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Jordan T. Ash
Jordan T. Ash
Microsoft Research NYC
Verified email at princeton.edu - Homepage
Title
Cited by
Cited by
Year
Deep batch active learning by diverse, uncertain gradient lower bounds
JT Ash, C Zhang, A Krishnamurthy, J Langford, A Agarwal
International Conference on Learning Representations, 2020
8932020
On warm-starting neural network training
JT Ash, RP Adams
Neural Information Processing Systems, 2020
222*2020
Transformers learn shortcuts to automata
B Liu, JT Ash, S Goel, A Krishnamurthy, C Zhang
International Conference on Learning Representations, 2023
1722023
Learning deep resnet blocks sequentially using boosting theory
F Huang, JT Ash, J Langford, R Schapire
International Conference on Machine Learning, 2017
1322017
Understanding contrastive learning requires incorporating inductive biases
N Saunshi, JT Ash, S Goel, D Misra, C Zhang, S Arora, S Kakade, ...
International Conference on Machine Learning, 19250-19286, 2022
1282022
Gone Fishing: Neural Active Learning with Fisher Embeddings
JT Ash, S Goel, A Krishnamurthy, S Kakade
Neural Information Processing Systems, 2021
882021
Joint analysis of gene expression levels and histological images identifies genes associated with tissue morphology
JT Ash, G Darnell, D Munro, B Engelhardt
Nature Communications, 458711, 2021
772021
Automated particle picking for low-contrast macromolecules in cryo-electron microscopy
R Langlois, J Pallesen, JT Ash, DN Ho, JL Rubinstein, J Frank
Journal of structural biology 186 (1), 1-7, 2014
672014
Investigating the Role of Negatives in Contrastive Representation Learning
JT Ash, S Goel, A Krishnamurthy, D Misra
Artificial Intelligence and Statistics, 2022
562022
A data-driven computational scheme for the nonlinear mechanical properties of cellular mechanical metamaterials under large deformation
T Xue, A Beatson, M Chiaramonte, G Roeder, JT Ash, Y Menguc, ...
Soft matter 16 (32), 7524-7534, 2020
532020
The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction
P Sharma, JT Ash, D Misra
International Conference on Learning Representations, 2024
472024
Exposing Attention Glitches with Flip-Flop Language Modeling
B Liu, JT Ash, S Goel, A Krishnamurthy, C Zhang
Neural Information Processing Systems, 2023
472023
End-to-end training of deep probabilistic CCA on paired biomedical observations
G Gundersen, B Dumitrascu, JT Ash, BE Engelhardt
Uncertainty in Artificial Intelligence, 2020
282020
Learning Composable Energy Surrogates for PDE Order Reduction
A Beatson, JT Ash, G Roeder, T Xie, RP Adams
Neural Information Processing Systems, 2020
212020
Streaming Active Learning with Deep Neural Networks
A Saran, S Yousefi, A Krishnamurthy, J Langford, JT Ash
International Conference On Machine Learning, 2023
202023
Anti-Concentrated Confidence Bonuses for Scalable Exploration
JT Ash, C Zhang, S Goel, A Krishnamurthy, S Kakade
International Conference on Learning Representations, 2022
112022
An Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models
G Bhatt, Y Chen, AM Das, J Zhang, ST Truong, S Mussmann, Y Zhu, ...
Association for Computational Linguistics, 2024
92024
Unsupervised domain adaptation using approximate label matching
JT Ash, RE Schapire, BE Engelhardt
ICML workshop on implicit generative models, 2017
92017
Scratchable devices: user-friendly programming for household appliances
J Ash, M Babes, G Cohen, S Jalal, S Lichtenberg, M Littman, V Marivate, ...
Human-Computer Interaction. Towards Mobile and Intelligent Interaction …, 2011
82011
Neural Active Learning on Heteroskedastic Distributions
S Khosla, CK Whye, JT Ash, C Zhang, K Kawaguchi, A Lamb
arXiv preprint arXiv:2211.00928, 2022
3*2022
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Articles 1–20