Sökning: "Meta-Learning"

Visar resultat 1 - 5 av 6 avhandlingar innehållade ordet Meta-Learning.

1. 1. Sharing to learn and learning to share : Fitting together metalearning and multi-task learning

   Författare :Richa Upadhyay; Marcus Liwicki; Ronald Phlypo; Rajkumar Saini; Atsuto Maki; Luleå tekniska universitet; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Multi-task learning; Meta learning; transfer learning; knowledge sharing algorithms; Machine Learning; Maskininlärning;

   Sammanfattning : This thesis focuses on integrating learning paradigms that ‘share to learn,’ i.e., Multitask Learning (MTL), and ‘learn (how) to share,’ i.e. LÄS MER

3. 2. Information-Theoretic Generalization Bounds: Tightness and Expressiveness

   Författare :Fredrik Hellström; Chalmers tekniska högskola; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; information theory; neural networks; generalization; statistical learning; meta learning; PAC-Bayes; Machine learning;

   Sammanfattning : Machine learning has achieved impressive feats in numerous domains, largely driven by the emergence of deep neural networks. Due to the high complexity of these models, classical bounds on the generalization error---that is, the difference between training and test performance---fail to explain this success. LÄS MER

4. 3. Enabling Enterprise Live Video Streaming with Reinforcement Learning and Graph Neural Networks

   Författare :Stefanos Antaris; Sarunas Girdzijauskas; Dimitrios Katsaros; KTH; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Graph Neural Networks; Reinforcement Learning; Meta-Learning; Knowledge Distillation; Enterprise Liveo Video Streaming;

   Sammanfattning : Over the last decade, video has vastly become the most popular way the world consumes content. Due to the increased popularity, video has been a strategic tool for enterprises. LÄS MER

5. 4. Embodied Evolution of Learning Ability

   Författare :Stefan Elfwing; Henrik Christensen; Jarmo Alander; KTH; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Embodied Evolution; Evolutionary Robotics; Reinforcement Learning; Shaping Rewards; Meta-parameters; Hierarchical Reinforcement Learning; Computer science; Datalogi;

   Sammanfattning : Embodied evolution is a methodology for evolutionary robotics that mimics the distributed, asynchronous, and autonomous properties of biological evolution. The evaluation, selection, and reproduction are carried out by cooperation and competition of the robots, without any need for human intervention. LÄS MER

7. 5. Data-Efficient Reinforcement and Transfer Learning in Robotics

   Författare :Xi Chen; Patric Jensfelt; Ville Kyrki; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; Computer Science; Datalogi;

   Sammanfattning : In the past few years, deep reinforcement learning (RL) has shown great potential in learning action selection policies for solving different tasks.Despite its impressive success in games, several challenges remain, such as designing appropriate reward functions, collecting large amounts of interactive data, and dealing with unseen cases, which make it difficult to apply RL algorithms to real-world robotics tasks. LÄS MER