Davis W. Blalock

25 papers A* 5A 1Journal 16Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	FlashOptim: Optimizers for Memory Efficient Training. CoRR Jose Javier Gonzalez Ortiz, Abhay Gupta, Chris Renard, Davis W. Blalock
2025	A*	`conf`	µnit Scaling: Simple and Scalable FP8 LLM Training. ICML Saaketh Narayan, Abhay Gupta, Mansheej Paul, Davis W. Blalock
2025	J	`jnl`	μnit Scaling: Simple and Scalable FP8 LLM Training. CoRR Saaketh Narayan, Abhay Gupta, Mansheej Paul, Davis W. Blalock
2024	—	`conf`	Dynamic Masking Rate Schedules for MLM Pretraining. EACL (2) Zachary Ankner, Naomi Saphra, Davis W. Blalock, Jonathan Frankle, Matthew L. Leavitt
2023	J	`jnl`	Compute-Efficient Deep Learning: Algorithmic Trends and Opportunities. J. Mach. Learn. Res. Brian R. Bartoldson, Bhavya Kailkhura, Davis W. Blalock
2023	J	`jnl`	Dynamic Masking Rate Schedules for MLM Pretraining. CoRR Zachary Ankner, Naomi Saphra, Davis W. Blalock, Jonathan Frankle, Matthew L. Leavitt
2022	A	`conf`	Causally motivated shortcut removal using auxiliary labels. AISTATS Maggie Makar, Ben Packer, Dan Moldovan, Davis W. Blalock, Yoni Halpern, Alexander D'Amour
2022	J	`jnl`	Compute-Efficient Deep Learning: Algorithmic Trends and Opportunities. CoRR Brian R. Bartoldson, Bhavya Kailkhura, Davis W. Blalock
2022	J	`jnl`	Fast Benchmarking of Accuracy vs. Training Time with Cyclic Learning Rates. CoRR Jacob P. Portes, Davis W. Blalock, Cory Stephenson, Jonathan Frankle
2021	A*	`conf`	Better Aggregation in Test-Time Augmentation. ICCV Divya Shanmugam, Davis W. Blalock, Guha Balakrishnan, John V. Guttag
2021	J	`jnl`	Causally-motivated Shortcut Removal Using Auxiliary Labels. CoRR Maggie Makar, Ben Packer, Dan Moldovan, Davis W. Blalock, Yoni Halpern, Alexander D'Amour
2021	A*	`conf`	Multiplying Matrices Without Multiplying. ICML Davis W. Blalock, John V. Guttag
2021	J	`jnl`	Multiplying Matrices Without Multiplying. CoRR Davis W. Blalock, John V. Guttag
2020	—	`conf`	What is the State of Neural Network Pruning? MLSys Davis W. Blalock, Jose Javier Gonzalez Ortiz, Jonathan Frankle, John V. Guttag
2020	J	`jnl`	What is the State of Neural Network Pruning? CoRR Davis W. Blalock, Jose Javier Gonzalez Ortiz, Jonathan Frankle, John V. Guttag
2020	J	`jnl`	When and Why Test-Time Augmentation Works. CoRR Divya Shanmugam, Davis W. Blalock, Guha Balakrishnan, John V. Guttag
2019	—	`conf`	Multiple Instance Learning for ECG Risk Stratification. MLHC Divya Shanmugam, Davis W. Blalock, John V. Guttag
2018	J	`jnl`	Multiple Instance Learning for ECG Risk Stratification. CoRR Divya Shanmugam, Davis W. Blalock, Jen J. Gong, John V. Guttag
2018	J	`jnl`	Sprintz: Time Series Compression for the Internet of Things. CoRR Davis W. Blalock, Samuel Madden, John V. Guttag
2018	J	`jnl`	Sprintz: Time Series Compression for the Internet of Things. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. Davis W. Blalock, Samuel Madden, John V. Guttag
2017	A*	`conf`	Bolt: Accelerated Data Mining with Fast Vector Compression. KDD Davis W. Blalock, John V. Guttag
2017	J	`jnl`	Bolt: Accelerated Data Mining with Fast Vector Compression. CoRR Davis W. Blalock, John V. Guttag
2016	A*	`conf`	EXTRACT: Strong Examples from Weakly-Labeled Sensor Data. ICDM Davis W. Blalock, John V. Guttag
2016	J	`jnl`	EXTRACT: Strong Examples from Weakly-Labeled Sensor Data. CoRR Davis W. Blalock, John V. Guttag
2015	J	`jnl`	Adaptive Synaptogenesis Constructs Neural Codes That Benefit Discrimination. PLoS Comput. Biol. Blake T. Thomas, Davis W. Blalock, William B. Levy