Michael Carbin

Orcid: 0000-0002-6928-0456

According to our database1, Michael Carbin authored at least 75 papers between 2005 and 2024.

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Bibliography

2024
Quantum Control Machine: The Limits of Control Flow in Quantum Programming.
Proc. ACM Program. Lang., 2024

The T-Complexity Costs of Error Correction for Control Flow in Quantum Computation.
Proc. ACM Program. Lang., 2024

Distributions for Compositionally Differentiating Parametric Discontinuities.
Proc. ACM Program. Lang., 2024

Inference Plans for Hybrid Particle Filtering.
CoRR, 2024

BioMedLM: A 2.7B Parameter Language Model Trained On Biomedical Text.
CoRR, 2024

Learning to Compile Programs to Neural Networks.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

The Cost of Scaling Down Large Language Models: Reducing Model Size Affects Memory before In-context Learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Turaco: Complexity-Guided Data Sampling for Training Neural Surrogates of Programs.
Proc. ACM Program. Lang., October, 2023

The Cost of Down-Scaling Language Models: Fact Recall Deteriorates before In-Context Learning.
CoRR, 2023

Verifying Performance Properties of Probabilistic Inference.
CoRR, 2023

Quantum Control Machine: The Limits of Quantum Programs as Data.
CoRR, 2023

Computably Continuous Reinforcement-Learning Objectives Are PAC-Learnable.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Twist: sound reasoning for purity and entanglement in Quantum programs.
Proc. ACM Program. Lang., 2022

Tower: data structures in Quantum superposition.
Proc. ACM Program. Lang., 2022

Semi-symbolic inference for efficient streaming probabilistic programming.
Proc. ACM Program. Lang., 2022

Acela: Predictable Datacenter-level Maintenance Job Scheduling.
CoRR, 2022

SCOPE: Safe Exploration for Dynamic Computer Systems Optimization.
CoRR, 2022

Cello: Efficient Computer Systems Optimization with Predictive Early Termination and Censored Regression.
CoRR, 2022

Pruning's Effect on Generalization Through the Lens of Training and Regularization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

On the (In)Tractability of Reinforcement Learning for LTL Objectives.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

2021
Simplifying dependent reductions in the polyhedral model.
Proc. ACM Program. Lang., 2021

𝜆ₛ: computable semantics for differentiable programming with higher-order functions and datatypes.
Proc. ACM Program. Lang., 2021

Statically bounded-memory delayed sampling for probabilistic streams.
Proc. ACM Program. Lang., 2021

Exploiting Errors for Efficiency: A Survey from Circuits to Applications.
ACM Comput. Surv., 2021

Reinforcement Learning for General LTL Objectives Is Intractable.
CoRR, 2021

Studying the Consistency and Composability of Lottery Ticket Pruning Masks.
CoRR, 2021

Generalizable and interpretable learning for configuration extrapolation.
Proceedings of the ESEC/FSE '21: 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2021

Programming with neural surrogates of programs.
Proceedings of the Onward! 2021: Proceedings of the 2021 ACM SIGPLAN International Symposium on New Ideas, 2021

On the Predictability of Pruning Across Scales.
Proceedings of the 38th International Conference on Machine Learning, 2021

Pruning Neural Networks at Initialization: Why Are We Missing the Mark?
Proceedings of the 9th International Conference on Learning Representations, 2021

The Lottery Tickets Hypothesis for Supervised and Self-Supervised Pre-Training in Computer Vision Models.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

VeGen: a vectorizer generator for SIMD and beyond.
Proceedings of the ASPLOS '21: 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2021

2020
Trace types and denotational semantics for sound programmable inference in probabilistic languages.
Proc. ACM Program. Lang., 2020

Programming and reasoning with partial observability.
Proc. ACM Program. Lang., 2020

Simplifying Multiple-Statement Reductions with the Polyhedral Model.
CoRR, 2020

λ<sub>S</sub>: Computable semantics for differentiable programming with higher-order functions and datatypes.
CoRR, 2020

TIRAMISU: A Polyhedral Compiler for Dense and Sparse Deep Learning.
CoRR, 2020

Reactive probabilistic programming.
Proceedings of the 41st ACM SIGPLAN International Conference on Programming Language Design and Implementation, 2020

The Lottery Ticket Hypothesis for Pre-trained BERT Networks.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

