41 posters were accepted at ML in PL Virtual Event 2020 and 34 were presented at the event.
The Best Poster Audience Award:
Hey, ML engineer! Is your model fair?, Jakub Wiśniewski, Przemysław Biecek (Warsaw University of Technology)
The Best Poster Audience Award Runner-ups:
Adversarial OverSampling for imbalanced image data classification, Adam Wojciechowski, Mateusz Lango (Poznan Supercomputing and Networking Center / Poznan University of Technology)
Automatic RL curriculum via peculiar states identification, Jakub Lewkowicz (Gdańsk University of Technology ), Bartłomiej Kocot (Gdańsk University of Technology ), Jakub Lewkowicz, Mikhail Lanchytski
A study of Democracy Backsliding in the Perspective of COVID-19 using econometrics and machine learning approaches, Michał Woźniak, Michał Wrzesiński, Jacek Lewkowicz (Faculty of Economic Sciences, University of Warsaw)
All presented posters:
- #1 - Machine learning in contract bridge, Anna Sztyber (Warsaw University of Technology), Michał Kocon, Filip Kołodziej, Patrycja Smaga, Maciej Romaniuk
- #2 - Adversarial OverSampling for imbalanced image data classification, Adam Wojciechowski, Mateusz Lango (Poznan Supercomputing and Networking Center / Poznan University of Technology)
- #3 - Is it real? Improving simulations with a deep learning discriminator, Bartłomiej Olechno (ECC Games S.A.), Piotr Migdał (ECC Games S.A., Quantum Flytrap)
- #4 - Automatic RL curriculum via peculiar states identification, Jakub Lewkowicz (Gdańsk University of Technology ), Bartłomiej Kocot (Gdańsk University of Technology ), Jakub Lewkowicz, Mikhail Lanchytski
- #5 - Multiple object tracking and segmentation with R-CNN networks, Michał Daniłowicz (AGH University of Science and Technology)
- #6 - Quantised Siamese Neural Networks for Energy Efficient Real-Time Object Tracking, Dominika Przewłocka-Rus (AGH UST), Tomasz Kryjak (AGH UST)
- #7 - Traffic Signs Classification using Convolutional Spiking Neural Networks, Dominika Przewłocka-Rus (AGH UST), Tomasz Kryjak (AGH UST)
- #8 - What factors determine unequal suburbanization? Explaining urban sprawl with machine learning, Honorata Bogusz (Faculty of Economic Sciences, University of Warsaw), Szymon Winnicki (Faculty of Economic Sciences, University of Warsaw), Piotr Wójcik (Faculty of Economic Sciences, University of Warsaw and Data Science Lab WNE UW)
- #10 - Impact of social media news on stock market index, Jakub Ajchel (Data Science Lab)
- #11 - Hey, ML engineer! Is your model fair?, Jakub Wiśniewski (Faculty of Mathematics and Information Science, Warsaw University of Technology), Przemysław Biecek
- #12 - BERT-based similarity learning for product matching, Janusz Tracz (ML Research at Allegro.pl), Piotr Wójcik (ML Research at Allegro.pl), Kalina Jasinska-Kobus (ML Research at Allegro.pl, Poznan University of Technology), Riccardo Belluzzo (ML Research at Allegro.pl), Robert Mroczkowski(ML Research at Allegro.pl), Ireneusz Gawlik (ML Research at Allegro.pl ,AGH University of Science and Technology)
- #13 - Finding perfectly fitting clothes, Konrad Czarnota (Fitly.ai), Magdalena Kalbarczyk (Fitly.ai), Jakub Cieślik (Fitly.ai)
- #14 - UCSG-Net - Unsupervised Discovering of Constructive Solid Geometry Tree, Kacper Kania, Maciej Zięba, Tomasz Kajdanowicz (Wrocław University of Science and Technology)
- #15 - Camera-based and 3D LiDAR-based place recognition across weather conditions, Kamil Żywanowski, Adam Banaszczyk, Michał Nowicki (Institute of Robotics and Machine Intelligence, Poznan University of Technology, Poland)
