Saeid Naderiparizi

I am a second year M.Sc. student in Computer Science at the University of British Columbia, working with Frank Wood.
My research interests are machine learning, Bayesian inference and, optimization.

Email  /  CV  /  GitHub  /  LinkedIn



LaTeq: Converting equation images to LaTeX
Under supervision of Frank Wood

We trained a generative model for LaTeX equation codes, which will be used as a part of a probabilistic program to perform Bayesian inference for converting equation images to LaTeX codes.

A bayesian approach to Visual Question Answering
Gursimran Singh, Saeid Naderiparizi, Setareh Cohan
Probabilistic Programming course, 2018

Using probabilistic programming and inference compilation to solve visual question answering task.


RegNet: Regularizing Deep Networks (code)
Setareh Cohan, Saeid Naderiparizi
Multimodal Learning with Vision, Language and Sound course, 2018

We can define regularizers to improve model's performance in the case of not having enough data for few classes. We tried different regularizers and tested it on image classification task.


A Multi-Plane Block-Coordinate Frank-Wolfe Algorithm for Training Latent Structural SVMs
Under supervision of Christoph H. Lampert

We designed and implemented a method for training Latent Structural SVMs with costly max-oracles using Frank-Wolfe algorithm on the dual objective. The method does not need specifying a learning rate and it gives a definite result.


Sequential Bound Optimization
Under supervision of Sobhan Naderi Parizi

We proposed an iterative procedure for optimizing non-convex objective functions that works by optimizing a sequence of convex bounds on the true objective.

Selected course Projects

Learning to ride a bike (code)
Setareh Cohan, Saeid Naderiparizi
Computer Animation course, 2017

We implemented a simulator for bicycle motion and used Fitted Value Iteration algorithm for learning to keep the bike balanced. The next goal is to add a target point which the bike should learn to get there and meanwhile, keep the bike balanced.


Learning Influence Probabilities under ICIDT model (code)
Saeid Naderiparizi, Polina Zablotskaia, Setareh Cohan
Topics in Data Management - Social and Information Networks course, 2017

We came up with a model for influence propagation in social networks which captures decay in adoption probabilities over time and implemented maximum likelihood estimation in C++ to learn the probabilities under this model. To my knowledge, the problem of learning probabilities in this time decaying model had not been studied before.

Implementation of a 3D reconstruction system
Saeid Naderiparizi, Setareh Cohan
Fundamentals of 3D Computer Vision course, 2016

Implemented an algortithm to generate the point cloud of a 3D object using a few photos taken of it. It uses SURF features to find and match keypoints, find position of cameras and then aggregates them to generate the point cloud. This project is done in Matlab.


Implemetation of Bitonic Sort in CUDA for NVIDIA GPUs
Fundamentals of Multicore Computing course, 2015

Implemented Bitonic Sort in CUDA and parallelized it according to the NVIDIA architecture to maximize performance.

UBC logo

University of British Columbia
M.Sc. in Computer Science
Supervisor: Frank Wood

Sharif logo

Sharif University of Technology
B.Sc. in Computer Engineering
Minor degree in Mathematics

Website source forked from Jon Barron.