People

Profile

Jason Pacheco

Assistant Professor, Computer Science | Member of the Graduate Faculty

Grants(6)

Page 1 of 2

Publications(23)

Recent

On convergence of polynomial approximations to the Gaussian mixture entropy

2024

Learning Contextualized Action Representations in Sequential Decision Making for Adversarial Malware Optimization

2024

Differentially Private Stochastic Gradient Descent with Fixed-Size Minibatches: Tighter RDP Guarantees with or without Replacement

2024

Efficient Variational Sequential Information Control

2024

Fast variational estimation of mutual information for implicit and explicit likelihood models

2023

Ew-tune: A framework for privately fine-tuning large language models with differential privacy

2022

An Adversarial Reinforcement Learning Framework for Robust Machine Learning-based Malware Detection

2022

How probabilistic electricity demand forecasts can expedite universal access to clean and reliable electricity

2021

Binary black-box attacks against static malware detectors with reinforcement learning in discrete action spaces

2021

Nonparametric object and parts modeling with lie groudynamics

2020

People

Profile

Jason Pacheco

Collaboration(2)

Larry Head

Malak Tfaily

Grants(6)

Publications(23)

On convergence of polynomial approximations to the Gaussian mixture entropy

Learning Contextualized Action Representations in Sequential Decision Making for Adversarial Malware Optimization

Differentially Private Stochastic Gradient Descent with Fixed-Size Minibatches: Tighter RDP Guarantees with or without Replacement

Efficient Variational Sequential Information Control

Fast variational estimation of mutual information for implicit and explicit likelihood models

Ew-tune: A framework for privately fine-tuning large language models with differential privacy

An Adversarial Reinforcement Learning Framework for Robust Machine Learning-based Malware Detection

How probabilistic electricity demand forecasts can expedite universal access to clean and reliable electricity

Binary black-box attacks against static malware detectors with reinforcement learning in discrete action spaces

Nonparametric object and parts modeling with lie groudynamics

Profile

Jason Pacheco

Collaboration(2)

Larry Head

Malak Tfaily

Grants(6)

Publications(23)

On convergence of polynomial approximations to the Gaussian mixture entropy

Learning Contextualized Action Representations in Sequential Decision Making for Adversarial Malware Optimization

Differentially Private Stochastic Gradient Descent with Fixed-Size Minibatches: Tighter RDP Guarantees with or without Replacement

Efficient Variational Sequential Information Control

Fast variational estimation of mutual information for implicit and explicit likelihood models

Ew-tune: A framework for privately fine-tuning large language models with differential privacy

An Adversarial Reinforcement Learning Framework for Robust Machine Learning-based Malware Detection

How probabilistic electricity demand forecasts can expedite universal access to clean and reliable electricity

Binary black-box attacks against static malware detectors with reinforcement learning in discrete action spaces

Nonparametric object and parts modeling with lie groudynamics