I am a CS Ph.D. student in The Center For Language and Speech Processing at the Johns Hopkins University. Currently, I am interested in solving problems posted on StackOverflow among other structured-predictiony things. I graduated from IIT Delhi in August 2011 with dual degrees in EE and IT. After graduation, I worked for a year at Goldman Sachs as a Core Ops Strat and then joined Aspiring Minds as an RnD engineer.

At CLSP, my advisor is Benjamin Van Durme and I have worked with Raman Arora, Jason Eisner and James Spall.

Selected Publications

• Weighting Finite-State Transductions With Neural Context, Pushpendre Rastogi, Ryan Cotterell, Jason Eisner. NAACL(2016) [bib] [pdf] [slides] [code]
• Efficient Implementation of Enhanced Adaptive Simultaneous Perturbation Algorithms, Pushpendre Rastogi, Jingyi Jhu, James Spall. CISS(2016) [bib] [code] [pdf]
• Multiview LSA: Representation Learning Via Generalized CCA, Pushpendre Rastogi, Benjamin Van Durme and Raman Arora, NAACL(2015) [pdf], [data+code], [bib], [poster], [supplementary]
• Augmenting FrameNet Via PPDB, Pushpendre Rastogi and Benjamin Van Durme, Events Workshop at ACL(2014), [pdf], [data], [poster] [bib]
• Stationarity Condition for Fractional Sampling Filters. Pushpendre Rastogi (Master's theses)[pdf]
• More at Google Scholar.

Posts

• Searchable PDF version of the Penn Treebank Bracketing Guideline
• Matrix Decompositions
• Beginners analysis for optimization in Data Science.
• The impossibility of specifying the number of samples needed in a validation set using t-distributions for regression with unbounded loss
• Edge Prediction in Semantic Graphs
• Induction and Recursion
• Understanding Logistic Regression II
• Convex Neural Networks?
• Online Sample Complexity Bound Calculator
• Understanding_logistic_regression
• Class Diagram Portion From Uml
• Multiview LSA Motivation and Proofs
• Mathematical Notation Glossary
• Eigenvalue Problems