31 citations
- Simon Fraser UniversityCA4 papers
- University of British ColumbiaCA3 papers
- Google (United States)US2 papers
- Brown UniversityUS1 paper
- Centrum Wiskunde & InformaticaNL1 paper
- Imperial College LondonGB1 paper
- Institute for Cognitive Science StudiesIR1 paper
- McGill UniversityCA1 paper
- North Carolina State UniversityUS1 paper
- University of TorontoCA1 paper
- University of WaterlooCA1 paper
- Vector InstituteCA1 paper
13 papers
TD-GEN: Graph Generation With Tree Decomposition
Hamed Shirzad, Hossein Hajimirsadeghi, Amir H. Abdi +1
We propose TD-GEN, a graph generation framework based on tree decomposition, and introduce a reduced upper bound on the maximum number of decisions needed for graph generation. The…
Learning Discriminative Prototypes with Dynamic Time Warping
Xiaobin Chang, Frederick Tung, Greg Mori
Dynamic Time Warping (DTW) is widely used for temporal data processing. However, existing methods can neither learn the discriminative prototypes of different classes nor exploit s…
SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks
Bahare Fatemi, Layla El Asri, Seyed Mehran Kazemi
Graph neural networks (GNNs) work well when the graph structure is provided. However, this structure may not always be available in real-world applications. One solution to this pr…
Adversarial Stylometry in the Wild: Transferable Lexical Substitution Attacks on Author Profiling
Chris Emmery, Ákos Kádár, Grzegorz Chrupała
Written language contains stylistic cues that can be exploited to automatically infer a variety of potentially sensitive author information. Adversarial stylometry intends to attac…
CDT: Cascading Decision Trees for Explainable Reinforcement Learning
Zihan Ding, Pablo Hernandez-Leal, Gavin Weiguang Ding +2
Deep Reinforcement Learning (DRL) has recently achieved significant advances in various domains. However, explaining the policy of RL agents still remains an open problem due to se…
PermuteAttack: Counterfactual Explanation of Machine Learning Credit Scorecards
Masoud Hashemi, Ali Fathi
This paper is a note on new directions and methodologies for validation and explanation of Machine Learning (ML) models employed for retail credit scoring in finance. Our proposed…