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ORCIDJordan T. Ash
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2020 – today
- 2024
[c16]Gantavya Bhatt, Yifang Chen, Arnav Mohanty Das, Jifan Zhang, Sang T. Truong, Stephen Mussmann, Yinglun Zhu, Jeff A. Bilmes, Simon S. Du, Kevin G. Jamieson, Jordan T. Ash, Robert D. Nowak:
An Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models. ACL (Findings) 2024: 6549-6560- [c15]Pratyusha Sharma, Jordan T. Ash, Dipendra Misra:
The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction. ICLR 2024 - [i17]Gantavya Bhatt, Yifang Chen, Arnav Mohanty Das, Jifan Zhang, Sang T. Truong, Stephen Mussmann, Yinglun Zhu, Jeffrey A. Bilmes, Simon S. Du, Kevin G. Jamieson, Jordan T. Ash, Robert D. Nowak:
An Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models. CoRR abs/2401.06692 (2024) - [i16]Arthur Juliani, Jordan T. Ash:
A Study of Plasticity Loss in On-Policy Deep Reinforcement Learning. CoRR abs/2405.19153 (2024) - 2023
- [c14]Savya Khosla, Chew Kin Whye, Jordan T. Ash, Cyril Zhang, Kenji Kawaguchi, Alex Lamb:
Understanding and Improving Neural Active Learning on Heteroskedastic Distributions. ECAI 2023: 1248-1255 - [c13]Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang:
Transformers Learn Shortcuts to Automata. ICLR 2023 - [c12]Akanksha Saran, Safoora Yousefi, Akshay Krishnamurthy, John Langford, Jordan T. Ash:
Streaming Active Learning with Deep Neural Networks. ICML 2023: 30005-30021 - [c11]Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang:
Exposing Attention Glitches with Flip-Flop Language Modeling. NeurIPS 2023 - [i15]Akanksha Saran, Safoora Yousefi, Akshay Krishnamurthy, John Langford, Jordan T. Ash:
Streaming Active Learning with Deep Neural Networks. CoRR abs/2303.02535 (2023) - [i14]Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang:
Exposing Attention Glitches with Flip-Flop Language Modeling. CoRR abs/2306.00946 (2023) - [i13]Pratyusha Sharma, Jordan T. Ash, Dipendra Misra:
The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction. CoRR abs/2312.13558 (2023) - 2022
- [c10]Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Dipendra Misra:
Investigating the Role of Negatives in Contrastive Representation Learning. AISTATS 2022: 7187-7209 - [c9]Jordan T. Ash, Cyril Zhang, Surbhi Goel, Akshay Krishnamurthy, Sham M. Kakade:
Anti-Concentrated Confidence Bonuses For Scalable Exploration. ICLR 2022 - [c8]Nikunj Saunshi, Jordan T. Ash, Surbhi Goel, Dipendra Misra, Cyril Zhang, Sanjeev Arora, Sham M. Kakade, Akshay Krishnamurthy:
Understanding Contrastive Learning Requires Incorporating Inductive Biases. ICML 2022: 19250-19286 - [i12]Nikunj Saunshi, Jordan T. Ash, Surbhi Goel, Dipendra Misra, Cyril Zhang, Sanjeev Arora, Sham M. Kakade, Akshay Krishnamurthy:
Understanding Contrastive Learning Requires Incorporating Inductive Biases. CoRR abs/2202.14037 (2022) - [i11]Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang:
Transformers Learn Shortcuts to Automata. CoRR abs/2210.10749 (2022) - [i10]Mark Rucker, Jordan T. Ash, John Langford, Paul Mineiro, Ida Momennejad:
Eigen Memory Trees. CoRR abs/2210.14077 (2022) - [i9]Savya Khosla, Chew Kin Whye, Jordan T. Ash, Cyril Zhang, Kenji Kawaguchi, Alex Lamb:
Neural Active Learning on Heteroskedastic Distributions. CoRR abs/2211.00928 (2022) - 2021
- [c7]Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Sham M. Kakade:
Gone Fishing: Neural Active Learning with Fisher Embeddings. NeurIPS 2021: 8927-8939 - [i8]Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Sham M. Kakade:
Gone Fishing: Neural Active Learning with Fisher Embeddings. CoRR abs/2106.09675 (2021) - [i7]Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Dipendra Misra:
Investigating the Role of Negatives in Contrastive Representation Learning. CoRR abs/2106.09943 (2021) - [i6]Jordan T. Ash, Cyril Zhang, Surbhi Goel, Akshay Krishnamurthy, Sham M. Kakade:
Anti-Concentrated Confidence Bonuses for Scalable Exploration. CoRR abs/2110.11202 (2021) - 2020
- [c6]Jordan T. Ash, Chicheng Zhang, Akshay Krishnamurthy, John Langford, Alekh Agarwal:
Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds. ICLR 2020 - [c5]Jordan T. Ash, Ryan P. Adams:
On Warm-Starting Neural Network Training. NeurIPS 2020 - [c4]Alex Beatson, Jordan T. Ash, Geoffrey Roeder, Tianju Xue, Ryan P. Adams:
Learning Composable Energy Surrogates for PDE Order Reduction. NeurIPS 2020 - [i5]Alex Beatson, Jordan T. Ash, Geoffrey Roeder, Tianju Xue, Ryan P. Adams:
Learning Composable Energy Surrogates for PDE Order Reduction. CoRR abs/2005.06549 (2020)
2010 – 2019
- 2019
- [c3]Gregory W. Gundersen, Bianca Dumitrascu, Jordan T. Ash, Barbara E. Engelhardt:
End-to-end Training of Deep Probabilistic CCA on Paired Biomedical Observations. UAI 2019: 945-955 - [i4]Jordan T. Ash, Chicheng Zhang, Akshay Krishnamurthy, John Langford, Alekh Agarwal:
Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds. CoRR abs/1906.03671 (2019) - [i3]Jordan T. Ash, Ryan P. Adams:
On the Difficulty of Warm-Starting Neural Network Training. CoRR abs/1910.08475 (2019) - 2018
- [c2]Furong Huang, Jordan T. Ash, John Langford, Robert E. Schapire:
Learning Deep ResNet Blocks Sequentially using Boosting Theory. ICML 2018: 2063-2072 - 2017
- [i2]Furong Huang, Jordan T. Ash, John Langford, Robert E. Schapire:
Learning Deep ResNet Blocks Sequentially using Boosting Theory. CoRR abs/1706.04964 (2017) - 2016
- [i1]Jordan T. Ash, Robert E. Schapire:
Multi-Source Domain Adaptation Using Approximate Label Matching. CoRR abs/1602.04889 (2016) - 2011
- [c1]Jordan T. Ash, Monica Babes, Gal Cohen, Sameen Jalal, Sam Lichtenberg, Michael L. Littman, Vukosi Marivate
, Phillip Quiza, Blase Ur, Emily Zhang:
Scratchable Devices: User-Friendly Programming for Household Appliances. HCI (3) 2011: 137-146
Coauthor Index
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last updated on 2024-09-26 00:59 CEST by the dblp team
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