(and counting)

99.9999%‘Good’ messages

6+Months

per case

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Why Hybrid Analytics?

Ignore more rules

Unusual timing

of events

Unusual

personal

network

Teamwork & scale

Think & talk

differently

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Why Hybrid Analytics?

Rules & Policies

Time Series Analys

isLink Analys

is

Ensemble

Learning

Natural Languag

e

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Streams processing

Kafka

Email Stream

Account transactions Stream

Email NLP Features

People graph

Transactions time series

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User Analysis Iteration

Email NLP

Features

User graph

Transactions

time series

Graph Features

Time SeriesFeatures

NLP Features

Agent Feedback

Train

/ T

est

Cla

ssifi

er

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Thank You!Notebooks for this talk are freely available

[email protected]@atigeo.com

Try xPatterns Connect at: http://xpatterns.com/connect/

http://xpatterns.com/connect/
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Change Detection in Graph Streams by Learning Graph ...Cesare Alippi is with the Dept. of Electronics, Information, and Bioengineer ing, Politecnico di Milano, Milan, Italy and Faculty

Change Detection in Graph Streams by Learning Graph ...Cesare Alippi is with the Dept. of Electronics, Information, and Bioengineer ing, Politecnico di Milano, Milan, Italy and Faculty

Graph signals - Andreas Loukas · 2019. 5. 15. · graph,2014]. • Common way to create multi-scale representations of graph-structured data. • Coarse-grained diffusion maps [Lafon

Graph signals - Andreas Loukas · 2019. 5. 15. · graph,2014]. • Common way to create multi-scale representations of graph-structured data. • Coarse-grained diffusion maps [Lafon

Software Defined Radio for processing GNSS signals · Software Defined Radio for processing GNSS signals BACHELOR’S THESIS ... 4.1.2 Doppler shift graph using gnss-sdr software

Software Defined Radio for processing GNSS signals · Software Defined Radio for processing GNSS signals BACHELOR’S THESIS ... 4.1.2 Doppler shift graph using gnss-sdr software

Identification of Outliers in Graph Signals*hamsa/pubs/GopalakrishnanLiBalakrishnan_CDC2019… · has received little attention in the context of graph signals. Our work attempts

Identification of Outliers in Graph Signals*hamsa/pubs/GopalakrishnanLiBalakrishnan_CDC2019… · has received little attention in the context of graph signals. Our work attempts

Two Classes Signals Deterministic Signals & Random SignalsMATLAB bar graphs can be created to plot either vertically or horizontally. The bar function produces a bar graph which for

Two Classes Signals Deterministic Signals & Random SignalsMATLAB bar graphs can be created to plot either vertically or horizontally. The bar function produces a bar graph which for

A test of hypotheses for random graph distributions built ... · A test of hypotheses for random graph distributions built from EEG ... signals collected during the observation of

A test of hypotheses for random graph distributions built ... · A test of hypotheses for random graph distributions built from EEG ... signals collected during the observation of

GraphZip: Mining Graph Streams using Dictionary-based ... · edges [8]. While it is possible to utilize conventional graph mining systems on dynamic graphs by processing static ‘snapshots’

GraphZip: Mining Graph Streams using Dictionary-based ... · edges [8]. While it is possible to utilize conventional graph mining systems on dynamic graphs by processing static ‘snapshots’

Downsampling of Signals on Graphs Via Maximum Spanning …minhdo/publications/GraphDownsampling.pdfA spanning tree (ST) of a connected graph Gis another connected graph Twithout cycles

Downsampling of Signals on Graphs Via Maximum Spanning …minhdo/publications/GraphDownsampling.pdfA spanning tree (ST) of a connected graph Gis another connected graph Twithout cycles

Visualizing Graph Differences from Social Media Streamscm.cecs.anu.edu.au/documents/shin_wsdm2019_demo.pdf · Visualizing Graph Differences from Social Media Streams Minjeong Shin1,2

