Contains implementations of several common machine learning models and optimization techniques used for regression and classification problems.

STAT 671 Cats and Dogs Classifier Demo

Nystrom Low Rank Gram Matrix Approximation in KELP

ExplainPolySVM is a python package to provide interpretation and explainability to Support Vector Machine models trained with polynomial kernels. The package can be used with any SVM model as long as the components of the model can be extracted.

A Python-based tool designed to attempt to hide processes from task managers.

Summer@ICERM 2020 - Random Projections

In terms of design, the Pixel 5 looks similar to the $499 Pixel 4a 5G. And at 5.7 by 2.8 by 0.3 inches (HWD) and weighs 5.3 ounces, it’s almost the same size and weight as the $349 Pixel 4a. It’s currently available in black or sage, though Google showed a gray model at its launch event that we hope will be available in the future.

Machine Learning Algorithms

Assignments done as a part of my SMAI-Course

ln estimation and kernel smoothing with C and R

UAI 2020. Kernel goodness-of-fit tests for conditional density models.

A novel incremental hierarchical clustering algorithm (KDD 22)

Implementation of Ada-BKB a scalable Gaussian Process bandit optimization algorithm

KSDAgg package implementing the KSDAgg test proposed in KSD Aggregated Goodness-of-fit Test by Schrab, Guedj and Gretton: https://arxiv.org/abs/2202.00824 NeurIPS 2022

Hardware-based attestation / intrusion detection app for Android devices. It provides both local verification with another Android device via QR codes and optional scheduled server-based verification with support for alert emails. It uses hardware-backed keys and attestation support as the foundation and chains trust to the app for software checks.

A library of smoothing kernels in multiple languages for use in kernel regression and kernel density estimation.

SVM trained by the PEGASOS Stochastic Subgradient Descent algorithm

Notes, Homework and Projects for PSU's STAT 671 Statistical Learning course, Fall 2019.