- #16 - Hardware-software system for 3D object detection in LiDAR point clouds based on deep neural network, Konrad Lis, Joanna Stanisz (AGH University of Science and Technology, Krakow, Poland)
- #17 - U-Net for Automated Segmentation of Knee Cartilage Imaging, Dominik Krzemiński (Cardiff University), Kevin A. Thomas, Łukasz Kidziński, Rohan Paul, Elka B. Rubin, Eni Halilaj, Marianne S. Black, Akshay Chaudhari, Garry E. Gold, Scott L. Delp ( Stanford University)
- #18 - Applying the new digital frontier. Optimization of sales promotions using heuristic techniques and machine learning., Krzysztof Szlaski (University of Warsaw)
- #19 - Universal Dependencies According to BERT: Both More Specific and More General, Tomasz Limisiewicz, David Mareček, Rudolf Rosa (everyone: Charles University in Prague, Institute of Formal and Applied Linguistics, Faculty of Mathematics and Physics)
- #20 - EDVR and U-Net for video quality mapping and artifacts removal, Łukasz Bala (TCL Research Europe), Łukasz Bala, Michał Kudelski, Dmitry Hrybov, Marcin Możejko
- #21 - Hyperparameter optimization for quantum solving sat classification, Marcin Wierzbiński (MIM UW),
- #22 - Orthogonal Rotation Invariant Moments for Equivariant Convolutional Neural Networks, Jaspreet Singh, Chandan Singh (Punjabi University, Patiala)
- #26 - Jazz Chords Generation, Mateusz Dorobek (Warsaw University of Technology),
- #27 - Recursive CNNs for ImageToLatex problem, Michał Tyrolski, Szymon Tworkowski (University of Warsaw)
- #28 - A study of Democracy Backsliding in the Perspective of COVID-19 using econometrics and machine learning approaches, Michał Woźniak, Michał Wrzesiński, Jacek Lewkowicz (Faculty of Economic Sciences, University of Warsaw)
- #29 - Segmentation of cloud patterns from satellite images to improve climate models, Kirill Vishnyakov, Mukharbek Organokov
- #30 - Training a Cooperating Team in GFootball Environment using Deep RL, Zuzanna Opała (University of Warsaw), Witalis Domitrz (University of Warsaw), Mateusz Sieniawski, Konrad Staniszewski
- #31 - Unsupervised Anomaly Detection on metal surfaces after machining, Paweł Majewski, Jacek Reiner (Wrocław University of Science and Technology)
- #34 - UAVVaste: COCO-like dataset and effective waste detection in aerial images, Mateusz Piechocki, Bartosz Ptak, Marek Kraft (Poznan University of Technology)
- #36 - Unsupervised image segmentation trained on a single image, Piotr Migdał (Quantum Flytrap / ECC Games), Bartłomiej Olechno (ECC Games)
- #37 - NeuralNDCG: Direct Optimisation of a Ranking Metric via Differentiable Relaxation of Sorting, Przemysław Pobrotyn, Radosław Białobrzeski (Machine Learning Research at Allegro.pl)
- #38 - Application of Generative Query Networks for industrial time series, Rafał A. Bachorz, Grzegorz Miebs, Małgorzata Mochol-Grzelak, Adam Karaszewski, Paulina Wawdysz (PSI Poland, Advanced Analytics Team)
- #39 - Pipeline for automated meta-analysis and tracking of academic discourse about models interpretability, transparency, and fairness, Stanisław Giziński (University of Warsaw / MI2 Data Lab), Michał Kuźba, Przemysław Biecek
- #40 - Comparative Study of Machine Learning Algorithms for Bankruptcy Prediction, Shuvam Sanyal (Symbiosis International University, Pune, India)
- #41 - napkinXC: Probabilistic Label Trees for Extreme Multi-label Classification, Marek Wydmuch (Poznan University of Technology), Kalina Jasińska (Poznan University of Technology, Allegro ML Research), Mikhail Kuznetsov (Yahoo! Research), Robert Busa-Fekete (Google Research), Krzysztof Dembczynski (Poznan University of Technology, Yahoo! Research)
