David Tedaldi
David Tedaldi
Cisco Systems, ETHZ
Verified email at student.ethz.ch - Homepage
Title
Cited by
Cited by
Year
A robust and easy to implement method for IMU calibration without external equipments
D Tedaldi, A Pretto, E Menegatti
2014 IEEE International Conference on Robotics and Automation (ICRA), 3042-3049, 2014
1732014
Feature detection and tracking with the dynamic and active-pixel vision sensor (DAVIS)
D Tedaldi, G Gallego, E Mueggler, D Scaramuzza
2016 Second International Conference on Event-based Control, Communication …, 2016
752016
Deep learning architecture for collaborative anomaly detection and explanation
G Mermoud, D Tedaldi, JP Vasseur
US Patent 10,574,512, 2020
12020
Anomaly detection with root cause learning in a network assurance service
G Mermoud, JP Vasseur, D Tedaldi
US Patent App. 15/983,615, 2019
12019
Unsupervised learning of local-aware attribute relevance for device classification and clustering
G Mermoud, D Tedaldi, PA Savalle, JP Vasseur, JN Diemand
US Patent App. 16/830,717, 2021
2021
Protecting device classification systems from adversarial endpoints
JP Vasseur, G Mermoud, PA Savalle, D Tedaldi
US Patent App. 16/823,650, 2021
2021
Compressed transmission of network data for networking machine learning systems
MY Raghuprasad, D Tedaldi, VK Kolar, JP Vasseur
US Patent App. 16/808,896, 2021
2021
Learning packet capture policies to enrich context for device classification systems
JP Vasseur, D Tedaldi, G Mermoud, PA Savalle
US Patent 11,018,943, 2021
2021
Learning when to reuse existing rules in active labeling for device classification
PA Savalle, JP Vasseur, G Mermoud, D Tedaldi, JN Diemand, SB Martin
US Patent 10,999,146, 2021
2021
Learning robust and accurate rules for device classification from clusters of devices
D Tedaldi, G Mermoud, PA Savalle, JP Vasseur
US Patent App. 17/142,447, 2021
2021
Systems and methods for application traffic simulation using captured flows
DJ Zacks, T Szigeti, T Peleg, D Tedaldi, VV Pendhar
US Patent 10,944,641, 2021
2021
Learning robust and accurate rules for device classification from clusters of devices
D Tedaldi, G Mermoud, PA Savalle, JP Vasseur
US Patent 10,917,302, 2021
2021
Device type classification using metric learning in weakly supervised settings
D Tedaldi, PA Savalle, SS Wulff, JP Vasseur, G Mermoud
US Patent App. 16/434,274, 2020
2020
Predicting network states for answering what-if scenario outcomes
D Tedaldi, G Mermoud, VK Kolar, JP Vasseur, PA Savalle
US Patent App. 16/431,782, 2020
2020
Detection and resolution of rule conflicts in device classification systems
G Mermoud, JP Vasseur, PA Savalle, D Tedaldi
US Patent App. 16/428,202, 2020
2020
Continuous validation of active labeling for device type classification
JP Vasseur, PA Savalle, G Mermoud, D Tedaldi
US Patent App. 16/404,153, 2020
2020
Learning stable representations of devices for clustering-based device classification systems
D Tedaldi, G Mermoud, PA Savalle, JP Vasseur
US Patent App. 16/389,013, 2020
2020
Using random forests to generate rules for causation analysis of network anomalies
D Tedaldi, G Mermoud, JP Vasseur
US Patent 10,771,313, 2020
2020
Active learning for interactive labeling of new device types based on limited feedback
G Mermoud, PA Savalle, JP Vasseur, D Tedaldi
US Patent App. 16/194,442, 2020
2020
Anomaly severity scoring in a network assurance service
JP Vasseur, G Mermoud, D Tedaldi, SG Pandey
US Patent App. 15/996,628, 2019
2019
The system can't perform the operation now. Try again later.
Articles 1–20