b'Pin-Yu Chen'

research

∙ 09/12/2023

Exploring the Benefits of Differentially Private Pre-training and Parameter-Efficient Fine-tuning for Table Transformers

For machine learning with tabular data, Table Transformer (TabTransforme...

0 Xilong Wang, et al. ∙

research

∙ 09/12/2023

Prompting4Debugging: Red-Teaming Text-to-Image Diffusion Models by Finding Problematic Prompts

Text-to-image diffusion models, e.g. Stable Diffusion (SD), lately have ...

0 Zhi-Yi Chin, et al. ∙

research

∙ 09/03/2023

Spectral Adversarial MixUp for Few-Shot Unsupervised Domain Adaptation

Domain shift is a common problem in clinical applications, where the tra...

0 Jiajin Zhang, et al. ∙

research

∙ 08/29/2023

Reprogramming under constraints: Revisiting efficient and reliable transferability of lottery tickets

In the era of foundation models with huge pre-training budgets, the down...

0 Diganta Misra, et al. ∙

research

∙ 08/19/2023

Robust Mixture-of-Expert Training for Convolutional Neural Networks

Sparsely-gated Mixture of Expert (MoE), an emerging deep model architect...

0 Yihua Zhang, et al. ∙

research

∙ 07/24/2023

Lost In Translation: Generating Adversarial Examples Robust to Round-Trip Translation

Language Models today provide a high accuracy across a large number of d...

0 Neel Bhandari, et al. ∙

research

∙ 07/07/2023

RADAR: Robust AI-Text Detection via Adversarial Learning

Recent advances in large language models (LLMs) and the intensifying pop...

0 Xiaomeng Hu, et al. ∙

research

∙ 06/29/2023

NeuralFuse: Learning to Improve the Accuracy of Access-Limited Neural Network Inference in Low-Voltage Regimes

Deep neural networks (DNNs) have become ubiquitous in machine learning, ...

0 Hao-Lun Sun, et al. ∙

research

∙ 06/12/2023

VillanDiffusion: A Unified Backdoor Attack Framework for Diffusion Models

Diffusion Models (DMs) are state-of-the-art generative models that learn...

0 Sheng Yen Chou, et al. ∙

research

∙ 06/07/2023

Patch-level Routing in Mixture-of-Experts is Provably Sample-efficient for Convolutional Neural Networks

In deep learning, mixture-of-experts (MoE) activates one or few experts ...

8 Mohammed Nowaz Rabbani Chowdhury, et al. ∙

research

∙ 05/26/2023

Diagnostic Spatio-temporal Transformer with Faithful Encoding

This paper addresses the task of anomaly diagnosis when the underlying d...

0 Jokin Labaien, et al. ∙

research

∙ 05/25/2023

Which Features are Learnt by Contrastive Learning? On the Role of Simplicity Bias in Class Collapse and Feature Suppression

Contrastive learning (CL) has emerged as a powerful technique for repres...

0 Yihao Xue, et al. ∙

research

∙ 05/24/2023

Uncovering and Quantifying Social Biases in Code Generation

With the popularity of automatic code generation tools, such as Copilot,...

0 Yan Liu, et al. ∙

research

∙ 04/19/2023

GREAT Score: Global Robustness Evaluation of Adversarial Perturbation using Generative Models

Current studies on adversarial robustness mainly focus on aggregating lo...

0 Li Zaitang, et al. ∙

research

∙ 04/11/2023

Overload: Latency Attacks on Object Detection for Edge Devices

Nowadays, the deployment of deep learning based applications on edge dev...

0 Erh-Chung Chen, et al. ∙

research

∙ 03/22/2023

Exploring the Benefits of Visual Prompting in Differential Privacy

Visual Prompting (VP) is an emerging and powerful technique that allows ...

0 Yizhe Li, et al. ∙

research

∙ 03/03/2023

Convex Bounds on the Softmax Function with Applications to Robustness Verification

The softmax function is a ubiquitous component at the output of neural n...

0 Dennis Wei, et al. ∙

research

∙ 02/12/2023

A Theoretical Understanding of shallow Vision Transformers: Learning, Generalization, and Sample Complexity

Vision Transformers (ViTs) with self-attention modules have recently ach...

4 Hongkang Li, et al. ∙

research

∙ 02/06/2023

Joint Edge-Model Sparse Learning is Provably Efficient for Graph Neural Networks

Due to the significant computational challenge of training large-scale g...

0 Shuai Zhang, et al. ∙

research

∙ 01/26/2023

Certified Interpretability Robustness for Class Activation Mapping

Interpreting machine learning models is challenging but crucial for ensu...

4 Alex Gu, et al. ∙

research

∙ 01/08/2023

AI Maintenance: A Robustness Perspective

With the advancements in machine learning (ML) methods and compute resou...

5 Pin-Yu Chen, et al. ∙

research

∙ 01/05/2023

Reprogramming Pretrained Language Models for Protein Sequence Representation Learning

Machine Learning-guided solutions for protein learning tasks have made s...

32 Ria Vinod, et al. ∙

research

∙ 12/19/2022

Stochastic Inexact Augmented Lagrangian Method for Nonconvex Expectation Constrained Optimization

Many real-world problems not only have complicated nonconvex functional ...

0 Zichong Li, et al. ∙

research

∙ 12/16/2022

On Human Visual Contrast Sensitivity and Machine Vision Robustness: A Comparative Study

It is well established in neuroscience that color vision plays an essent...

