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We will hold a joint workshop with Istituto Italiano di Tecnologia (IIT), Italy as follows;
Date and Time:
May 20, 2024: 9:25 am - 17:30 pm (JST)
May 21, 2024: 9:00 am - 15:00 pm (JST)
Venue: Online and Open Space at the RIKEN AIP Nihonbashi office
*The Open Space; only available to AIP researchers. (The application deadline has passed.)
Program:
9:25-9:30 Welcome & Introduction
9:30-10:00 Alessio Del Bue (IIT)
Title: Spatial AI: Semantic 3D Scene Understanding
10:00-10:30 Daniele Pucci (IIT)
Title: Artificial and Machine Intelligence
10:30-11:00 Coffee/Tea Break
11:00-11:30 Marta Lagomarsino (IIT)
Title: Human-Robot Interfaces and Interaction Laboratory
11:30-12:00 Arren Glover (IIT)
Title: Event-driven Perception for Robotics
12:00-13:30 Lunch Time
13:30-14:15 Keynote Speaker Masashi Sugiyama (RIKEN AIP)
Title:
-Latest update in RIKEN AIP
-Recent advances in robust machine learning: from weak supervision to changing environments
14:15-15:00 Keynote Speaker Giorgio Metta (IIT)
Title: AI-driven research at IIT: flagships and blue-sky research at the institute
15:00-16:00 Coffee/Tea Break & Poster Session (On-site only)
16:00-16:30 Mihoko Otake-Matsuura (RIKEN AIP)
Title: Robotics and AI for Cognitive Health
16:30-17:00 Lin Gu (RIKEN AIP)
Title: Representation learning from physical world to cognition
17:00-17:30 Tomasz M. Rutkowski (RIKEN AIP)
Title: AI and Brain: Machine-learning for Brain-computer Interface (BCI) Applications in Healthy Aging and Neurobiomarkers
9:00-9:30 Minh Ha Quang (RIKEN AIP)
Title: Information geometry of Gaussian processes
9:30-10:00 Yuka Hashimoto (NTT / RIKEN AIP)
Title: Deep learning with kernels through RKHM and the Perron-Frobenius operator
10:00-10:30 Sho Sonoda (RIKEN AIP)
Title: Ridgelet Transform: Harmonic Analysis for Deep Neural Networks
10:30-11:00 Coffee/Tea Break
11:00-11:30 Vittorio Murino (IIT)
Title: Multimodal Learning and Dealing with Dataset Bias
11:30-12:00 Lorenzo Natale (IIT)
Title: Interactive learning with vision and touch
12:00-13:30 Lunch Time
13:30-14:00 Qibin Zhao (RIKEN AIP)
Title: Efficient and robust machine learning with tensor networks
14:00-14:30 Kazusato Oko (RIKEN AIP)
Title: Learning summed diverse features: Efficient gradient-based learning and computational hardness of ridge combination
14:30-15:00 Thomas Möllenhoff (RIKEN AIP)
Title: Variational Learning is Effective for Large Deep Networks
Public events of RIKEN Center for Advanced Intelligence Project (AIP)
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