3 papers
math.ST2026
Sharp Minimax Theory for Randomized Experiments
Timothy Sudijono, Edgar Dobriban, Eric Tchetgen Tchetgen
We study minimax-optimal designs and estimators for estimating the sample average treatment effect in finite population randomized experiments, where both design and estimator are…
quant-ph2025
Robust Decentralized Quantum Kernel Learning for Noisy and Adversarial Environment
Wenxuan Ma, Kuan-Cheng Chen, Shang Yu +2
This paper proposes a general decentralized framework for quantum kernel learning (QKL). It has robustness against quantum noise and can also be designed to defend adversarial info…
cs.CV2025
Can't Slow me Down: Learning Robust and Hardware-Adaptive Object Detectors against Latency Attacks for Edge Devices
Tianyi Wang, Zichen Wang, Cong Wang +4
Object detection is a fundamental enabler for many real-time downstream applications such as autonomous driving, augmented reality and supply chain management. However, the algorit…