Jordan Ash
8 papers · 2018–2024 · 4 venues · across top CS/AI venues
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Achievements
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🌍 Conference Polyglot · Bronze 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (26) 🐣 Hot Topic Early Bird
🔥
Unstoppable · Bronze
Venues
Top co-authors
Research topics
Machine Learning
(8)
Learning Types · Machine Learning
(6)
Deep Learning
(5)
Optimization & Theory
(5)
Artificial Intelligence
(4)
Learning Types · Deep Learning
(3)
Natural Language Processing
(2)
Core AI
(2)
Core Methods
(2)
Resources & Methods
(2)
Mathematics & Optimization
(1)
Application Areas
(1)
Architectures
(1)
Bayesian & Probabilistic
(1)
Learning Paradigms
(1)
Keywords
neural network
(2)
large language model
(2)
inductive bia
(2)
active learning
(2)
neural network training
(1)
model selection
(1)
representation learning
(1)
language modeling
(1)
warm starting
(1)
incremental learning
(1)
energy minimization
(1)
maximum likelihood
(1)
fisher information
(1)
experimental design
(1)
label efficiency
(1)
attention mechanism
(1)
parametric optimization
(1)
generalization error bound
(1)
unsupervised representation learning
(1)
margin theory
(1)
Papers
An Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models
ACL 2024
Exposing Attention Glitches with Flip-Flop Language Modeling
NeurIPS 2023
Investigating the Role of Negatives in Contrastive Representation Learning
AISTATS 2022
Understanding Contrastive Learning Requires Incorporating Inductive Biases
ICML 2022
Gone Fishing: Neural Active Learning with Fisher Embeddings
NeurIPS 2021
Learning Composable Energy Surrogates for PDE Order Reduction
NeurIPS 2020
On Warm-Starting Neural Network Training
NeurIPS 2020
Learning Deep ResNet Blocks Sequentially using Boosting Theory
ICML 2018