Ching-Yun Ko | DeepAI

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Pin-Yu Chen
183 publications
Dahua Lin
142 publications
Sijia Liu
112 publications
Payel Das
56 publications
Polina Golland
55 publications
Hao Yu
43 publications
Ngai Wong
29 publications
Tsui-Wei Weng
25 publications
Luca Daniel
25 publications
Wenjian Yu
21 publications
Yuan Cheng
20 publications

∙ 04/25/2023

Sample-Specific Debiasing for Better Image-Text Models

Self-supervised representation learning on image-text data facilitates c...

0 Peiqi Wang, et al. ∙

∙ 10/06/2022

SynBench: Task-Agnostic Benchmarking of Pretrained Representations using Synthetic Data

Recent success in fine-tuning large models, that are pretrained on broad...

2 Ching-Yun Ko, et al. ∙

∙ 06/30/2022

Visual Pre-training for Navigation: What Can We Learn from Noise?

A powerful paradigm for sensorimotor control is to predict actions from ...

0 Yanwei Wang, et al. ∙

∙ 12/08/2021

Revisiting Contrastive Learning through the Lens of Neighborhood Component Analysis: an Integrated Framework

As a seminal tool in self-supervised representation learning, contrastiv...

7 Ching-Yun Ko, et al. ∙

∙ 10/13/2020

Higher-Order Certification for Randomized Smoothing

Randomized smoothing is a recently proposed defense against adversarial ...

6 Jeet Mohapatra, et al. ∙

∙ 03/02/2020

Rethinking Randomized Smoothing for Adversarial Robustness

The fragility of modern machine learning models has drawn a considerable...

5 Jeet Mohapatra, et al. ∙

∙ 02/28/2020

HOTCAKE: Higher Order Tucker Articulated Kernels for Deeper CNN Compression

The emerging edge computing has promoted immense interests in compacting...

5 Rui Lin, et al. ∙

∙ 12/02/2019

Fastened CROWN: Tightened Neural Network Robustness Certificates

The rapid growth of deep learning applications in real life is accompani...

0 Zhaoyang Lyu, et al. ∙

∙ 05/17/2019

MiSC: Mixed Strategies Crowdsourcing

Popular crowdsourcing techniques mostly focus on evaluating workers' lab...

0 Ching-Yun Ko, et al. ∙

∙ 05/17/2019

POPQORN: Quantifying Robustness of Recurrent Neural Networks

The vulnerability to adversarial attacks has been a critical issue for d...

0 Ching-Yun Ko, et al. ∙

∙ 11/12/2018

Matrix Product Operator Restricted Boltzmann Machines

A restricted Boltzmann machine (RBM) learns a probability distribution o...

22 Cong Chen, et al. ∙

∙ 11/09/2018

Deep Compression of Sum-Product Networks on Tensor Networks

Sum-product networks (SPNs) represent an emerging class of neural networ...

0 Ching-Yun Ko, et al. ∙

∙ 04/17/2018

Fast and Accurate Tensor Completion with Total Variation Regularized Tensor Trains

We propose a new tensor completion method based on tensor trains. The to...

0 Ching-Yun Ko, et al. ∙

∙ 04/17/2018

Fast and Accurate Tensor Completion with Tensor Trains: A System Identification Approach

We propose a novel tensor completion approach by equating it to a system...

0 Ching-Yun Ko, et al. ∙

∙ 04/17/2018

A Support Tensor Train Machine

There has been growing interest in extending traditional vector-based ma...

0 Cong Chen, et al. ∙

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