Active Learning Insights
Yoshua discusses the concept of active learning, where models can choose training examples from the real world efficiently. Tim delves into machine teaching, emphasizing the importance of selecting data that holds rich information for training machine learning models effectively. Markov chain Monte Carlo emerges as a powerful method for sampling distributions, even when only the density calculation is known.In this clip
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Machine Learning Street Talk (MLST)
#063 - Prof. YOSHUA BENGIO - GFlowNets, Consciousness & Causality
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