b'Kevin Lin'

Mesh Graphormer

We present a graph-convolution-reinforced transformer, named Mesh Grapho...
04/01/2021 ∙ by Kevin Lin, et al. ∙ 0 ∙ share

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Do Abstractions Have Politics? Towards a More Critical Algorithm Analysis

The expansion of computer science (CS) education in K–12 and higher-educ...
01/04/2021 ∙ by Kevin Lin, et al. ∙ 0 ∙ share

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End-to-End Human Pose and Mesh Reconstruction with Transformers

We present a new method, called MEsh TRansfOrmer (METRO), to reconstruct...
12/17/2020 ∙ by Kevin Lin, et al. ∙ 0 ∙ share

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Nifty Web Apps: Build a Web App for Any Text-Based Programming Assignment

While many students now interact with web apps across a variety of smart...
10/09/2020 ∙ by Kevin Lin, et al. ∙ 0 ∙ share

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VIVO: Surpassing Human Performance in Novel Object Captioning with Visual Vocabulary Pre-Training

It is highly desirable yet challenging to generate image captions that c...
09/28/2020 ∙ by Xiaowei Hu, et al. ∙ 1 ∙ share

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A Berkeley View of Teaching CS at Scale

Over the past decade, undergraduate Computer Science (CS) programs acros...
04/28/2020 ∙ by Kevin Lin, et al. ∙ 0 ∙ share

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Evaluating NLP Models via Contrast Sets

Standard test sets for supervised learning evaluate in-distribution gene...
04/06/2020 ∙ by Matt Gardner, et al. ∙ 0 ∙ share

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Learning Nonparametric Human Mesh Reconstruction from a Single Image without Ground Truth Meshes

Nonparametric approaches have shown promising results on reconstructing ...
02/28/2020 ∙ by Kevin Lin, et al. ∙ 0 ∙ share

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Train Large, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers

Since hardware resources are limited, the objective of training deep lea...
02/26/2020 ∙ by Zhuohan Li, et al. ∙ 0 ∙ share

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Learning to Generate Multiple Style Transfer Outputs for an Input Sentence

Text style transfer refers to the task of rephrasing a given text in a d...
02/16/2020 ∙ by Kevin Lin, et al. ∙ 0 ∙ share

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Neural Module Networks for Reasoning over Text

Answering compositional questions that require multiple steps of reasoni...
12/10/2019 ∙ by Nitish Gupta, et al. ∙ 0 ∙ share

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QuaRTz: An Open-Domain Dataset of Qualitative Relationship Questions

We introduce the first open-domain dataset, called QuaRTz, for reasoning...
09/08/2019 ∙ by Oyvind Tafjord, et al. ∙ 0 ∙ share

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Reasoning Over Paragraph Effects in Situations

A key component of successfully reading a passage of text is the ability...
08/16/2019 ∙ by Kevin Lin, et al. ∙ 0 ∙ share

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Cross-Domain Complementary Learning with Synthetic Data for Multi-Person Part Segmentation

The success of supervised deep learning depends on the training labels. ...
07/11/2019 ∙ by Kevin Lin, et al. ∙ 1 ∙ share

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Statistically and Computationally Efficient Change Point Localization in Regression Settings

Detecting when the underlying distribution changes from the observed tim...
06/26/2019 ∙ by Daren Wang, et al. ∙ 0 ∙ share

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Grammar-based Neural Text-to-SQL Generation

The sequence-to-sequence paradigm employed by neural text-to-SQL models ...
05/30/2019 ∙ by Kevin Lin, et al. ∙ 0 ∙ share

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Subgoals, Problem Solving Phases, and Sources of Knowledge: A Complex Mangle

Educational researchers have increasingly drawn attention to how student...
01/05/2019 ∙ by Kevin Lin, et al. ∙ 0 ∙ share

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Covariance-based sample selection for heterogenous data: Applications to gene expression and autism risk gene detection

Risk for autism can be influenced by genetic mutations in hundreds of ge...
12/19/2018 ∙ by Kevin Lin, et al. ∙ 0 ∙ share

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Post-Selection Inference for Changepoint Detection Algorithms with Application to Copy Number Variation Data

Changepoint detection methods are used in many areas of science and engi...
12/10/2018 ∙ by Sangwon Hyun, et al. ∙ 0 ∙ share

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DeepBase: Deep Inspection of Neural Networks

Although deep learning models perform remarkably across a range of tasks...
08/13/2018 ∙ by Thibault Sellam, et al. ∙ 0 ∙ share

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Adversarial Learning for Fine-grained Image Search

Fine-grained image search is still a challenging problem due to the diff...
07/06/2018 ∙ by Kevin Lin, et al. ∙ 0 ∙ share

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Adversarial Ranking for Language Generation

Generative adversarial networks (GANs) have great successes on synthesiz...
05/31/2017 ∙ by Kevin Lin, et al. ∙ 0 ∙ share

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Supervised Learning of Semantics-Preserving Hash via Deep Convolutional Neural Networks

This paper presents a simple yet effective supervised deep hash approach...
07/01/2015 ∙ by Huei-Fang Yang, et al. ∙ 0 ∙ share

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Optimization for Compressed Sensing: the Simplex Method and Kronecker Sparsification

In this paper we present two new approaches to efficiently solve large-s...
12/16/2013 ∙ by Robert Vanderbei, et al. ∙ 0 ∙ share

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Kevin Lin

Featured Co-authors

Lei Zhang

Jianfeng Gao

Fan Yang

Jan Kautz

Han Liu

Dan Roth

Noah A. Smith

Kurt Keutzer

Xiaodong He

Joseph E. Gonzalez

Jonathan Berant

Mesh Graphormer

Do Abstractions Have Politics? Towards a More Critical Algorithm Analysis

End-to-End Human Pose and Mesh Reconstruction with Transformers

Nifty Web Apps: Build a Web App for Any Text-Based Programming Assignment

VIVO: Surpassing Human Performance in Novel Object Captioning with Visual Vocabulary Pre-Training

A Berkeley View of Teaching CS at Scale

Evaluating NLP Models via Contrast Sets

Learning Nonparametric Human Mesh Reconstruction from a Single Image without Ground Truth Meshes

Train Large, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers

Learning to Generate Multiple Style Transfer Outputs for an Input Sentence

Neural Module Networks for Reasoning over Text

QuaRTz: An Open-Domain Dataset of Qualitative Relationship Questions

Reasoning Over Paragraph Effects in Situations

Cross-Domain Complementary Learning with Synthetic Data for Multi-Person Part Segmentation

Statistically and Computationally Efficient Change Point Localization in Regression Settings

Grammar-based Neural Text-to-SQL Generation

Subgoals, Problem Solving Phases, and Sources of Knowledge: A Complex Mangle

Covariance-based sample selection for heterogenous data: Applications to gene expression and autism risk gene detection

Post-Selection Inference for Changepoint Detection Algorithms with Application to Copy Number Variation Data

DeepBase: Deep Inspection of Neural Networks

Adversarial Learning for Fine-grained Image Search

Adversarial Ranking for Language Generation

Supervised Learning of Semantics-Preserving Hash via Deep Convolutional Neural Networks

Optimization for Compressed Sensing: the Simplex Method and Kronecker Sparsification