Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning
Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning
 
AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks
AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks
 
signSGD via Zeroth-Order Oracle
signSGD via Zeroth-Order Oracle
 
Adversarial T-shirt! Evading Person Detectors in A Physical World
Adversarial T-shirt! Evading Person Detectors in A Physical World
 
CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks
CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks
 
On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning
On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning
 
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach
 
Neural Network Robustness Certification with General Activation Functions
Neural Network Robustness Certification with General Activation Functions
 
Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case
Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case
 
Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases
Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases
 
Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing
Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing
 
Self-Progressing Robust Training
Self-Progressing Robust Training
 
Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization
Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization
 
Higher-Order Certification For Randomized Smoothing
Higher-Order Certification For Randomized Smoothing
 
On the Design of Black-box Adversarial Examples by Leveraging Gradient-free Optimization and Operator Splitting Method
On the Design of Black-box Adversarial Examples by Leveraging Gradient-free Optimization and Operator Splitting Method
 
Structured Adversarial Attack: Towards General Implementation and Better Interpretability
Structured Adversarial Attack: Towards General Implementation and Better Interpretability
 
Hidden Cost of Randomized Smoothing
Hidden Cost of Randomized Smoothing
 
MCUNet: Tiny Deep Learning on IoT Devices
MCUNet: Tiny Deep Learning on IoT Devices
 
Training Stronger Baselines for Learning to Optimize
Training Stronger Baselines for Learning to Optimize
 
Robust Overfitting may be mitigated by properly learned smoothening
Robust Overfitting may be mitigated by properly learned smoothening
 
Deep Analysis of CNN-based Spatio-temporal Representations for Action Recognition
Deep Analysis of CNN-based Spatio-temporal Representations for Action Recognition
 
RT3D: Achieving Real-Time Execution of 3D Convolutional Neural Networks on Mobile Devices
RT3D: Achieving Real-Time Execution of 3D Convolutional Neural Networks on Mobile Devices
 
Foley Music: Learning to Generate Music from Videos
Foley Music: Learning to Generate Music from Videos
 
Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport
Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport
 
NASTransfer: Analyzing Architecture Transferability in Large Scale Neural Architecture Search
NASTransfer: Analyzing Architecture Transferability in Large Scale Neural Architecture Search
 
Long Live the Lottery: The Existence of Winning Tickets in Lifelong Learning
Long Live the Lottery: The Existence of Winning Tickets in Lifelong Learning
 
An Image Enhancing Pattern-based Sparsity for Real-time Inference on Mobile Devices
An Image Enhancing Pattern-based Sparsity for Real-time Inference on Mobile Devices
 
Graph Universal Adversarial Attacks: A Few Bad Actors Ruin Graph Learning Models
Graph Universal Adversarial Attacks: A Few Bad Actors Ruin Graph Learning Models
 
Grounding Physical Concepts of Objects and Events Through Dynamic Visual Reasoning
Grounding Physical Concepts of Objects and Events Through Dynamic Visual Reasoning
 
The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models
The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models
 
Self-supervised Moving Vehicle Tracking with Stereo Sound
Self-supervised Moving Vehicle Tracking with Stereo Sound
 
RSPNet: Relative Speed Perception for Unsupervised Video Representation Learning.
RSPNet: Relative Speed Perception for Unsupervised Video Representation Learning.
 
Debiased Contrastive Learning
Debiased Contrastive Learning
 
The Lottery Ticket Hypothesis for the Pre-trained BERT Networks
The Lottery Ticket Hypothesis for the Pre-trained BERT Networks
 
Deep Symbolic Superoptimization Without Human Knowledge
Deep Symbolic Superoptimization Without Human Knowledge
 
EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs
EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs
 
ZO-AdaMM: Derivative-free optimization for black-box problems
ZO-AdaMM: Derivative-free optimization for black-box problems
 
Big-Little-Video-Net: Work smarter, not harder, for video understanding
Big-Little-Video-Net: Work smarter, not harder, for video understanding
 
Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics
Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics
 
On the Convergence of A Class of Adam-Type Algorithms for Non-Convex Optimization
On the Convergence of A Class of Adam-Type Algorithms for Non-Convex Optimization
 
Scalable Graph Learning for Anti-Money Laundering: A First Look
Scalable Graph Learning for Anti-Money Laundering: A First Look
 
Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders
Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders
 
Embedding Compression with Isotropic Iterative Quantization
Embedding Compression with Isotropic Iterative Quantization
 
Online AI planning with graph neural networks and adaptive scheduling
Online AI planning with graph neural networks and adaptive scheduling
 
Fast and efficient black-box testing for AI cybersecurity
Fast and efficient black-box testing for AI cybersecurity