Yoonho Lee | DeepAI

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Featured Co-authors

Sergey Levine
379 publications
Chelsea Finn
167 publications
Percy Liang
165 publications
Yee Whye Teh
122 publications
Sung Ju Hwang
109 publications
Christopher D. Manning
79 publications
Jung-Woo Ha
58 publications
Eunho Yang
58 publications
Juho Lee
50 publications
Suha Kwak
39 publications
Huaxiu Yao
32 publications

∙ 06/19/2023

Confidence-Based Model Selection: When to Take Shortcuts for Subpopulation Shifts

Effective machine learning models learn both robust features that direct...

0 Annie S. Chen, et al. ∙

∙ 06/08/2023

Conservative Prediction via Data-Driven Confidence Minimization

Errors of machine learning models are costly, especially in safety-criti...

0 Caroline Choi, et al. ∙

∙ 02/10/2023

Project and Probe: Sample-Efficient Domain Adaptation by Interpolating Orthogonal Features

Conventional approaches to robustness try to learn a model based on caus...

0 Annie S. Chen, et al. ∙

∙ 01/26/2023

DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature

The fluency and factual knowledge of large language models (LLMs) height...

0 Eric Mitchell, et al. ∙

∙ 11/25/2022

Wild-Time: A Benchmark of in-the-Wild Distribution Shift over Time

Distribution shift occurs when the test distribution differs from the tr...

0 Huaxiu Yao, et al. ∙

∙ 10/20/2022

Surgical Fine-Tuning Improves Adaptation to Distribution Shifts

A common approach to transfer learning under distribution shift is to fi...

6 Yoonho Lee, et al. ∙

∙ 10/12/2022

On Divergence Measures for Bayesian Pseudocoresets

A Bayesian pseudocoreset is a small synthetic dataset for which the post...

17 Balhae Kim, et al. ∙

∙ 02/07/2022

Diversify and Disambiguate: Learning From Underspecified Data

Many datasets are underspecified, which means there are several equally ...

11 Yoonho Lee, et al. ∙

∙ 10/27/2021

Diversity Matters When Learning From Ensembles

Deep ensembles excel in large-scale image classification tasks both in t...

0 Giung Nam, et al. ∙

∙ 07/05/2021

On The Distribution of Penultimate Activations of Classification Networks

This paper studies probability distributions of penultimate activations ...

0 Minkyo Seo, et al. ∙

∙ 10/29/2020

Attentive Clustering Processes

Amortized approaches to clustering have recently received renewed attent...

11 Ari Pakman, et al. ∙

∙ 08/07/2020

Bootstrapping Neural Processes

Unlike in the traditional statistical modeling for which a user typicall...

1 Juho Lee, et al. ∙

∙ 08/07/2020

Neural Complexity Measures

While various complexity measures for diverse model classes have been pr...

24 Yoonho Lee, et al. ∙

∙ 09/30/2019

Deep Amortized Clustering

We propose a deep amortized clustering (DAC), a neural architecture whic...

30 Juho Lee, et al. ∙

∙ 05/28/2019

Learning Dynamics of Attention: Human Prior for Interpretable Machine Reasoning

Without relevant human priors, neural networks may learn uninterpretable...

0 Wonjae Kim, et al. ∙

∙ 05/28/2019

Discrete Infomax Codes for Meta-Learning

Learning compact discrete representations of data is itself a key task i...

0 Yoonho Lee, et al. ∙

∙ 10/01/2018

Set Transformer

Many machine learning tasks such as multiple instance learning, 3D shape...

10 Juho Lee, et al. ∙

∙ 01/17/2018

Meta-Learning with Adaptive Layerwise Metric and Subspace

Recent advances in meta-learning demonstrate that deep representations c...

0 Yoonho Lee, et al. ∙

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