Jason L. Pacheco

Orcid: 0000-0003-1711-1041

Affiliations:
  • University of Arizona, Tucson, AZ, USA
  • MIT CSAIL, MA, USA (former)


According to our database1, Jason L. Pacheco authored at least 20 papers between 2009 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2023
Network-Level Safety Metrics for Overall Traffic Safety Assessment: A Case Study.
IEEE Access, 2023

On Convergence of Polynomial Approximations to the Gaussian Mixture Entropy.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Fast Variational Estimation of Mutual Information for Implicit and Explicit Likelihood Models.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Network-level Safety Metrics for Overall Traffic Safety Assessment: A Case Study.
CoRR, 2022

An Adversarial Reinforcement Learning Framework for Robust Machine Learning-based Malware Detection.
Proceedings of the IEEE International Conference on Data Mining Workshops, 2022

EW-Tune: A Framework for Privately Fine-Tuning Large Language Models with Differential Privacy.
Proceedings of the IEEE International Conference on Data Mining Workshops, 2022

2021
Binary Black-Box Attacks Against Static Malware Detectors with Reinforcement Learning in Discrete Action Spaces.
Proceedings of the IEEE Security and Privacy Workshops, 2021

2020
Lightweight Data Fusion with Conjugate Mappings.
CoRR, 2020

Sequential Bayesian Experimental Design with Variable Cost Structure.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Nonparametric Object and Parts Modeling With Lie Group Dynamics.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
Variational Information Planning for Sequential Decision Making.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
A Robust Approach to Sequential Information Theoretic Planning.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Multiscale Semi-Markov Dynamics for Intracortical Brain-Computer Interfaces.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016
Variational Approximations with Diverse Applications.
PhD thesis, 2016

2015
Proteins, Particles, and Pseudo-Max-Marginals: A Submodular Approach.
Proceedings of the 32nd International Conference on Machine Learning, 2015

2014
Preserving Modes and Messages via Diverse Particle Selection.
Proceedings of the 31th International Conference on Machine Learning, 2014

2012
Improved variational inference for tracking in clutter.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2012

Minimization of Continuous Bethe Approximations: A Positive Variation.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2011
Performance analysis of Adaptive Probabilistic Multi-hypothesis Tracking with the Metron data sets.
Proceedings of the 14th International Conference on Information Fusion, 2011

2009
Performance analysis of the Probabilistic Multi-hypothesis Tracking algorithm on the SEABAR data sets.
Proceedings of the 12th International Conference on Information Fusion, 2009


  Loading...