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Layerwise align the neurons across different neural nets by OT and then average their parameters.

Representing each entity as a distribution over contexts endowed in a ground space.

Experience

 
 
 
 
 
September 2018 – February 2019
Menlo Park, California

Research Intern

Facebook AI Research

Worked on building non-compositional embeddings for application in text representation and generation.
 
 
 
 
 
May 2016 – July 2016
Kyoto, Japan

Research Intern

Kyoto University

  • Developed a training mechanism for Generative Adversarial Networks (GANs) using entropy regularized Wasserstein distances. Utilized Large Margin Nearest Neighbors (LMNN) for learning the ground metric.
  • Implemented the system in Chainer, with the architectural inspirations from DCGAN.
 
 
 
 
 
November 2015 – January 2016
Bangalore, India

Research Intern

Xerox Research Centre

  • Developed prototype of a multimodal trip planning system that integrates dynamic ridesharing with scheduled transportation services.
  • Used k-medoids algorithm to find clusters of landmarks in road network graph. Implemented a variant of hill climbing algorithm & silhouette analysis to find the optimal number of clusters
 
 
 
 
 
May 2015 – July 2016
West Lafayette, Indiana

Summer Intern

Purdue University

  • Designed and implemented a method to estimate the relevance of reviews using their metadata, with a particular focus on reviews with limited votes.
  • Implemented consumer Rating as a Service (RaaS) architecture and provided a RESTful API for interaction, which were written using Node.js and Express with MongoDB for persistence.

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