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Workshop
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Learning to Continually Learn with Topological Regularization
Tananun Songdechakraiwut · Xiaoshuang Yin · Barry Van Veen
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Poster
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Thu 9:00
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Toward Equation of Motion for Deep Neural Networks: Continuous-time Gradient Descent and Discretization Error Analysis
Taiki Miyagawa
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Workshop
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Machine Learning Explainability from an Information-theoretic Perspective
Debargha Ganguly · Debayan Gupta
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Competition
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Tue 3:15
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Towards better benchmarks for AutoML, meta-learning and continual learning in computer vision
Joaquin Vanschoren
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Poster
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Thu 9:00
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Continuous Deep Q-Learning in Optimal Control Problems: Normalized Advantage Functions Analysis
Anton Plaksin · Stepan Martyanov
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Workshop
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Memory bounds for continual learning
Binghui Peng · Xi Chen · Christos Papadimitriou
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Poster
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Task-Free Continual Learning via Online Discrepancy Distance Learning
Fei Ye · Adrian G. Bors
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Poster
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Wed 14:00
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An Information-Theoretic Framework for Deep Learning
Hong Jun Jeon · Benjamin Van Roy
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Workshop
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Multiple Modes for Continual Learning
Siddhartha Datta · Nigel Shadbolt
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Workshop
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Multiple Modes for Continual Learning
Siddhartha Datta · Nigel Shadbolt
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Workshop
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Fri 3:50
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Continual learning on deployment pipelines for Machine Learning Systems
Li Qiang · Chongyu Zhang
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Workshop
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Multiple Modes for Continual Learning
Siddhartha Datta · Nigel Shadbolt
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