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Hierarchies of Abstract Machines — A forgotten Hierarchical RL Framework [Link]
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Published in Humanizing Artificial Intelligence Workshop, IJCAI-18, Stockholm, Sweden, 2018
This paper details the approach which achieved state-of-the-art performance on FigureQA Dataset
Published in Young Researchers' Symposium, CoDS-COMAD 2019, Kolkata, India, 2019
We propose and experiment with methods to combine the use of ontologies and function approximaters. We pose the methods as a type of data-knowledge trade-off and achieve superior performance on muliple tasks
Presented the idea of using semantic information in label names and how this idea dovetails with co-training [Slides]
Presented usefulness of Proto-Value Functions and the paper’s laplacian framework for finding useful options [Slides]
Presented a cognitive approach to explaining how children and adults search for information equally efficiently but differ in the implementation of the stopping rule along with a primer on ANOVA and Bonferroni corrected multiple comparisons [Slides]
Workshop, Indian Institute of Technology Madras, 2018
Conducted classes covering basics of Machine Learning and Deep Learning, Optimization, Regularization, CNNs, Word Vectors, RNNs and Encoder-Decoder Models for an audience of 90 people comprising Undergraduate and Post-Graduate students