Brandon Amos

Orcid: 0000-0003-2884-0119

Affiliations:
  • Facebook AI, New Yourk City, Ny, USA
  • Carnegie Mellon University, Pittsburgh, PA, USA (PhD 2019)
  • Virginia Tech, Blacksburg, VA, USA


According to our database1, Brandon Amos authored at least 57 papers between 2013 and 2023.

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Bibliography

2023
Tutorial on Amortized Optimization.
Found. Trends Mach. Learn., 2023

Stochastic Optimal Control Matching.
CoRR, 2023

Learning to Warm-Start Fixed-Point Optimization Algorithms.
CoRR, 2023

Landscape Surrogate: Learning Decision Losses for Mathematical Optimization Under Partial Information.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

TaskMet: Task-driven Metric Learning for Model Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

End-to-End Learning to Warm-Start for Real-Time Quadratic Optimization.
Proceedings of the Learning for Dynamics and Control Conference, 2023

Semi-Supervised Offline Reinforcement Learning with Action-Free Trajectories.
Proceedings of the International Conference on Machine Learning, 2023

Multisample Flow Matching: Straightening Flows with Minibatch Couplings.
Proceedings of the International Conference on Machine Learning, 2023

Meta Optimal Transport.
Proceedings of the International Conference on Machine Learning, 2023

On amortizing convex conjugates for optimal transport.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Tutorial on amortized optimization for learning to optimize over continuous domains.
CoRR, 2022

Nocturne: a scalable driving benchmark for bringing multi-agent learning one step closer to the real world.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Theseus: A Library for Differentiable Nonlinear Optimization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Semi-Discrete Normalizing Flows through Differentiable Tessellation.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Matching Normalizing Flows and Probability Paths on Manifolds.
Proceedings of the International Conference on Machine Learning, 2022

Cross-Domain Imitation Learning via Optimal Transport.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Input Convex Gradient Networks.
CoRR, 2021

Neural Fixed-Point Acceleration for Convex Optimization.
CoRR, 2021

MBRL-Lib: A Modular Library for Model-based Reinforcement Learning.
CoRR, 2021

Scalable Online Planning via Reinforcement Learning Fine-Tuning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On the model-based stochastic value gradient for continuous reinforcement learning.
Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

CombOptNet: Fit the Right NP-Hard Problem by Learning Integer Programming Constraints.
Proceedings of the 38th International Conference on Machine Learning, 2021

Riemannian Convex Potential Maps.
Proceedings of the 38th International Conference on Machine Learning, 2021

Neural Spatio-Temporal Point Processes.
Proceedings of the 9th International Conference on Learning Representations, 2021

Learning Neural Event Functions for Ordinary Differential Equations.
Proceedings of the 9th International Conference on Learning Representations, 2021

Aligning Time Series on Incomparable Spaces.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Improving Sample Efficiency in Model-Free Reinforcement Learning from Images.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Algorithm 1007: QNSTOP - Quasi-Newton Algorithm for Stochastic Optimization.
ACM Trans. Math. Softw., 2020

Objective Mismatch in Model-based Reinforcement Learning.
Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

The Differentiable Cross-Entropy Method.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Quasi-Newton Stochastic Optimization Algorithm for Parameter Estimation of a Stochastic Model of the Budding Yeast Cell Cycle.
IEEE ACM Trans. Comput. Biol. Bioinform., 2019

Generalized Inner Loop Meta-Learning.
CoRR, 2019

The Limited Multi-Label Projection Layer.
CoRR, 2019

Differentiable Convex Optimization Layers.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018
Enabling Live Video Analytics with a Scalable and Privacy-Aware Framework.
ACM Trans. Multim. Comput. Commun. Appl., 2018

Depth-Limited Solving for Imperfect-Information Games.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Differentiable MPC for End-to-end Planning and Control.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Learning Awareness Models.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017
Task-based End-to-end Model Learning.
CoRR, 2017

Task-based End-to-end Model Learning in Stochastic Optimization.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

A Scalable and Privacy-Aware IoT Service for Live Video Analytics.
Proceedings of the 8th ACM on Multimedia Systems Conference, 2017

Input Convex Neural Networks.
Proceedings of the 34th International Conference on Machine Learning, 2017

OptNet: Differentiable Optimization as a Layer in Neural Networks.
Proceedings of the 34th International Conference on Machine Learning, 2017

You can teach elephants to dance: agile VM handoff for edge computing.
Proceedings of the Second ACM/IEEE Symposium on Edge Computing, San Jose / Silicon Valley, 2017

An empirical study of latency in an emerging class of edge computing applications for wearable cognitive assistance.
Proceedings of the Second ACM/IEEE Symposium on Edge Computing, San Jose / Silicon Valley, 2017

2016
HotMobile 2016.
IEEE Pervasive Comput., 2016

Privacy Mediators: Helping IoT Cross the Chasm.
Proceedings of the 17th International Workshop on Mobile Computing Systems and Applications, 2016

Collapsed Variational Inference for Sum-Product Networks.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Quantifying the Impact of Edge Computing on Mobile Applications.
Proceedings of the 7th ACM SIGOPS Asia-Pacific Workshop on Systems, 2016

2015
Edge Analytics in the Internet of Things.
IEEE Pervasive Comput., 2015

Bad Parts: Are Our Manufacturing Systems at Risk of Silent Cyberattacks?
IEEE Secur. Priv., 2015

The Case for Offload Shaping.
Proceedings of the 16th International Workshop on Mobile Computing Systems and Applications, 2015

Early Implementation Experience with Wearable Cognitive Assistance Applications.
Proceedings of the 2015 workshop on Wearable Systems and Applications, 2015

2014
Global parameter estimation for a eukaryotic cell cycle model in systems biology.
Proceedings of the 2014 Summer Simulation Multiconference, 2014

Fortran 95 implementation of QNSTOP for global and stochastic optimization.
Proceedings of the 2014 Spring Simulation Multiconference, 2014

Performance Study of Spindle, A Web Analytics Query Engine Implemented in Spark.
Proceedings of the IEEE 6th International Conference on Cloud Computing Technology and Science, 2014

2013
Applying machine learning classifiers to dynamic Android malware detection at scale.
Proceedings of the 2013 9th International Wireless Communications and Mobile Computing Conference, 2013


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