About Conference

WELCOME

The aim of GHOST Day: AMLC is to create an outstanding space for exchanging experiences between machine learning practitioners and, most importantly, a friendly environment for updating knowledge in the rapidly changing area of data analysis. To this end, conference speakers will include several recognized representatives of the scientific community publishing at top-tier global conferences such as NeurIPS or ICML and numerous experts from companies constructing ML-based products such as Intel, IBM, Allegro or Pearson. The conference also wants to create a gateway for all talented and interested people who want to enter the fascinating world of data analysis and artificial intelligence.

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Conference Date

8 November 2019

Our Speakers

Who’s speaking

Our Timetable

Agenda

9:00 - 10:00 Registration (Lecture and Conference Centre of Poznan University of Technology, abbr. CW)
10:00 – 10:15 Conference opening (Aula Magna, CW 4)
10:15 - 11:15 Keynote lecture: "Quo vadis Reinforcement Learning?" by Wojciech Jaśkowski, PhD (Aula Magna, CW 4)
11:15 - 11:45 Coffee break (Pasaż Bernardyński, CW)
11:45 – 13:45 Session 1: NLP (CW 8) Session 2: General ML (CW 9) Session 3: Computer Vision (CW 7)
13:45 - 14:45 Lunch break (CW 0.53)
14:45 – 16:45 Session 4: ML in Medicine (CW 7) Session 5: ML Applications (CW 8)
This session is sponsored by Antmicro
Session 6: Student Session (CW 9)
16:45 - 17:45 Poster session (Pasaż Bernardyński, CW)
17:45 - 18:00 Closing session (CW 7)

Conference Sessions

Word sense disambiguation and mechanisms improving NLP

by Mateusz Półtorak | Pearson

11:45-12:15

CW 8

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Debugging black-box NLP models

by Filip Graliński | Applica.ai

12:15-12:45

CW 8

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Artificial intelligence - human emotions

by Konrad Juszczyk | Sentimenti

12:45-13:15

CW 8

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A long long time ago in an NLP model far far away - are computers able to create stories?

by Dawid Wiśniewski | Applica.ai

13:15-13:45

CW 8

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Hacking AI

by Michał Łukaszewski | Intel

11:45-12:15

CW 9

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Scale-invariant online learning

by Wojciech Kotłowski | PUT

12:15-12:45

CW 9

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Is practical AutoML more than CASH?

by Alexandre Quemy | IBM

12:45-13:15

CW 9

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Scaling machine learning systems up to billions of predictions per day

by Carmine Paolino | OLX

13:15-13:45

CW 9

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Learning binary image representations and the path towards 3D

by Tomasz Trzciński | Tooploox

11:45-12:45

CW 7

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How to find that red dress? - Visual Search in Allegro

by Piotr Rybak | Allegro

12:45-13:45

CW 7

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Transfer learning in healthcare industry

by Michał Kierzynka | Roche

14:45-15:15

CW 7

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Sound event detection using self-consistency checking neural networks

by Tomasz Grzywalski | StethoMe

15:15-15:45

CW 7

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The machine learning for de novo drug design

by Rafał A. Bachorz | PSI

15:45-16:15

CW 7

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Prediction of phase change in bipolar disorder

by Olga Kamińska | Britenet

16:15-16:45

CW 7

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How to model students' knowledge using recurrent neural networks?

by Mikołaj Olszewski & Mateusz Otmianowski | Pearson

14:45-15:15

CW 8

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Machine Learning at the very edge with TensorFlow and beyond

by Michael Gielda | Antmicro

15:15-15:45

CW 8

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OCR for Data Extraction from Receipts

by Bartosz Ludwiczuk | intive

15:45-16:15

CW 8

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Data Science in Cybersecurity

by Zuzanna Kunik | F-Secure

16:15-16:45

CW 8

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How to win Data Science competitions? (Student Session opening)

by Paweł Sienkowski | Fathom

14:45-15:15

CW 9

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Making your neural networks pay more attention

by Dariusz Max Adamski | GHOST

15:15-15:45

CW 9

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Unsupervised anomaly detection in multivariate time series data

by Damian Horna | GHOST

15:45-16:15

CW 9

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GhostRacer - towards self-driving cars

by Jakub Tomczak | GHOST

16:15-16:45

CW 9

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Partners & Sponsors

Honorary Patronage

Official Sponsors

Platinum
Gold
Silver

Media Partners