3 citations · 3 across the 4 of their papers we have counts for
9 papers
Data Augmentation for Improving Tail-traffic Robustness in Skill-routing for Dialogue Systems
Ting-Wei Wu, Fatemeh Sheikholeslami, Mohammad Kachuee +2
Large-scale conversational systems typically rely on a skill-routing component to route a user request to an appropriate skill and interpretation to serve the request. In such syst…
Scalable and Safe Remediation of Defective Actions in Self-Learning Conversational Systems
Sarthak Ahuja, Mohammad Kachuee, Fateme Sheikholeslami +2
Off-Policy reinforcement learning has been a driving force for the state-of-the-art conversational AIs leading to more natural humanagent interactions and improving the user satisf…
Improving Adversarial Robustness via Joint Classification and Multiple Explicit Detection Classes
Sina Baharlouei, Fatemeh Sheikholeslami, Meisam Razaviyayn +1
This work concerns the development of deep networks that are certifiably robust to adversarial attacks. Joint robust classification-detection was recently introduced as a certified…
You Only Query Once: Effective Black Box Adversarial Attacks with Minimal Repeated Queries
Devin Willmott, Anit Kumar Sahu, Fatemeh Sheikholeslami +2
Researchers have repeatedly shown that it is possible to craft adversarial attacks on deep classifiers (small perturbations that significantly change the class label), even in the…
Reinforcement Learning for Caching with Space-Time Popularity Dynamics
Alireza Sadeghi, Georgios B. Giannakis, Gang Wang +1
With the tremendous growth of data traffic over wired and wireless networks along with the increasing number of rich-media applications, caching is envisioned to play a critical ro…
Minimum Uncertainty Based Detection of Adversaries in Deep Neural Networks
Fatemeh Sheikholeslami, Swayambhoo Jain, Georgios B. Giannakis
Despite their unprecedented performance in various domains, utilization of Deep Neural Networks (DNNs) in safety-critical environments is severely limited in the presence of even s…