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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...
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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 ...
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09/03/2023
Spectral Adversarial MixUp for Few-Shot Unsupervised Domain Adaptation
Domain shift is a common problem in clinical applications, where the tra...
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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...
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08/19/2023
Robust Mixture-of-Expert Training for Convolutional Neural Networks
Sparsely-gated Mixture of Expert (MoE), an emerging deep model architect...
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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...
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07/07/2023
RADAR: Robust AI-Text Detection via Adversarial Learning
Recent advances in large language models (LLMs) and the intensifying pop...
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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, ...
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06/12/2023
VillanDiffusion: A Unified Backdoor Attack Framework for Diffusion Models
Diffusion Models (DMs) are state-of-the-art generative models that learn...
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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 ...
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05/26/2023
Diagnostic Spatio-temporal Transformer with Faithful Encoding
This paper addresses the task of anomaly diagnosis when the underlying d...
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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...
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05/24/2023
Uncovering and Quantifying Social Biases in Code Generation
With the popularity of automatic code generation tools, such as Copilot,...
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04/19/2023
GREAT Score: Global Robustness Evaluation of Adversarial Perturbation using Generative Models
Current studies on adversarial robustness mainly focus on aggregating lo...
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04/11/2023
Overload: Latency Attacks on Object Detection for Edge Devices
Nowadays, the deployment of deep learning based applications on edge dev...
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03/22/2023
Exploring the Benefits of Visual Prompting in Differential Privacy
Visual Prompting (VP) is an emerging and powerful technique that allows ...
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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...
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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...
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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...
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01/26/2023
Certified Interpretability Robustness for Class Activation Mapping
Interpreting machine learning models is challenging but crucial for ensu...
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01/08/2023
AI Maintenance: A Robustness Perspective
With the advancements in machine learning (ML) methods and compute resou...
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01/05/2023
Reprogramming Pretrained Language Models for Protein Sequence Representation Learning
Machine Learning-guided solutions for protein learning tasks have made s...
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12/19/2022
Stochastic Inexact Augmented Lagrangian Method for Nonconvex Expectation Constrained Optimization
Many real-world problems not only have complicated nonconvex functional ...
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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...
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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 ...
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12/11/2022
How to Backdoor Diffusion Models?
Diffusion models are state-of-the-art deep learning empowered generative...
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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...
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11/29/2022
NCTV: Neural Clamping Toolkit and Visualization for Neural Network Calibration
With the advancement of deep learning technology, neural networks have d...
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11/21/2022
Understanding and Improving Visual Prompting: A Label-Mapping Perspective
We revisit and advance visual prompting (VP), an input prompting techniq...
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11/02/2022
Low-Resource Music Genre Classification with Advanced Neural Model Reprogramming
Transfer learning (TL) approaches have shown promising results when hand...
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11/02/2022
Inference and Denoise: Causal Inference-based Neural Speech Enhancement
This study addresses the speech enhancement (SE) task within the causal ...
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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...
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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 ...
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10/23/2022
FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning
Federated Learning (FL) is a distributed learning paradigm that enables ...
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10/12/2022
Visual Prompting for Adversarial Robustness
In this work, we leverage visual prompting (VP) to improve adversarial r...
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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...
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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...
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09/22/2022
Iterative Qubits Management for Quantum Index Searching in a Hybrid System
Recent advances in quantum computing systems attract tremendous attentio...
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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 ...
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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...
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08/10/2022
Active Sampling of Multiple Sources for Sequential Estimation
Consider K processes, each generating a sequence of identical and indepe...
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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...
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07/16/2022
CARBEN: Composite Adversarial Robustness Benchmark
Prior literature on adversarial attack methods has mainly focused on att...
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07/07/2022
Generalization Guarantee of Training Graph Convolutional Networks with Graph Topology Sampling
Graph convolutional networks (GCNs) have recently achieved great empiric...
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06/15/2022
Linearity Grafting: Relaxed Neuron Pruning Helps Certifiable Robustness
Certifiable robustness is a highly desirable property for adopting deep ...
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06/13/2022
Distributed Adversarial Training to Robustify Deep Neural Networks at Scale
Current deep neural networks (DNNs) are vulnerable to adversarial attack...
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06/08/2022
Sharp-MAML: Sharpness-Aware Model-Agnostic Meta Learning
Model-agnostic meta learning (MAML) is currently one of the dominating a...
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06/08/2022
Theoretical Error Performance Analysis for Variational Quantum Circuit Based Functional Regression
The noisy intermediate-scale quantum (NISQ) devices enable the implement...
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05/20/2022
Learning Geometrically Disentangled Representations of Protein Folding Simulations
Massive molecular simulations of drug-target proteins have been used as ...
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05/01/2022
