Michael Carbin
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
33
Venues
19
Active years
2005–2025
Best venue rank
A*
Where they publish
Papers
33 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICML | Learning to Keep a Promise: Scaling Language Model Decoding Parallelism with Learned Asynchronous Decoding. | Tian Jin, Ellie Y. Cheng, Zachary Ankner, Nikunj Saunshi, Blake M. Elias, Amir Yazdanbakhsh, Jonathan Ragan-Kelley, Suvinay Subramanian, Michael Carbin |
| 2024 | ICLR | The Cost of Scaling Down Large Language Models: Reducing Model Size Affects Memory before In-context Learning. | Tian Jin, Nolan Clement, Xin Dong, Vaishnavh Nagarajan, Michael Carbin, Jonathan Ragan-Kelley, Gintare Karolina Dziugaite |
| 2024 | ICML | Learning to Compile Programs to Neural Networks. | Logan Weber, Jesse Michel, Alex Renda, Michael Carbin |
| 2023 | AAAI | Computably Continuous Reinforcement-Learning Objectives Are PAC-Learnable. | Cambridge Yang, Michael Littman, Michael Carbin |
| 2022 | IJCAI | On the (In)Tractability of Reinforcement Learning for LTL Objectives. | Cambridge Yang, Michael L. Littman, Michael Carbin |
| 2021 | ASPLOS | VeGen: a vectorizer generator for SIMD and beyond. | Yishen Chen, Charith Mendis, Michael Carbin, Saman P. Amarasinghe |
| 2021 | CVPR | The Lottery Tickets Hypothesis for Supervised and Self-Supervised Pre-Training in Computer Vision Models. | Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Michael Carbin, Zhangyang Wang |
| 2021 | ICLR | Pruning Neural Networks at Initialization: Why Are We Missing the Mark? | Jonathan Frankle, Gintare Karolina Dziugaite, Daniel M. Roy, Michael Carbin |
| 2021 | ICML | On the Predictability of Pruning Across Scales. | Jonathan S. Rosenfeld, Jonathan Frankle, Michael Carbin, Nir Shavit |
| 2021 | OOPSLA | Programming with neural surrogates of programs. | Alex Renda, Yi Ding, Michael Carbin |
| 2020 | ICLR | Comparing Rewinding and Fine-tuning in Neural Network Pruning. | Alex Renda, Jonathan Frankle, Michael Carbin |
| 2020 | ICML | Linear Mode Connectivity and the Lottery Ticket Hypothesis. | Jonathan Frankle, Gintare Karolina Dziugaite, Daniel M. Roy, Michael Carbin |
| 2020 | MICRO | DiffTune: Optimizing CPU Simulator Parameters with Learned Differentiable Surrogates. | Alex Renda, Yishen Chen, Charith Mendis, Michael Carbin |
| 2020 | PLDI | Reactive probabilistic programming. | Guillaume Baudart, Louis Mandel, Eric Atkinson, Benjamin Sherman, Marc Pouzet, Michael Carbin |
| 2019 | ICLR | The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks. | Jonathan Frankle, Michael Carbin |
| 2019 | ICML | Ithemal: Accurate, Portable and Fast Basic Block Throughput Estimation using Deep Neural Networks. | Charith Mendis, Alex Renda, Saman P. Amarasinghe, Michael Carbin |
| 2018 | LICS | Computable decision making on the reals and other spaces: via partiality and nondeterminism. | Benjamin Sherman, Luke Sciarappa, Adam Chlipala, Michael Carbin |
| 2018 | PLDI | The three pillars of machine programming. | Justin Gottschlich, Armando Solar-Lezama, Nesime Tatbul, Michael Carbin, Martin C. Rinard, Regina Barzilay, Saman P. Amarasinghe, Joshua B. Tenenbaum, Tim Mattson |
| 2017 | ASPLOS | Optimizing CNNs on Multicores for Scalability, Performance and Goodput. | Samyam Rajbhandari, Yuxiong He, Olatunji Ruwase, Michael Carbin, Trishul M. Chilimbi |
| 2014 | OOPSLA | Chisel: reliability- and accuracy-aware optimization of approximate computational kernels. | Sasa Misailovic, Michael Carbin, Sara Achour, Zichao Qi, Martin C. Rinard |
| 2013 | OOPSLA | Verifying quantitative reliability for programs that execute on unreliable hardware. | Michael Carbin, Sasa Misailovic, Martin C. Rinard |
| 2013 | PEPM | Verified integrity properties for safe approximate program transformations. | Michael Carbin, Deokhwan Kim, Sasa Misailovic, Martin C. Rinard |
| 2012 | ICSE | Automatic input rectification. | Fan Long, Vijay Ganesh, Michael Carbin, Stelios Sidiroglou, Martin C. Rinard |
| 2012 | OOPSLA | Bolt: on-demand infinite loop escape in unmodified binaries. | Michael Kling, Sasa Misailovic, Michael Carbin, Martin C. Rinard |
| 2012 | PLDI | Proving acceptability properties of relaxed nondeterministic approximate programs. | Michael Carbin, Deokhwan Kim, Sasa Misailovic, Martin C. Rinard |
| 2011 | ASPLOS | Dynamic knobs for responsive power-aware computing. | Henry Hoffmann, Stelios Sidiroglou, Michael Carbin, Sasa Misailovic, Anant Agarwal, Martin C. Rinard |
| 2011 | ECOOP | Detecting and Escaping Infinite Loops with Jolt. | Michael Carbin, Sasa Misailovic, Michael Kling, Martin C. Rinard |
| 2010 | ISSTA | Automatically identifying critical input regions and code in applications. | Michael Carbin, Martin C. Rinard |
| 2009 | SOSP | Automatically patching errors in deployed software. | Jeff H. Perkins, Sunghun Kim, Samuel Larsen, Saman P. Amarasinghe, Jonathan Bachrach, Michael Carbin, Carlos Pacheco, Frank Sherwood, Stelios Sidiroglou, Gregory T. Sullivan, Weng-Fai Wong, Yoav Zibin, Michael D. Ernst, Martin C. Rinard |
| 2007 | PPoPP | Transactional collection classes. | Brian D. Carlstrom, Austen McDonald, Michael Carbin, Christos Kozyrakis, Kunle Olukotun |
| 2006 | GPCE | Reflective program generation with patterns. | Manuel Fhndrich, Michael Carbin, James R. Larus |
| 2005 | APLAS | Using Datalog with Binary Decision Diagrams for Program Analysis. | John Whaley, Dzintars Avots, Michael Carbin, Monica S. Lam |
| 2005 | PODS | Context-sensitive program analysis as database queries. | Monica S. Lam, John Whaley, V. Benjamin Livshits, Michael C. Martin, Dzintars Avots, Michael Carbin, Christopher Unkel |