Jordan T. Ash

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 32

Top Topics

Active Learning

Language Modeling

Selective Sampling

Top Venues

Publications

Pratyusha Sharma, Jordan T. Ash, Dipendra Misra
The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction. ICLR (2024)
Arthur Juliani, Jordan T. Ash
A Study of Plasticity Loss in On-Policy Deep Reinforcement Learning. CoRR (2024)
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 (2024)
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)
Akanksha Saran, Safoora Yousefi, Akshay Krishnamurthy, John Langford, Jordan T. Ash
Streaming Active Learning with Deep Neural Networks. CoRR (2023)
Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang
Exposing Attention Glitches with Flip-Flop Language Modeling. NeurIPS (2023)
Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang
Exposing Attention Glitches with Flip-Flop Language Modeling. CoRR (2023)
Pratyusha Sharma, Jordan T. Ash, Dipendra Misra
The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction. CoRR (2023)
Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang
Transformers Learn Shortcuts to Automata. ICLR (2023)
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)
Akanksha Saran, Safoora Yousefi, Akshay Krishnamurthy, John Langford, Jordan T. Ash
Streaming Active Learning with Deep Neural Networks. ICML (2023)
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 (2022)
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)
Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang
Transformers Learn Shortcuts to Automata. CoRR (2022)
Savya Khosla, Chew Kin Whye, Jordan T. Ash, Cyril Zhang, Kenji Kawaguchi, Alex Lamb
Neural Active Learning on Heteroskedastic Distributions. CoRR (2022)
Mark Rucker, Jordan T. Ash, John Langford, Paul Mineiro, Ida Momennejad
Eigen Memory Trees. CoRR (2022)
Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Dipendra Misra
Investigating the Role of Negatives in Contrastive Representation Learning. AISTATS (2022)
Jordan T. Ash, Cyril Zhang, Surbhi Goel, Akshay Krishnamurthy, Sham M. Kakade
Anti-Concentrated Confidence Bonuses For Scalable Exploration. ICLR (2022)
Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Sham M. Kakade
Gone Fishing: Neural Active Learning with Fisher Embeddings. CoRR (2021)
Jordan T. Ash, Cyril Zhang, Surbhi Goel, Akshay Krishnamurthy, Sham M. Kakade
Anti-Concentrated Confidence Bonuses for Scalable Exploration. CoRR (2021)
Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Dipendra Misra
Investigating the Role of Negatives in Contrastive Representation Learning. CoRR (2021)
Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Sham M. Kakade
Gone Fishing: Neural Active Learning with Fisher Embeddings. NeurIPS (2021)
Alex Beatson, Jordan T. Ash, Geoffrey Roeder, Tianju Xue, Ryan P. Adams
Learning Composable Energy Surrogates for PDE Order Reduction. CoRR (2020)
Jordan T. Ash, Ryan P. Adams
On Warm-Starting Neural Network Training. NeurIPS (2020)
Alex Beatson, Jordan T. Ash, Geoffrey Roeder, Tianju Xue, Ryan P. Adams
Learning Composable Energy Surrogates for PDE Order Reduction. NeurIPS (2020)
Jordan T. Ash, Chicheng Zhang, Akshay Krishnamurthy, John Langford, Alekh Agarwal
Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds. ICLR (2020)
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)
Jordan T. Ash, Chicheng Zhang, Akshay Krishnamurthy, John Langford, Alekh Agarwal
Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds. CoRR (2019)
Jordan T. Ash, Ryan P. Adams
On the Difficulty of Warm-Starting Neural Network Training. CoRR (2019)
Furong Huang, Jordan T. Ash, John Langford, Robert E. Schapire
Learning Deep ResNet Blocks Sequentially using Boosting Theory. ICML (2018)
Furong Huang, Jordan T. Ash, John Langford, Robert E. Schapire
Learning Deep ResNet Blocks Sequentially using Boosting Theory. CoRR (2017)
Jordan T. Ash, Robert E. Schapire
Multi-Source Domain Adaptation Using Approximate Label Matching. CoRR (2016)
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)