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Profile
Jason Pacheco
Assistant Professor, Computer Science | Member of the Graduate Faculty
Computer Science
Full Page
Overview
Research
More
Collaboration
(2)
Larry Head
Mutual work: 1 Proposal﹒1 Grant
Collaboration Details
Malak Tfaily
Mutual work: 1 Proposal
Collaboration Details
Grants
(6)
Inference Methods for use with Simulation Models
Active
·
2024
·
$38.5K
·
External
Principal Investigator (PI)
inference methods,
simulation models,
statistical inference,
simulation methods,
computational modeling
Robust Maximum Entropy Planning, Learning and Control in Uncertain Environments
Active
·
2022
·
$422.6K
·
External
Principal Investigator (PI)
planning,
learning,
control,
uncertainty,
entropy
Development of Inference Capabilities for 1D and 3D Material Simulation Models
2023
·
$37.1K
·
External
Principal Investigator (PI)
material simulation,
inference,
1d modeling,
3d modeling,
development
Estimation of Stochastic Surface and Region Growth from Temporally Sparse and Spatially Dense Geophysical Data
2021
·
$60K
·
External
Principal Investigator (PI)
stochastic modeling,
geophysical data analysis,
spatial-temporal analysis,
surface growth,
region growth
Estimation of Stochastic Surface and Region Growth from Temporally Sparse and Spatially Dense Geophysical Data
2021
·
$60K
·
External
Principal Investigator (PI)
geophysical data,
stochastic processes,
surface growth,
region growth,
temporal-spatial analysis
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Publications
(23)
Recent
Efficient Variational Sequential Information Control
2024
variational inference,
efficient algorithms,
information processing,
optimal control
On convergence of polynomial approximations to the Gaussian mixture entropy
2024
convergence analysis,
probabilistic methods
Differentially Private Stochastic Gradient Descent with Fixed-Size Minibatches: Tighter RDP Guarantees with or without Replacement
2024
differential privacy,
stochastic gradient descent,
data privacy
Learning Contextualized Action Representations in Sequential Decision Making for Adversarial Malware Optimization
2024
malware detection,
sequential decision making
Fast variational estimation of mutual information for implicit and explicit likelihood models
2023
variational inference,
mutual information,
likelihood models,
estimation methods
Ew-tune: A framework for privately fine-tuning large language models with differential privacy
2022
privacy,
fine-tuning,
framework,
differential privacy
An Adversarial Reinforcement Learning Framework for Robust Machine Learning-based Malware Detection
2022
reinforcement learning,
malware detection,
adversarial learning,
machine learning,
robust framework
How probabilistic electricity demand forecasts can expedite universal access to clean and reliable electricity
2021
electricity demand,
clean energy,
probabilistic forecasting,
universal access,
reliable electricity
Binary black-box attacks against static malware detectors with reinforcement learning in discrete action spaces
2021
malware detection,
reinforcement learning,
adversarial attacks,
black-box attacks,
static analysis
Nonparametric object and parts modeling with lie groudynamics
2020
nonparametric modeling,
object modeling,
parts modeling,
lie group dynamics,
machine learning
