RAAI Summer School 2019 Survey
We need your feedback.
First Name (you can go with N/A in case you want to go anonymous)
Your answer
Second Name (you can go with N/A in case you want to go anonymous)
Your answer
How are you satisfied with the school in general?
Completely un-satisfied
1
2
3
4
5
Completely satisfied
What lectures did you like?
L1. Michal Valko "Active multiple matrix completion with adaptive confidence sets"
L2. Roni Stern "Multi-agent pathfinding: robust and efficient solutions"
L3. Gennady Osipov "Introduction to AI methods"
L4. Sergei Kuznetsov "Pattern Structures and Pattern Setups for Knowledge Discovery in Complex Data"
L5. Vadim Stefanuk. "Mathematical modeling of distributed memory"
L6. Simon Mille "What about the "Linguistics" in "Computational Linguistics: The case of Natural Language Generation""
IL1. Irina Piontkovskaya, Huawei "Projects and Research Directions of Huawei Noah's Ark Lab"
IL2. Vitaly Shiryaev, NLMK “Data analysis and mathematical modeling on NLMK”
L7. Ricardo R. Gudwin “Motivational Systems in Cognitive Architectures”
L8. Evgeny Osipov “Computing with randomness: A new-old paradigm for energy efficient Artificial Intelligence”
L9. Ildar Batyrshin “Outline of the general theory of similarity, correlation and association measures and its applications to constructing measures of relationship of data for different domains”
L10. Vladimir Gorodetsky “Behavior-based Paradigm for Group Control of Agent Networks”
L11. Hermann Ney “Speech Recognition and Machine Translation: From Bayes Decision Rule to Deep Learning”
L12. Ruslan Salakhutdinov "Recent Advances in Deep Reinforcement Learning"
L13. Tamas Gergely “An Alternative for Artificial Intelligence – conceptual and formal theory”
L 14. Namkug Kim “Clinical Unmet Needs of Deep Learning in Medical Imaging”
L15. Alexey Averkin "Hybrid intelligent systems based on fuzzy logic and deep learning"
L16. Konstantin Yakovlev "Intelligent Robotics"
What lectures you did NOT like?
L1. Michal Valko "Active multiple matrix completion with adaptive confidence sets"
L2. Roni Stern "Multi-agent pathfinding: robust and efficient solutions"
L3. Gennady Osipov "Introduction to AI methods"
L4. Sergei Kuznetsov "Pattern Structures and Pattern Setups for Knowledge Discovery in Complex Data"
L5. Vadim Stefanuk. "Mathematical modeling of distributed memory"
L6. Simon Mille "What about the "Linguistics" in "Computational Linguistics: The case of Natural Language Generation""
IL1. Irina Piontkovskaya, Huawei "Projects and Research Directions of Huawei Noah's Ark Lab"
IL2. Vitaly Shiryaev, NLMK “Data analysis and mathematical modeling on NLMK”
L7. Ricardo R. Gudwin “Motivational Systems in Cognitive Architectures”
L8. Evgeny Osipov “Computing with randomness: A new-old paradigm for energy efficient Artificial Intelligence”
L9. Ildar Batyrshin “Outline of the general theory of similarity, correlation and association measures and its applications to constructing measures of relationship of data for different domains”
L10. Vladimir Gorodetsky “Behavior-based Paradigm for Group Control of Agent Networks”
L11. Hermann Ney “Speech Recognition and Machine Translation: From Bayes Decision Rule to Deep Learning”
L12. Ruslan Salakhutdinov "Recent Advances in Deep Reinforcement Learning"
L13. Tamas Gergely “An Alternative for Artificial Intelligence – conceptual and formal theory”
L 14. Namkug Kim “Clinical Unmet Needs of Deep Learning in Medical Imaging”
L15. Alexey Averkin "Hybrid intelligent systems based on fuzzy logic and deep learning"
L16. Konstantin Yakovlev "Intelligent Robotics"
What tutorials/workshops/hackathons did you like?
H1. Dmitry Yudin "Computer vision and reinforcement learning"
H2. Alexander Petyushko "Metric learning for facial descriptors"
H3. NLMK “The prediction of rolls wear in the hot strip mill”
W1. Konstantin Yakovlev "Single- and multi-agent path finding algorithms"
W2. Ivan Mazurenko "On fundamental mathematical problems of deep learning"
T1. Mikhail Korobkin “HD maps construction”
T2. Ivan Fursov "Neural Networks with Attention Mechanism for Efficient Paraphrase Retrieval"
T3. Dilyara Baymurzina "How to solve NLP tasks with DeepPavlov
T4. Ricardo R. Gudwin "Using CST to build a Cognitive Architecture controlling an NPC in a Computer Game"
T5. Ilya Shepel "ROS and virtual modeling tools. How to start assembling and developing robots "on the table".
T6. Anton Dvorkovich "Correction of typos"
What tutorials/workshops/hackathons you did NOT like?
H1. Dmitry Yudin "Computer vision and reinforcement learning"
H2. Alexander Petyushko "Metric learning for facial descriptors"
H3. NLMK “The prediction of rolls wear in the hot strip mill”
W1. Konstantin Yakovlev "Single- and multi-agent path finding algorithms"
W2. Ivan Mazurenko "On fundamental mathematical problems of deep learning"
T1. Mikhail Korobkin “HD maps construction”
T2. Ivan Fursov "Neural Networks with Attention Mechanism for Efficient Paraphrase Retrieval"
T3. Dilyara Baymurzina "How to solve NLP tasks with DeepPavlov
T4. Ricardo R. Gudwin "Using CST to build a Cognitive Architecture controlling an NPC in a Computer Game"
T5. Ilya Shepel "ROS and virtual modeling tools. How to start assembling and developing robots "on the table".
T6. Anton Dvorkovich "Correction of typos"
What things did you like about the school?
Your answer
What things you did not like (it can be anything - schedule, class rooms, course structure etc.)?
Your answer
What are your recommendations to the organizers of the future RAAI schools
Your answer
How did you find out about the school
Your answer
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