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06/01/2023
Exposing Attention Glitches with Flip-Flop Language Modeling
Why do large language models sometimes output factual inaccuracies and e...
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03/05/2023
Streaming Active Learning with Deep Neural Networks
Active learning is perhaps most naturally posed as an online learning pr...
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11/02/2022
Neural Active Learning on Heteroskedastic Distributions
Models that can actively seek out the best quality training data hold th...
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10/25/2022
Eigen Memory Tree
This work introduces the Eigen Memory Tree (EMT), a novel online memory ...
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10/19/2022
Transformers Learn Shortcuts to Automata
Algorithmic reasoning requires capabilities which are most naturally und...
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10/21/2021
Anti-Concentrated Confidence Bonuses for Scalable Exploration
Intrinsic rewards play a central role in handling the exploration-exploi...
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06/18/2021
Investigating the Role of Negatives in Contrastive Representation Learning
Noise contrastive learning is a popular technique for unsupervised repre...
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06/17/2021
Gone Fishing: Neural Active Learning with Fisher Embeddings
There is an increasing need for effective active learning algorithms tha...
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05/13/2020
Learning Composable Energy Surrogates for PDE Order Reduction
Meta-materials are an important emerging class of engineered materials i...
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10/18/2019
On the Difficulty of Warm-Starting Neural Network Training
In many real-world deployments of machine learning systems, data arrive ...
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06/09/2019
Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds
We design a new algorithm for batch active learning with deep neural net...
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02/16/2016
