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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

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Future Blog Post

less than 1 minute read

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This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.

Blog Post number 4

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 3

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 2

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 1

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

portfolio

A Multivariate Hawkes Process for Detecting Individuals with Depressive Disorder

We propose a personalized framework for classifying individuals with and without depression symptoms. We simulated the interplay between the distributional semantics and the temporal stochasticity of online activities with a mutually exciting multidimensional Hawkes Process.

Machine Learning → Temporal Point Process; Mental Health.

Understanding Diversity-based Pruning of Neural Networks – Statistical Mechanical Analysis

Despite the multitude of empirical advances, there is no theoretical understanding of the effectiveness of different pruning methods. We address this issue by setting up the problem in the statistical mechanics formulation of a teacher-student framework and deriving generalization error (GE) bounds of specific pruning methods.

Theory for Deep Learning → Statistical Mechanical Analysis.

Decoding Word Sense with Graphical Embeddings

Implemented three deep graph encoders over WordNet for word sense embeddings bounded by hypernyms-hyponyms and meronyms-holonyms: a child-sum graph bi-LSTM, a matrix decomposition method with graph kernels, and a GCN.

Word Sense Disambiguation.

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