Posts by Collection

portfolio

publications

Towards Realistic Single-Task Continuous Learning Research for NER

Published in Findings of The 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Recommended citation: Justin Payan, Yuval Merhav, He Xie, Satyapriya Krishna, Anil Ramakrishna, Mukund Sridhar and Rahul Gupta. Towards Realistic Single-Task Continuous Learning Research for NER. In Findings of The 2021 Conference on Empirical Methods in Natural Language Processing.

talks

Fair Division of Indivisible Resources

Published:

Presented known results from On Approximately Fair Allocations of Indivisible Goods and The Unreasonable Fairness of Maximum Nash Welfare in the UMass CICS Theory Seminar. Video is available at this link.

teaching

CMPSCI 590N: Introduction to Numerical Computing with Python (Fall 2020)

Graduate course, Instructor, UMass Amherst, 2020

Six week course for graduate students at UMass Amherst on using Python and libraries such as Numpy for scientific and numerical computing. I was the sole instructor for this course. I designed the syllabus, recorded and uploaded all lectures and demo sessions, designed and graded all assignments and a final project, and held office hours twice weekly.

CMPSCI 611: Advanced Algorithms (Spring 2021)

Graduate course, Teaching assistant, UMass Amherst, 2021

One of 2 required theory core courses for MS/PhD students at UMass Amherst. Covers many important algorithmic concepts by presenting a few examples of each in detail. Topics include: divide and conquer, matroids, matchings, network flow, randomized algorithms, approximation algorithms, and computational complexity. Instructor is Ramesh Sitaraman.