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The Theoretical Basis of Machine Learning 2018 (ML)

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Deep Reinforcement Learning of Marked Temporal Point Processes by Abir De

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The Loss Landscape of Deep Neural Networks by Shankar Krishnan

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Fairness in Algorithmic Decision Making: Classification and Beyond by Abhijnan Chakraborty

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A Deep Generative Model for Molecular Graphs by Niloy Ganguly

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ProtoDash: Fast Interpretable Prototype Selection by Karthik Gurumoorthy

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Machine Learning in Face of Data Irregularities: Some Key Challenges by Swagatam Das

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Inverse Problems under a Learned Generative Prior (Lecture 1) by Paul Hand

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