Search Results for author: Ching-Yun Ko

Found 14 papers, 4 papers with code

Sample-Specific Debiasing for Better Image-Text Models

no code implementations25 Apr 2023 Peiqi Wang, Yingcheng Liu, Ching-Yun Ko, William M. Wells, Seth Berkowitz, Steven Horng, Polina Golland

Self-supervised representation learning on image-text data facilitates crucial medical applications, such as image classification, visual grounding, and cross-modal retrieval.

Contrastive Learning Cross-Modal Retrieval +4

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

no code implementations6 Oct 2022 Ching-Yun Ko, Pin-Yu Chen, Jeet Mohapatra, Payel Das, Luca Daniel

Given a pretrained model, the representations of data synthesized from the Gaussian mixture are used to compare with our reference to infer the quality.

Benchmarking Representation Learning

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

1 code implementation30 Jun 2022 Yanwei Wang, Ching-Yun Ko, Pulkit Agrawal

One powerful paradigm in visual navigation is to predict actions from observations directly.

Inductive Bias Navigate +1

Higher-Order Certification for Randomized Smoothing

no code implementations NeurIPS 2020 Jeet Mohapatra, Ching-Yun Ko, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel

We also provide a framework that generalizes the calculation for certification using higher-order information.

Hidden Cost of Randomized Smoothing

no code implementations2 Mar 2020 Jeet Mohapatra, Ching-Yun Ko, Tsui-Wei, Weng, Sijia Liu, Pin-Yu Chen, Luca Daniel

The fragility of modern machine learning models has drawn a considerable amount of attention from both academia and the public.

HOTCAKE: Higher Order Tucker Articulated Kernels for Deeper CNN Compression

no code implementations28 Feb 2020 Rui Lin, Ching-Yun Ko, Zhuolun He, Cong Chen, Yuan Cheng, Hao Yu, Graziano Chesi, Ngai Wong

The emerging edge computing has promoted immense interests in compacting a neural network without sacrificing much accuracy.

Edge-computing Tensor Decomposition

Fastened CROWN: Tightened Neural Network Robustness Certificates

1 code implementation2 Dec 2019 Zhaoyang Lyu, Ching-Yun Ko, Zhifeng Kong, Ngai Wong, Dahua Lin, Luca Daniel

We draw inspiration from such work and further demonstrate the optimality of deterministic CROWN (Zhang et al. 2018) solutions in a given linear programming problem under mild constraints.

POPQORN: Quantifying Robustness of Recurrent Neural Networks

2 code implementations17 May 2019 Ching-Yun Ko, Zhaoyang Lyu, Tsui-Wei Weng, Luca Daniel, Ngai Wong, Dahua Lin

The vulnerability to adversarial attacks has been a critical issue for deep neural networks.

MiSC: Mixed Strategies Crowdsourcing

no code implementations17 May 2019 Ching-Yun Ko, Rui Lin, Shu Li, Ngai Wong

Popular crowdsourcing techniques mostly focus on evaluating workers' labeling quality before adjusting their weights during label aggregation.

Matrix Product Operator Restricted Boltzmann Machines

no code implementations12 Nov 2018 Cong Chen, Kim Batselier, Ching-Yun Ko, Ngai Wong

This work presents the matrix product operator RBM (MPORBM) that utilizes a tensor network generalization of Mv/TvRBM, preserves input formats in both the visible and hidden layers, and results in higher expressive power.

Denoising Dimensionality Reduction +1

Deep Compression of Sum-Product Networks on Tensor Networks

no code implementations9 Nov 2018 Ching-Yun Ko, Cong Chen, Yuke Zhang, Kim Batselier, Ngai Wong

Sum-product networks (SPNs) represent an emerging class of neural networks with clear probabilistic semantics and superior inference speed over graphical models.

Tensor Networks

A Support Tensor Train Machine

no code implementations17 Apr 2018 Cong Chen, Kim Batselier, Ching-Yun Ko, Ngai Wong

There has been growing interest in extending traditional vector-based machine learning techniques to their tensor forms.

BIG-bench Machine Learning

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