DiffTune: Optimizing CPU Simulator Parameters with Learned Differentiable Surrogates.
Proceedings of the 53rd Annual IEEE/ACM International Symposium on Microarchitecture, 2020

Linear Mode Connectivity and the Lottery Ticket Hypothesis.
Proceedings of the 37th International Conference on Machine Learning, 2020

Comparing Rewinding and Fine-tuning in Neural Network Pruning.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Sound and robust solid modeling via exact real arithmetic and continuity.
Proc. ACM Program. Lang., 2019

The Lottery Ticket Hypothesis at Scale.
CoRR, 2019

Overparameterization: A Connection Between Software 1.0 and Software 2.0.
Proceedings of the 3rd Summit on Advances in Programming Languages, 2019

Compiler Auto-Vectorization with Imitation Learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

BHive: A Benchmark Suite and Measurement Framework for Validating x86-64 Basic Block Performance Models.
Proceedings of the IEEE International Symposium on Workload Characterization, 2019

Ithemal: Accurate, Portable and Fast Basic Block Throughput Estimation using Deep Neural Networks.
Proceedings of the 36th International Conference on Machine Learning, 2019

The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Leto: verifying application-specific hardware fault tolerance with programmable execution models.
Proc. ACM Program. Lang., 2018

Exploiting Errors for Efficiency: A Survey from Circuits to Algorithms.
CoRR, 2018

Ithemal: Accurate, Portable and Fast Basic Block Throughput Estimation using Deep Neural Networks.
CoRR, 2018

Verifying Programs Under Custom Application-Specific Execution Models.
CoRR, 2018

Verifying Handcoded Probabilistic Inference Procedures.
CoRR, 2018

The Three Pillars of Machine-Based Programming.
CoRR, 2018

The Lottery Ticket Hypothesis: Training Pruned Neural Networks.
CoRR, 2018

The three pillars of machine programming.
Proceedings of the 2nd ACM SIGPLAN International Workshop on Machine Learning and Programming Languages, 2018

Computable decision making on the reals and other spaces: via partiality and nondeterminism.
Proceedings of the 33rd Annual ACM/IEEE Symposium on Logic in Computer Science, 2018

2017
Optimizing CNNs on Multicores for Scalability, Performance and Goodput.
Proceedings of the Twenty-Second International Conference on Architectural Support for Programming Languages and Operating Systems, 2017

2016
Verifying quantitative reliability for programs that execute on unreliable hardware.
Commun. ACM, 2016

2015
Logical reasoning for approximate and unreliable computation.
PhD thesis, 2015

2014
Chisel: reliability- and accuracy-aware optimization of approximate computational kernels.
Proceedings of the 2014 ACM International Conference on Object Oriented Programming Systems Languages & Applications, 2014

2013
Verified integrity properties for safe approximate program transformations.
Proceedings of the ACM SIGPLAN 2013 Workshop on Partial Evaluation and Program Manipulation, 2013

2012
Cryptographic Path Hardening: Hiding Vulnerabilities in Software through Cryptography
CoRR, 2012

Proving acceptability properties of relaxed nondeterministic approximate programs.
Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation, 2012

Bolt: on-demand infinite loop escape in unmodified binaries.
Proceedings of the 27th Annual ACM SIGPLAN Conference on Object-Oriented Programming, 2012

Automatic input rectification.
Proceedings of the 34th International Conference on Software Engineering, 2012

2011
Detecting and Escaping Infinite Loops with Jolt.
Proceedings of the ECOOP 2011 - Object-Oriented Programming, 2011

Dynamic knobs for responsive power-aware computing.
Proceedings of the 16th International Conference on Architectural Support for Programming Languages and Operating Systems, 2011

2010
Automatically identifying critical input regions and code in applications.
Proceedings of the Nineteenth International Symposium on Software Testing and Analysis, 2010

2009
Automatically patching errors in deployed software.
Proceedings of the 22nd ACM Symposium on Operating Systems Principles 2009, 2009

2007
Transactional collection classes.
Proceedings of the 12th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2007

2006
Reflective program generation with patterns.
Proceedings of the Generative Programming and Component Engineering, 2006

2005
Context-sensitive program analysis as database queries.
Proceedings of the Twenty-fourth ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, 2005

Using Datalog with Binary Decision Diagrams for Program Analysis.
Proceedings of the Programming Languages and Systems, Third Asian Symposium, 2005


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