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Found 11 papers, 4 papers with code
DisDet: Exploring Detectability of Backdoor Attack on Diffusion Models
In this paper, for the first time, we systematically explore the detectability of the poisoned noise input for the backdoored diffusion models, an important performance metric yet little explored in the existing works.
Classification with neural networks with quadratic decision functions
Neural network with quadratic decision functions have been introduced as alternatives to standard neural networks with affine linear one.
Benchmarking and Analyzing Robust Point Cloud Recognition: Bag of Tricks for Defending Adversarial Examples
In this paper, we first establish a comprehensive, and rigorous point cloud adversarial robustness benchmark to evaluate adversarial robustness, which can provide a detailed understanding of the effects of the defense and attack methods.
Personalized Pricing with Invalid Instrumental Variables: Identification, Estimation, and Policy Learning
Specifically, relying on the structural models of revenue and price, we establish the identifiability condition of an optimal pricing strategy under endogeneity with the help of invalid instrumental variables.
PASTA: Pessimistic Assortment Optimization
The objective is to use the offline dataset to find an optimal assortment.
RIBAC: Towards Robust and Imperceptible Backdoor Attack against Compact DNN
Recently backdoor attack has become an emerging threat to the security of deep neural network (DNN) models.
Simultaneous Monitoring of Multiple People's Vital Sign Leveraging a Single Phased-MIMO Radar
Based on the designed TDM phased-MIMO radar, we develop a system to automatically localize multiple human subjects and estimate their vital signs.
MoNet3D: Towards Accurate Monocular 3D Object Localization in Real Time
Monocular multi-object detection and localization in 3D space has been proven to be a challenging task.
Neural Network Activation Quantization with Bitwise Information Bottlenecks
Recent researches on information bottleneck shed new light on the continuous attempts to open the black box of neural signal encoding.
Enabling Fast and Universal Audio Adversarial Attack Using Generative Model
These idealized assumptions, however, makes the existing audio adversarial attacks mostly impossible to be launched in a timely fashion in practice (e. g., playing unnoticeable adversarial perturbations along with user's streaming input).
Real-time, Universal, and Robust Adversarial Attacks Against Speaker Recognition Systems
As the popularity of voice user interface (VUI) exploded in recent years, speaker recognition system has emerged as an important medium of identifying a speaker in many security-required applications and services.