Visualizing Graph Differences from Social Media Streamscm.cecs.anu.edu.au/documents/shin_wsdm2019_demo.pdf · Visualizing Graph Differences from Social Media Streams Minjeong Shin1,2

Graphs as Streams: Rethinking Graph Processing in the Streaming Era

Graphs as Streams: Rethinking Graph Processing in the Streaming Era

Gait Recognition Using WiFi Signals€¦ · Gait Recognition Using WiFi Signals Wei Wang Alex X. Liu Muhammad Shahzad ... § Changes in CSI streams caused by human movement are correlated

Gait Recognition Using WiFi Signals€¦ · Gait Recognition Using WiFi Signals Wei Wang Alex X. Liu Muhammad Shahzad ... § Changes in CSI streams caused by human movement are correlated

Schedule Signals and Streams Version 1docs.oasis-open.org/ws-calendar/streams/v1.0/cs01/streams-v1.0-cs… · Schedule Signals and Streams Version 1.0. Edited by Toby Considine and

Schedule Signals and Streams Version 1docs.oasis-open.org/ws-calendar/streams/v1.0/cs01/streams-v1.0-cs… · Schedule Signals and Streams Version 1.0. Edited by Toby Considine and

Dictionary Learning for Graph Signals · 2019. 12. 21. · Dictionary Learning for Graph Signals By: Yael Yankelevsky Ignore structure (MOD, K-SVD) [Engan et al. 99],[Aharon et al.

Dictionary Learning for Graph Signals · 2019. 12. 21. · Dictionary Learning for Graph Signals By: Yael Yankelevsky Ignore structure (MOD, K-SVD) [Engan et al. 99],[Aharon et al.

On Clustering Graph Streams

On Clustering Graph Streams

1 Efficient Continuous Multi-Query Processing over Graph ... · 1 Efficient Continuous Multi-Query Processing over Graph Streams Lefteris Zervakis, Vinay Setty, Christos Tryfonopoulos,

1 Efficient Continuous Multi-Query Processing over Graph ... · 1 Efficient Continuous Multi-Query Processing over Graph Streams Lefteris Zervakis, Vinay Setty, Christos Tryfonopoulos,

Change Detection in Graph Streams by Learning Graph ... · Graph Embeddings on Constant-Curvature Manifolds Daniele Grattarola, Student Member, IEEE, Daniele Zambon, Student Member,

Change Detection in Graph Streams by Learning Graph ... · Graph Embeddings on Constant-Curvature Manifolds Daniele Grattarola, Student Member, IEEE, Daniele Zambon, Student Member,

Maths for Signals and Systems - Imperial College Londontania/teaching... · Mathematics for Signals and Systems Graphs and networks: incidence matrix • A graph is a set of nodes

Maths for Signals and Systems - Imperial College Londontania/teaching... · Mathematics for Signals and Systems Graphs and networks: incidence matrix • A graph is a set of nodes

Drug-disease Graph: Predicting Adverse Drug Reaction ...€¦ · Predicting Adverse Drug Reaction Signals via Graph Neural Network with Clinical Data HeeyoungKwak, ... Healthcare

Drug-disease Graph: Predicting Adverse Drug Reaction ...€¦ · Predicting Adverse Drug Reaction Signals via Graph Neural Network with Clinical Data HeeyoungKwak, ... Healthcare

Graph-Based Multi-Tweet Summarization using Social Signals · Besides utilizing social signals, our system has two additional features. Firstly, the read-ability feature is introduced

Graph-Based Multi-Tweet Summarization using Social Signals · Besides utilizing social signals, our system has two additional features. Firstly, the read-ability feature is introduced

Outlier Detection in Graph Streamscharuaggarwal.net/357present.pdf• Events in social networks may lead to local patterns of ac-tivity, which may be modeled as streams of graph objects.

Outlier Detection in Graph Streamscharuaggarwal.net/357present.pdf• Events in social networks may lead to local patterns of ac-tivity, which may be modeled as streams of graph objects.