23.6k citations
- Carnegie Mellon UniversityUS49 papers
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22 papers · 2 filters
Learning to Navigate the Web
Izzeddin Gur, Ulrich Rueckert, Aleksandra Faust +1
Learning in environments with large state and action spaces, and sparse rewards, can hinder a Reinforcement Learning (RL) agent's learning through trial-and-error. For instance, fo…
Trust Region Based Adversarial Attack on Neural Networks
Zhewei Yao, Amir Gholami, Peng Xu +2
Deep Neural Networks are quite vulnerable to adversarial perturbations. Current state-of-the-art adversarial attack methods typically require very time consuming hyper-parameter tu…
Transferring Knowledge across Learning Processes
Sebastian Flennerhag, Pablo G. Moreno, Neil D. Lawrence +1
In complex transfer learning scenarios new tasks might not be tightly linked to previous tasks. Approaches that transfer information contained only in the final parameters of a sou…
Benchmarking datasets for Anomaly-based Network Intrusion Detection: KDD CUP 99 alternatives
Abhishek Divekar, Meet Parekh, Vaibhav Savla +2
Machine Learning has been steadily gaining traction for its use in Anomaly-based Network Intrusion Detection Systems (A-NIDS). Research into this domain is frequently performed usi…
An Efficient Bandit Algorithm for Realtime Multivariate Optimization
Daniel N Hill, Houssam Nassif, Yi Liu +2
Optimization is commonly employed to determine the content of web pages, such as to maximize conversions on landing pages or click-through rates on search engine result pages. Ofte…
Generative Low-Shot Network Expansion
Adi Hayat, Mark Kliger, Shachar Fleishman +1
Conventional deep learning classifiers are static in the sense that they are trained on a predefined set of classes and learning to classify a novel class typically requires re-tra…