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Learning Low-Rank Feature for Thorax Disease Classification
We study thorax disease classification in this paper.
Reinforcement Learning with L TL and ω-Regular Objectives via Optimality-Preserving Translation to Average Rewards Xuan-Bach Le
In this work, we study the relationship between these objectives.
SusHi Tech Tokyo 2026 set to be largest yet
Deputy Tokyo Gov. Manabu Miyasaka speaks during a SusHi Tech pre-event in Tokyo on Monday. Tokyo's annual startup convention, SusHi Tech Tokyo, is growing to be Asia's largest startup event with this year's conference in April set to focus on artificial intelligence, robotics, resilience and entertainment. The fourth SusHi Tech Tokyo -- which stands for Sustainable High City Tech Tokyo -- is expected to be the largest to date, with over 700 startups in participation. It will be held from April 27 to 29, with the first two days reserved for businesses and the final day open to the public. "(SusHi Tech Tokyo) has grown into Asia's largest innovation conference," Manabu Miyasaka, Tokyo's deputy governor, said on Monday.
Focus On What Matters: Separated Models For Visual-Based RL Generalization
Perceiving the pre-eminence of image reconstruction in representation learning, we propose SMG (Separated Models for Generalization), a novel approach that exploits image reconstruction for generalization.
Soft Superpixel Neighborhood Attention
Images contain objects with deformable boundaries, such as the contours of a human face, yet attention operators act on square windows.
Meta-Exploiting Frequency Prior for Cross-Domain Few-Shot Learning
Meta-learning offers a promising avenue for few-shot learning (FSL), enabling models to glean a generalizable feature embedding through episodic training on synthetic FSL tasks in a source domain.