0 Ming-Chang Chiu, et al. ∙

research

∙ 12/16/2022

Better May Not Be Fairer: Can Data Augmentation Mitigate Subgroup Degradation?

It is no secret that deep learning models exhibit undesirable behaviors ...

0 Ming-Chang Chiu, et al. ∙

research

∙ 12/11/2022

How to Backdoor Diffusion Models?

Diffusion models are state-of-the-art deep learning empowered generative...

0 Sheng Yen Chou, et al. ∙

research

∙ 12/01/2022

When Neural Networks Fail to Generalize? A Model Sensitivity Perspective

Domain generalization (DG) aims to train a model to perform well in unse...

16 Jiajin Zhang, et al. ∙

research

∙ 11/29/2022

NCTV: Neural Clamping Toolkit and Visualization for Neural Network Calibration

With the advancement of deep learning technology, neural networks have d...

0 Lei Hsiung, et al. ∙

research

∙ 11/21/2022

Understanding and Improving Visual Prompting: A Label-Mapping Perspective

We revisit and advance visual prompting (VP), an input prompting techniq...

9 Aochuan Chen, et al. ∙

research

∙ 11/02/2022

Low-Resource Music Genre Classification with Advanced Neural Model Reprogramming

Transfer learning (TL) approaches have shown promising results when hand...

0 Yun-Ning Hung, et al. ∙

research

∙ 11/02/2022

Inference and Denoise: Causal Inference-based Neural Speech Enhancement

This study addresses the speech enhancement (SE) task within the causal ...

0 Tsun-An Hsieh, et al. ∙

research

∙ 11/02/2022

Certified Robustness of Quantum Classifiers against Adversarial Examples through Quantum Noise

Recently, quantum classifiers have been known to be vulnerable to advers...

0 Jhih-Cing Huang, et al. ∙

research

∙ 10/27/2022

An Empirical Evaluation of Zeroth-Order Optimization Methods on AI-driven Molecule Optimization

Molecule optimization is an important problem in chemical discovery and ...

0 Elvin Lo, et al. ∙

research

∙ 10/23/2022

FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning

Federated Learning (FL) is a distributed learning paradigm that enables ...

1 Kaiyuan Zhang, et al. ∙

research

∙ 10/12/2022

Visual Prompting for Adversarial Robustness

In this work, we leverage visual prompting (VP) to improve adversarial r...

21 Aochuan Chen, et al. ∙

research

∙ 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. ∙

research

∙ 09/23/2022

Neural Clamping: Joint Input Perturbation and Temperature Scaling for Neural Network Calibration

Neural network calibration is an essential task in deep learning to ensu...

0 Yung-Chen Tang, et al. ∙

research

∙ 09/22/2022

Iterative Qubits Management for Quantum Index Searching in a Hybrid System

Recent advances in quantum computing systems attract tremendous attentio...

0 Wenrui Mu, et al. ∙

research

∙ 09/08/2022

Uncovering the Connection Between Differential Privacy and Certified Robustness of Federated Learning against Poisoning Attacks

Federated learning (FL) provides an efficient paradigm to jointly train ...

11 Chulin Xie, et al. ∙

research

∙ 08/31/2022

Be Your Own Neighborhood: Detecting Adversarial Example by the Neighborhood Relations Built on Self-Supervised Learning

Deep Neural Networks (DNNs) have achieved excellent performance in vario...

0 Zhiyuan He, et al. ∙

research

∙ 08/10/2022

Active Sampling of Multiple Sources for Sequential Estimation

Consider K processes, each generating a sequence of identical and indepe...

5 Arpan Mukherjee, et al. ∙

research

∙ 07/20/2022

Improving Privacy-Preserving Vertical Federated Learning by Efficient Communication with ADMM

Federated learning (FL) enables distributed devices to jointly train a s...

4 Chulin Xie, et al. ∙

research

∙ 07/16/2022

CARBEN: Composite Adversarial Robustness Benchmark

Prior literature on adversarial attack methods has mainly focused on att...

0 Lei Hsiung, et al. ∙

research

∙ 07/07/2022

Generalization Guarantee of Training Graph Convolutional Networks with Graph Topology Sampling

Graph convolutional networks (GCNs) have recently achieved great empiric...

6 Hongkang Li, et al. ∙

research

∙ 06/15/2022

Linearity Grafting: Relaxed Neuron Pruning Helps Certifiable Robustness

Certifiable robustness is a highly desirable property for adopting deep ...

4 Tianlong Chen, et al. ∙

research

∙ 06/13/2022

Distributed Adversarial Training to Robustify Deep Neural Networks at Scale

Current deep neural networks (DNNs) are vulnerable to adversarial attack...

15 Gaoyuan Zhang, et al. ∙

research

∙ 06/08/2022

Sharp-MAML: Sharpness-Aware Model-Agnostic Meta Learning

Model-agnostic meta learning (MAML) is currently one of the dominating a...

9 Momin Abbas, et al. ∙

research

∙ 06/08/2022

Theoretical Error Performance Analysis for Variational Quantum Circuit Based Functional Regression

The noisy intermediate-scale quantum (NISQ) devices enable the implement...

0 Jun Qi, et al. ∙

research

∙ 05/20/2022

Learning Geometrically Disentangled Representations of Protein Folding Simulations

Massive molecular simulations of drug-target proteins have been used as ...

12 N. Joseph Tatro, et al. ∙

research

∙ 05/01/2022

A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock Prediction

More and more investors and machine learning models rely on social media...

3 Yong Xie, et al. ∙

Pin-Yu Chen

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